Mary Meeker May 31, 2017 kpcb.com/InternetTrends INTERNET TRENDS 2017 CODE CONFERENCE KP INTERNET TRENDS 2017 | PAGE 2 Internet Trends 2017 1) Global Internet Trends = SolidSlowing Smartphone Growth 4-9 2) Online Advertising (+ Commerce) = Increasingly Measurable + Actionable 10-79 3) Interactive Games = Motherlode of Tech Product Innovation + Modern Learning 80-150 4) Media = Distribution Disruption @ Torrid Pace 151-177 5) The Cloud = Accelerating Change Across Enterprises 178-192 6) China Internet = Golden Age of Entertainment + Transportation 193-231 (Provided by Hillhouse Capital) 7) India Internet = Competition Continues to IntensifyConsumers Winning 232-287 8) Healthcare @ Digital Inflection Point 288-319 9) Global Public / Private Internet Companies 320-333 10) Some Macro Thoughts 334-351 11) Closing Thoughts 352-353 KP INTERNET TRENDS 2017 | PAGE 3 Thanks... Kleiner Perkins Partners Alexander Krey & Ansel Parikh - who were fearless and sometimes sleepless - helped steer the ideas / presentation we hope you find useful / learn from / improve on. Key contributors to specific content include: Noah Knauf & Nina Lu (Healthcare), Bing Gordon (Interactive Games), Alex Tran & Anjney Midha (India), Daegwon Chae (Ads + Commerce) and Alex Kurland & Lucas Swisher (Enterprise). In addition, Mood Rowghani, Eric Feng, Daniel Axelsen, Dino Becirovic and Shabih Rizvi were more than on call with help. Hillhouse Capital Especially Liang Wuhis / their contribution of the China sector of Internet Trends provides an especially thoughtful overview of the largest market of Internet users in the world Participants in Evolution of Internet Connectivity From creators to consumers who keep us on our toes 24x7...and the people who directly help us prepare this presentation... Kara & Walt For continuing to do what you do so well... KP INTERNET TRENDS 2017 | PAGE 4 GLOBAL INTERNET TRENDS = SOLID USER GROWTH SLOWING SMARTPHONE GROWTH KP INTERNET TRENDS 2017 | PAGE 5 Global Internet Trends = Solid User GrowthSlowing Smartphone Growth 1) Global Internet Users = 3.4BFlat Growth +10% vs. 10% Y/Y +8% vs. 8% Y/Y (ex. India) 2) Global Smartphone Shipments = Slowing +3% vs. +10% Y/Y 3) Global Smartphone Installed Base = Slowing +12% vs. +25% Y/Y 4) USA Internet Usage (Engagement) = Solid +4% Y/Y KP INTERNET TRENDS 2017 | PAGE 6 Source: United Nations / International Telecommunications Union, US Census Bureau. Internet user data is as of mid-year. Internet user data for: USA from Pew Research, China from CNNIC, Iran from Islamic Republic News Agency / InternetWorldStats / KPCB estimates, India from KPCB estimates based on IAMAI data, Indonesia from APJII. Global Internet Users = 3.4B @ 46% Penetration... +10% Y/Y vs. +10%...+8% Y/Y vs. +8% (Ex-India) 0% 5% 10% 15% 20% 25% 30% 35% 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 2009 2010 2011 2012 2013 2014 2015 2016 Y/Y % GrowthGlobal Internet Users (MM)Global Internet Users (MM) Y/Y Growth (%) Global Internet Users (MM), 2009 2016 KP INTERNET TRENDS 2017 | PAGE 7 Global Smartphone Unit Shipments = Continue to Slow... @ +3% Y/Y vs. +10% (2015) / +28% (2014) Source: Morgan Stanley Research (5/17) Smartphone Unit Shipments by Operating System (MM), Global, 2009 2016 0% 20% 40% 60% 80% 100% 0 300 600 900 1,200 1,500 2009 2010 2011 2012 2013 2014 2015 2016 Y/Y Growth (%)Global Smartphone Unit Shipments (MM)Android iOS Other Y/Y Growth KP INTERNET TRENDS 2017 | PAGE 8 Source: Morgan Stanley Research (5/17) Note: Owing to use of different source, prior period data may have slight adjustments vs prior reports. Smartphone installed base based on preceding 8 quarters of smartphone shipments. Global Smartphone Installed Base = 2.8B +12% Y/Y vs. +25% (2015) / +37% (2014) 0% 10% 20% 30% 40% 50% 60% 70% 0 500 1,000 1,500 2,000 2,500 3,000 3,500 2009 2010 2011 2012 2013 2014 2015 2016 Y/Y % GrowthGlobal Smartphone Installed Base (MM)Global Smartphone Installed Base (MM) Y/Y Growth (%) Global Smartphone Installed Base (MM), 2009 2016 KP INTERNET TRENDS 2017 | PAGE 9 Internet Usage (Engagement) = Solid Growth+4% Y/Y Mobile >3 Hours / Day per User vs. <1 Five Years Ago, USA Source: eMarketer 9/14 (2008-2010), eMarketer 4/15 (2011-2013), eMarketer 4/17 (2014-2016). Note: Other connected devices include OTT and game consoles. Mobile includes smartphone and tablet. Usage includes both home and work. Ages 18+; time spent with each medium includes all time spent with that medium, regardless of multitasking. Time Spent per Adult User per Day with Digital Media, USA, 2008 2016 0.2 0.3 0.4 0.3 0.3 0.3 0.3 0.4 0.4 2.2 2.3 2.4 2.6 2.5 2.3 2.2 2.2 2.2 0.3 0.3 0.4 0.8 1.6 2.3 2.6 2.8 3.1 2.7 3.0 3.2 3.7 4.3 4.9 5.1 5.4 5.6 0 1 2 3 4 5 6 2008 2009 2010 2011 2012 2013 2014 2015 2016 Hours per DayOther Connected Devices Desktop / Laptop Mobile KP INTERNET TRENDS 2017 | PAGE 10 ONLINE ADVERTISING (+ COMMERCE) = INCREASINGLY MEASURABLE + ACTIONABLE KP INTERNET TRENDS 2017 | PAGE 11 Ad Growth = Driven by Mobile KP INTERNET TRENDS 2017 | PAGE 12 Online Advertising = Growth Accelerating, +22% vs. +20% Y/Y... Mobile $ > Desktop (2016) on Higher Growth, USA Source: IAB / PWC Internet Advertising Report (2016) USA Internet Advertising ($B), 2009 2016 $23 $26 $32 $37 $43 $50 $60 $73 0% 5% 10% 15% 20% 25% 30% 35% 40% $0 $10 $20 $30 $40 $50 $60 $70 $80 2009 2010 2011 2012 2013 2014 2015 2016 % Y/Y GrowthUSA Internet Advertising ($B)Desktop Advertising Mobile Advertising Y/Y Growth KP INTERNET TRENDS 2017 | PAGE 13 Advertising $ = Shift to Usage (Mobile) Continues % of Time Spent in Media vs. % of Advertising Spending, USA, 2016 4% 9% 38% 20% 28% 12% 9% 38% 20% 21% 0% 10% 20% 30% 40% 50% Print Radio TV Internet Mobile % of Total Media Consumption Timeor Advertising SpendingTime Spent Ad Spend Total Internet Ad = $73B Of Which Mobile Ad = $37B ~$16B Opportunity in USA Source: Internet and Mobile advertising spend based on IAB and PwC data for full year 2016. Print, Radio, and TV advertising spend based on Magna Global estimates for full year 2016. Print includes newspaper and magazine. Internet (IAB) includes desktop + laptop + other connected devices. ~$16B opportunity calculated assuming Mobile (IAB) ad spend share equal its respective time spent share. Time spent share data based on eMarketer (4/17). Arrows denote Y/Y shift in percent share. Excludes out-of-home, video game, and cinema advertising. KP INTERNET TRENDS 2017 | PAGE 14 Advertising $ = Internet > TV Within 6 Months, Global Internet vs. TV Ad Spend ($B), Global, 1995-2017E $0 $50 $100 $150 $200 $250 Global Advertising Spend ($B)Global Internet Ad Spend Global TV Ad Spend Source: Zenith Advertising Expenditure Forecasts (3/17) KP INTERNET TRENDS 2017 | PAGE 15 $ $5 $10 $15 $20 $25 $30 $35 $40 $45 $50 USA Advertising Revenue ($B)$0 $5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 50,000 Google + Facebook = 85% (& Rising) Share of Internet Advertising Growth, USA Advertising Revenue ($B) and Growth Rates (%) of Google vs. Facebook vs. Other, USA, 2015 2016 2015 2016 2015 2016 2015 2016 Google Facebook Others +20% Y/Y +62% Y/Y +9% Y/Y Source: IAB / PWC Advertising Report (2016), Facebook, Morgan Stanley Research Note: Facebook revenue includes Canada. Google USA ad revenue per Morgan Stanley estimates as company only discloses total ad revenue and total USA revenue. "Others" includes all other USA internet (mobile + desktop) advertising revenue ex-Google / Facebook. KP INTERNET TRENDS 2017 | PAGE 16 Ad Measurability = Can Be Triple-Edged When Things Are Measured = People Don't Always Like What They See Users Don't Always Like Data Collected KP INTERNET TRENDS 2017 | PAGE 17 56% 21% 15% 0% 10% 20% 30% 40% 50% 60% 70% Engagement Conversion & Revenue Amplification & Brand Awareness % of RespondentsAdvertisers = Like Measurable Engagement Metrics But Some Find Measuring ROI Challenging (as with Offline) Social Advertisers Metrics Used to Measure Success, 6/16 Social Media Marketing Top Challenges, 6/16 61% 38% 34% 0% 10% 20% 30% 40% 50% 60% 70% Measuring ROI Securing Budget & Resources Tying Social Campaigns to Business Goals % of RespondentsSource: SimplyMeasured State of Social Marketing Annual Report (6/16) Note: Based on a survey of social media advertisers, n=350. KP INTERNET TRENDS 2017 | PAGE 18 Ad Blocking = Growth ContinuesEspecially in Developing Markets Users Increasingly Opt Out of Stuff They Don't Want 0 100 200 300 400 2009 2010 2011 2012 2013 2014 2015 2016 Global AdblockingUsers (MM)Desktop Adblocking Software Users Mobile Adblocking Browser Users Adblocking Users on Web (Mobile + Desktop), Global, 4/09 12/16 Adblocking Penetration (Mobile + Desktop), Selected Countries, 12/16 Country Desktop Mobile China 1% 13% India 1% 28% USA 18% 1% Brazil 6% 1% Japan 3% -- Russia 6% 3% Germany 28% 1% Indonesia 8% 58% UK 16% 1% France 11% 1% Canada 24% -- Source: PageFair 2015, 2017 reports. These two data sets have not been de-duplicated. The number of desktop adblockers after 1/16 are estimates based on the observed trend in desktop adblocking and provided by PageFair. Note that mobile adblocking refers to web / browser-based adblocking and not in-app adblocking. Desktop adblocking estimates are for global monthly active users of desktop adblocking software between 4/09 12/16, as calculated in the PageFair's 2015 and 2017 reports. Mobile adblocking estimates are for global monthly active users of mobile browsers that block ads by default between 9/14 12/16, including the number of Digicel subscribers in the Caribbean (added 10/15), as calculated in the PageFair & Priori Data 2016 and PageFair 2017 Adblocking Report. KP INTERNET TRENDS 2017 | PAGE 19 Leading Platform Ad Offerings = Rapidly Improving with Back-End Data + Front-End Measurement Tools + Targeted Delivery of Ads Users Increasingly Want KP INTERNET TRENDS 2017 | PAGE 20 Source: Facebook, Google, Snap Leading Online Ad Platforms = Providing More Ways to Target + Measure Ads Facebook (Delivery Insights) Google (AdWords) Snap (Snap Ads) KP INTERNET TRENDS 2017 | PAGE 21 Product Listing Ads (Google) = Driving Clicks to Product Pages Google Product Listing Ads (PLAs) Share of Retail Paid Clicks on Google, USA, 2014-2016 29% 52% 0% 10% 20% 30% 40% 50% 60% PLA Share of Retail Paid Clicks on Google (%)Google PLA on Mobile Web, 12/16 Source: Merkle Digital Marketing Report (Q1:14-Q1:17), Right image: Search Engine Land KP INTERNET TRENDS 2017 | PAGE 22 Targeted Pins (Pinterest) = Driving Product Discovery + Purchase Pinterest Browsing Turning into Buying, 4/17 33% 12% 44% 24% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% Browse Buy % of Respondents4/15 4/17 Which of these services is a great place to browse for things you might want to buy? Which of these services is a great place to buy things online? Shop the Look Inspired Purchases, 2/17 Source: Pinterest Note: Based on an internal survey of global internet users, n=12K. Other answers to the questions include Facebook, Instagram, Twitter, Snap, YouTube, and Google with each respondent only allowed to choose one option. KP INTERNET TRENDS 2017 | PAGE 23 Contextual Ads (Facebook) = Driving Direct Purchases Facebook Messenger Conversational Transactions, 9/16 26% 7% 10% 74% 93% 90% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Clicked on an Ad Didn't Click on Ad Not Sure % of RespondentsMade a Purchase Did Not Make a Purchase Facebook Users 26% that Click Ads Make Purchase, USA, 3/17 In past 30 days, have you clicked an ad on Facebook? In past 30 days, have you purchased a product you saw on Facebook? Source: Survata (4/17), Messenger Image: Facebook Blog (9/16) Note: Based on survey of USA internet users, n=1,500 (3/17). KP INTERNET TRENDS 2017 | PAGE 24 Goal Based Bidding Ads (Snap) = Driving User Action Snap / Gatorade Ad Campaign Users Swipe Through Ad to Web Game, 8/16 Users Spend Average of 196 Seconds Playing Game Source: Snap Case Study: Gatorade (8/16) KP INTERNET TRENDS 2017 | PAGE 25 Geo-Targeted Local Ads (Google) = Driving Foot Traffic to Stores Google Location-Tagged Ads 99% Accuracy Tracking Visits to 200MM Stores Globally, 9/16 5B Cumulative Tracked Store Visits, Up 5x Y/Y*, 5/17 Source: Google Adwords Blog (5/16, 9/16, 5/17), Image: Google Adwords Blog (9/16) * 5B (5/17) vs. 1B cumulative tracked (5/16). KP INTERNET TRENDS 2017 | PAGE 26 Incentive-Based + Skippable Video Ads = Driving Positive Interactions Incentive-Based + Skippable Video Ads More Likely to be Viewed Positively, 5/16 How would you characterize your attitude towards the following formats of online video advertising? 19% 20% 21% 26% 45% 46% 51% 52% 68% 81% 80% 79% 74% 55% 54% 49% 48% 32% Mobile App Pop-Up Pre-Roll In-Banner Auto-Play Social Auto-Play In-Banner Click-to-Play Skippable Mobile Pop-up Skippable Pre-Roll Social Click-to-Play Mobile App Reward % of Respondents Positive Negative Source: MillwardBrown AdReaction Video Creative in a Digital World (5/16) Note: Survey of people from Argentina, Australia, Brazil, France, Germany, Mexico, UK, and USA who watched 20 ads (at least 100 per ad) and answered positive or negative, n=10.739. The survey included TV, YouTube skippable pre-roll, Facebook auto-play, Facebook click-to-play, and mobile video ad formats. KP INTERNET TRENDS 2017 | PAGE 27 In-App Ads + Dynamic Creative (Vungle) = Driving Higher In-App Install Performance Dynamic Tab Ad Video + Images 0.00% 0.10% 0.20% 0.30% 0.40% 0.50% 0.60% 0 100 200 300 400 500 600 1/162/163/164/165/166/167/168/169/1610/1611/1612/161/172/173/174/17Conversion Rate (%)Dynamic Creative Variations (K)Dynamic Creative Variations Conversion Rate Vungle Dynamic Creative Ads Improving Conversion Rates, 5/17 Source: Vungle (5/17) Note: "Dynamic creative" is any creative ad that changes automatically based on information about the user (behavior, location, or context). A dynamic tab ad includes multiple interactive promotional modules alongside a video ad. KP INTERNET TRENDS 2017 | PAGE 28 In-Ride / In-Hand Recommendations (Uber + Foursquare) = Location + Route + Destination + Time of Day (+ an Offer) Uber / Foursquare Partnership In-App Recommendations for Nearby Businesses, 4/17 Source: Uber (4/17) KP INTERNET TRENDS 2017 | PAGE 29 Hyperlocal Targeting (NextdoorxAd) = From Home (Neighborhood) to Work (Commute) xAd Tracking Where / When Purchases Likely to be Made Nextdoor Neighbors Drive Word of Mouth +8% Engagement Lift for Ring Source: Nextdoor, xAd KP INTERNET TRENDS 2017 | PAGE 30 Advertising Inefficiency = Increasingly Exposed by Data Right 'Ad' @ Right Place / Time KP INTERNET TRENDS 2017 | PAGE 31 Right Ad @ Right Place / Time (Driven by Algorithms) User-Typed Input (Words) Linked to Relevant Ad = Google AdWords (Launched 2000) Source: Historyofinformation.com, Google KP INTERNET TRENDS 2017 | PAGE 32 Right Ad @ Right Place / Time Based on User-Typed Input (Words) = Big Business for Google Google = $679B Market Capitalization +30x vs. IPO $0 $200 $400 $600 $800 $1,000 $1,200 8/042/058/052/068/062/078/072/088/082/098/092/108/102/118/112/128/122/138/132/148/142/158/152/168/162/17Share Price ($)Source: Yahoo Finance Note: Priced as of 5/26/17 market close. Google IPO'ed @ $85 / share on 8/19/04. KP INTERNET TRENDS 2017 | PAGE 33 Right Ad @ Right Place / Time (Driven by Algorithms) User-Uploaded Input (Real-Time Images) Linked to Relevant Ad = SnapAds (Launched 2014) Source: Image: Adweek (10/14) KP INTERNET TRENDS 2017 | PAGE 34 Right Ad @ Right Place / Time Based on User-Uploaded Input (Images) = Big Business for Snap Snap = $25B Market Capitalization 0 20 40 60 80 100 120 140 160 180 $0 $20 $40 $60 $80 $100 $120 $140 $160 $180 Q1:15 Q2:15 Q3:15 Q4:15 Q1:16 Q2:16 Q3:16 Q4:16 Q1:17 DAU (MM)Net Revenue ($MM)Net Revenue DAU Source: Snap Filings Note: Priced as of 5/26/17 market close. Snap IPO'ed @ $17 / share on 3/2/17. KP INTERNET TRENDS 2017 | PAGE 35 A lot of the future of search is going to be about pictures instead of keywords. - Ben Silbermann, Pinterest Founder / CEO, 4/17 Source: CNBC interview (4/3/17) KP INTERNET TRENDS 2017 | PAGE 36 Ads Evolving Rapidly = Often Organic + Data @ Core KP INTERNET TRENDS 2017 | PAGE 37 Emerging Retailers + Crafty Big Brands = Finding Ways to Make Collaborative Ad Creation (Social + UGC) Work for Them KP INTERNET TRENDS 2017 | PAGE 38 Brands + Consumers = Re-Distribution Driving Engagement Ben & Jerry's / UGC on Instagram, 5/17 Effective UGC can generate 6.9x higher engagement than brand generated content on Facebook, per Mavrck, 2/17 Source: Mavrck Facebook UGC Benchmark Report (2/17), Image: benandjerrys Instagram featuring mistress_spice (4/17) Note: Study based on 536,238 micro-influencer brand activations completed via Mavrck Platform from 1/1/16-12/13/16. KP INTERNET TRENDS 2017 | PAGE 39 Brands + Consumers = Brands Sourcing Content from Fans Brands = Leveraging UGC on Instagram 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Amazon Video Emirates Turkish Airlines Cathay Pacific Starbucks Netflix Sephora Wayfair BMW Red Bull Qatar Airways % of Instagram Content Regrammed Source: SimplyMeasured (11/16) Note: Data collected from each company's Instagram page from 7/16-10/16. Posts were manually tagged for regrams based on mentions on 'regram' in the post or the camera emojis. KP INTERNET TRENDS 2017 | PAGE 40 Brands + Influencers = Re-Distribution Driving Engagement Influencers = Can Impact Followers Source: Stance KP INTERNET TRENDS 2017 | PAGE 41 Emerging Retailers + Crafty Big Brands = Finding Ways to Make Images (+ Video) + Data + Algorithms + Voice Work for Them KP INTERNET TRENDS 2017 | PAGE 42 Image-Based Platform Front-Ends = Tap + Augment Can Replace Typing 'Front-End' User-Generated Real-Time Geolocated Images Source: Left Image: Snap, Right Image: Instagram blog (3/17) KP INTERNET TRENDS 2017 | PAGE 43 Image-Based Platform Front-Ends = Taking Pictures Can Replace Typing 'Front-End' Google Lens Will Provide Greater Context to Images Source: Google I/O (5/17) KP INTERNET TRENDS 2017 | PAGE 44 Image-Based Platform Back-Ends = Algorithms Infer User Context from Images 'Back-End' Algorithms Infer Images / Project AR Objects into Scenes Source: Images: CB Insights, Seene Patents (acquired by Snap in 6/16) and Looksery Patents (acquired by Snap in 9/15) KP INTERNET TRENDS 2017 | PAGE 45 Image Recognition Back-Ends = Can Provide Contextual Relevance for Advertisers Snap Image Recognition Potential Ad Targeting Tool Google Visual Positioning Service Tracking Path to PurchaseIn-Store Source: Left Image : Snap Patent (7/16), Right Image: Google I/O (5/17) KP INTERNET TRENDS 2017 | PAGE 46 Voice-Based Mobile Platform Front-Ends = Voice Can Replace Typing Google Assistant Nearly 70% of Requests are Natural / Conversational Language, 5/17 20% of Mobile Queries Made via Voice, 5/16 Source: Google I/O (5/16), Image: Macrumors (2/17) KP INTERNET TRENDS 2017 | PAGE 47 Voice-Based In-Home Platform Front-Ends = Voice Can Replace Typing 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 Number of SkillsAmazon Echo Device Installed Base, USA Amazon Echo Skills Broadening Use Cases Amazon Echo Evolution, 11/14 5/17 Echo = Shopping + Media Echo Look = Shopping + Recommendations Echo Show = Video + Voice Calls 0 2 4 6 8 10 12 Echo Installed Base (MM)Source: Image: Amazon, Consumer Intelligence Research Partners LLC, Geekwire, Technology Review, Wired, Fast Company KP INTERNET TRENDS 2017 | PAGE 48 Voice-Based Platform Back-Ends = Voice Recognition Accuracy Continues to Improve Google Machine Learning Achieving Higher Word Accuracy, 2013-2017 95% 95% 70% 80% 90% 100% 2013 2014 2015 2016 2017 Word Accuracy Rate (%)Google Threshold for Human Accuracy Source: Google (5/17) Note: Data as of 5/17/17 and refers to recognition accuracy for English language. Word error rate is evaluated using real world search data which is extremely diverse and more error prone than typical human dialogue. KP INTERNET TRENDS 2017 | PAGE 49 Ads = Becoming Targeted Storefronts KP INTERNET TRENDS 2017 | PAGE 50 Ads / Content / Products / Transactions = Lines Blurring. Fast The Content = The Store Emails Curated Storefronts Facebook Feed Browsable Storefronts Source: Left Image: Facebook, Right Image: Stitch Fix KP INTERNET TRENDS 2017 | PAGE 51 Ads / Content / Products / Transactions = Lines Blurring. Fast. The Ad = The Transaction Instagram Feed Tap to Book, 4/17 Snap eCommerce Ad Swipe Up to Buy, 5/16 Source: Left Image: Instagram, Right Image: Snap KP INTERNET TRENDS 2017 | PAGE 52 Product Quality + Customer Support + Transparency Bars Rising = Owing to Social Media KP INTERNET TRENDS 2017 | PAGE 53 60% 53% 29% 21% 0% 10% 20% 30% 40% 50% 60% 70% Easier Access to Online Support Channels Faster Agent Reponse Times Consistent Customer Experience Across Channels Faster Access to Live Support % of ResponsesSocial Media = Can Provide Opportunity to Improve Customer Service If you could choose two things for organizations to improve in customer service, what would they be? (Select two), 8/16 Source: Ovum Get It Right: Deliver the Omni-Channel Support Customers Want (8/16) Note: Survey of consumers ages 18-80 in Australia, Europe, New Zealand, and USA, n=400. KP INTERNET TRENDS 2017 | PAGE 54 Social Media = Can Drive Accountability 82% of Customers Stopped Doing Business with a Company After Bad Experience vs. 76% in 2014, 8/16 Source: Image: Allbirds, Ovum Get It Right: Deliver the Omni-Channel Support Customers Want (8/16) Note: Survey based on consumers ages 18-80 in Australia, Europe, New Zealand, and USA; n=400. KP INTERNET TRENDS 2017 | PAGE 55 Intercom Simple + Engaging UI Real-Time Online Customer Conversations = Rising Rapidly Intercom Conversations Started, Global, 12/13-12/16 0 100 200 300 400 Conversations Started (MM)Source: Intercom Note: Conversations include messages initiated by businesses & consumers. KP INTERNET TRENDS 2017 | PAGE 56 Customers = Increasingly Expect to Understand How Things Work SoFi 'How It Works' Most Viewed Content, After Home Page SoFi Member Dashboard Send Questions Directly to CEO Source: SoFi KP INTERNET TRENDS 2017 | PAGE 57 Retailers Emerging With Especially Effective Strategies KP INTERNET TRENDS 2017 | PAGE 58 Chewy.com = Pet Treats / Food / Supplies Strong User Community + Great Target Market Engaged Community + High Customer Satisfaction Strong Revenue Growth $0 $100 $200 $300 $400 $500 $600 $700 $800 $900 $1,000 2015 2016 Revenue ($MM)Dynamic Customer Service Source: Chewy.com KP INTERNET TRENDS 2017 | PAGE 59 Glossier = Skincare & Beauty Products... Content Marketing User Generated Content = Influencers 300% 350% 400% 450% 500% 550% 600% 2015 2016 Active Customer % Y/Y GrowthAccelerating Active Customer Growth 'Into the Gloss' = Content Marketing Source: Glossier, Top Left Image: Instagram user genius_hotel, Bottom Left Image: Glossier KP INTERNET TRENDS 2017 | PAGE 60 UNTUCKit = Shirts Online-Offline Synergies in Marketing + Merchandising Source: UNTUCKit Note: Online session defined as website visit. 0 1 2 3 4 5 6 7 8 2015 2016 Sessions (MM)Online Sessions Up >2.5x Y/Y Offline Engagement Direct Touchpoints in Physical World Online Storefront Digital Merchandising Insights In-Store Interactions Intimacy + Active Dialogue Digital-Physical Feedback Loop Deliberate Branding + Clear Messaging @ Core KP INTERNET TRENDS 2017 | PAGE 61 Allbirds = Shoes Innovative Product + Simple Choice (Less Selection = More) Source: Allbirds * 3/16-6/16, H1:17 data from 1/17-5/17. 0 1 2 3 4 5 6 H1:16* H2:16 H1:17 eCommerceSessions (MM)Growing eCommerce Sessions Two Comfortable, High Quality Styles Tongue base double row stitch implemented Tongue lace loop reworked Tongue reinforcement layer added New internal toe reinforcement added 3x adjustments to U-throat opening Insole geometry modified New process/ material logo tabs developed Outsole durometer reduced Outsole redesigned Alternative insole cover material developed New vamp lining wool textile introduced Product Changes Based on Customer Input KP INTERNET TRENDS 2017 | PAGE 62 Trendyol = Apparel... Private Label + Local Sourcing for Local Consumers (Middle East) High Purchase Re-Engagement Items Purchased per Shopper Continue to Rise 0 2 4 6 8 10 12 2014 2015 2016 2017 YTD Average Units per Active ShopperPrivate Label + Local Sourcing Low Prices + Short Lead Times ~1K Suppliers 50km from Trendyol HQ Fast Replenishment (7-10 days) Private Label @ 38% of Revenue Other Fashion Brands Source: Trendyol Note: Average units per active shopper calculated over the course of shopper lifetime. KP INTERNET TRENDS 2017 | PAGE 63 MM.LaFleur = Women's Professional Wardrobe Relationship-Driven Experience (Online & Offline) High Growth + Retention $0 $5 $10 $15 $20 $25 $30 $35 2015 2016 Revenue ($MM)Returning Customers New Customers Wardrobe Survey Algorithmic Optimization Bento Box Curated Impressions Online Shopping Ongoing Customer Engagement In-Store Stylist Appointments Human Touch + Active Dialogue Source: MM.LaFleur KP INTERNET TRENDS 2017 | PAGE 64 eCommerce A-Ha's KP INTERNET TRENDS 2017 | PAGE 65 0% 2% 4% 6% 8% 10% 12% 0 2 4 6 8 10 12 2010 2011 2012 2013 2014 2015 2016 Y/Y Growth (%)Parcel Volume* (B)If It Seems Like Package / Parcel Growth is Accelerating It's Because It Is, +9% Y/Y Parcel Volume*, USA, 2010-2016 Source: USPS, Fedex, UPS Filings *Combines USPS's Domestic Shipping and Package Services volumes, Fedex's calendar year Domestic Package volumes, and UPS's Domestic Package volumes. KP INTERNET TRENDS 2017 | PAGE 66 Apartment Building Lobbies Becoming Warehouses Doormen Becoming Foremen Landlords Expanding Package Rooms to Accommodate Rising Online Order Delivery Source: Image: NYTimes Photographer Tony Cenicola KP INTERNET TRENDS 2017 | PAGE 67 Unwrapping Boxes Becoming Entertainment Unboxing YouTube Top 5 Channels = 33MM+ Subscribers, 5/17 Source: YouTube: Ryan's Toy Review, Fun Toys Collector Disney Toys Review, Disney Car Toys, Toys AndMe, Blu Toys Club Surprise, Images: CKN Toys KP INTERNET TRENDS 2017 | PAGE 68 Eating Out is Increasingly Eating In Top 10 DoorDash San Francisco Bay Area Restaurants Delivery as % of Revenue = 7% vs. 2% (2015) Revenue Growth = +45% Y/Y vs. 10% (2015) Eating Out Eating In Source: DoorDash, Left image: Pexels, Right image: DoorDash KP INTERNET TRENDS 2017 | PAGE 69 Grocery Shopping Getting Personal / Fast / Easy Instacart = Personalized Grocery Recommendations 8x More Likely to Buy When Prompted with 'Buy It Again' Option 85% of In-Store Replacements... Chosen Based on Algorithmic Recommendations Source: Instacart KP INTERNET TRENDS 2017 | PAGE 70 Lowe's Doing Augmented Reality Helping Consumers Find Products In-Store Lowe's / Google Partnership Guides Customers to In-Store Items via Augmented Reality on Mobiles, 3/17 Source: Google, Lowe's KP INTERNET TRENDS 2017 | PAGE 71 Stitch Fix Launching Another Private-Label Clothing Brand & It's Computer-Generated (1% of Products for Now)... Product Attributes + Customer Feedback + Data Science / Testing New Style, 5/17 Silhouette Sleeve Lace Feature Hem Type Print Cassie Crochet Detail Top Source: Stitch Fix, Left Image: Stitch Fix Algorithms Tour, Right Image: Stitch Fix KP INTERNET TRENDS 2017 | PAGE 72 Retail Store Closings May Break 20 Year Record While... Amazon Opens Retail Stores Retail Unit Closings, USA, 1995-2017 YTD 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 19951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017EUnit ClosingsAverage Amazon Looks to Expand its Physical Footprint Source: Credit Suisse, Amazon Note: 2017 is YTD as of 4/6/17. 2017 estimate per Credit Suisse. KP INTERNET TRENDS 2017 | PAGE 73 Digitally Native Brands = Go Offline I don't think retail is dead. Mediocre retail experiences are dead. - Neil Blumenthal, Co-CEO @ Warby Parker, 1/17 Bonobos Guide Shops Try On In-StoreShip to Home Warby Parker Schedule Eye ExamsBuy Glasses Source: WSJ interview 1/23/17, Left image: Pinterest, Right image: Fashion Trends Daily KP INTERNET TRENDS 2017 | PAGE 74 World's Largest Offline Retailer (Wal-Mart) Getting Aggressive Online Wal-Mart eCommerce Revenue Y/Y Growth, Global 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% % Y/Y Growth90% of Americans Live Within 10 Miles of a Wal-Mart FQ1:18 eCommerce Revenue Growth @ 63% Y/Y vs. 29% FQ4:17, USA Modcloth.com, 3/17 Moosejaw, 2/17 JD.com (Increased to 12%), 2/17 Shoebuy, 1/17 Recent Acquisitions & Investments Organic + Inorganic Growth Source: Wal-Mart Note: Fiscal year ends January. Wal-Mart stopped disclosing global eCommerce revenue growth after FQ4:17 and began disclosing USA eCommerce revenue growth. Acquired Jet.com, 8/16 KP INTERNET TRENDS 2017 | PAGE 75 Amazon Becoming a Leading Private-Label Supplier of Baby Wipes + Batteries, USA Amazon Basics Market Share, 8/16 USA 0% 5% 10% 15% 20% 25% 30% 35% Online Baby Wipes Market Share (%)0% 5% 10% 15% 20% 25% 30% 35% Online Battery Market Share (%)Source: Images: Amazon, 1010 Data Note: Data collected from 9/15-8/16 KP INTERNET TRENDS 2017 | PAGE 76 eCommerce Growth = +15% Y/Y Accelerating, Again, USA Online Retail Sales vs. Y/Y Growth, USA 2010-2016 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% $0 $50 $100 $150 $200 $250 $300 $350 $400 $450 2010 2011 2012 2013 2014 2015 2016 % Y/Y GrowthUSA Online Retail Sales ($B)Source: St. Louis Federal Reserve FRED Database KP INTERNET TRENDS 2017 | PAGE 77 And Now We Have a New Kind of Store = A Subscription Store Amazon Subscription Store = Central Hub for Monthly Services, 4/17 Entertainment Education Professional Services Cloud Storage News Source: Amazon KP INTERNET TRENDS 2017 | PAGE 78 More / Faster Than Ever = Great Products Find Customers Customers Find Great Products Process + Data Collection + Intermediaries = Changing @ Torrid Pace KP INTERNET TRENDS 2017 | PAGE 79 1) Ad Growth = Driven by Mobile 2) Ad Measurability = Can Be Triple-Edged 3) Ads Evolving Rapidly = Often Organic + Data @ Core 4) Ads = Becoming Targeted Storefronts 5) eCommerce Growth = Accelerating, Again 6) eCommerce A-Ha's Online Advertising (+ Commerce) = Increasingly Measurable + Actionable KP INTERNET TRENDS 2017 | PAGE 80 INTERACTIVE GAMES = MOTHERLODE OF TECH PRODUCT INNOVATION / EVOLUTION + MODERN LEARNING WITH THANKS TO BING GORDON FOR INSIGHT + INSPIRATION KP INTERNET TRENDS 2017 | PAGE 81 Global Interactive Gaming = Mainstream / Evolving Rapidly / Still Early Days 2.6B Gamers* vs. 100MM in 1995 Source: Unity Q1:17 estimate (5/17), Electronic Arts 2016 estimate (12/16), Electronic Arts 1995 estimate (5/17) *Unity estimates reflect the total number of users seen playing mobile games (at least once every three months) powered by both proprietary and leading 3rd party game engines. This number assumes all PC or Console gamers also play at least 1 mobile game. KP INTERNET TRENDS 2017 | PAGE 82 Gaming Evolution = Individual Play Global Collaborative Play (1967-2017) 45 Years Solo Living Room Many Arena (Thousands) Online (Millions) Moore's Law (Processing) Zuckerberg's Law* (Sharing) 1 Player = Arcade 2 Players = Consoles 2+ Players = Consoles + LAN Millions of Players = Online Network Millions of Players + Spectators = eSports Source: Images: National Museum of American History (Brown Box), Wikipedia Creative Commons (Pac-Man, Atari 2600, SG-1000, SNES, N64, PS1, Xbox, PS2), Flickr user Sham Hardy (World of Warcraft), Flickr user coneybeare (Words with Friends), ESL (ESL Logo), Twitch (Twitch Logo), Major League Gaming (MLG Logo), Wikimedia Creative Commons (Pong), Flickr user BagoGames (eSports Stadium) Note: In 1967 TV Game Unit #7, also known as the "Brown Box" was launched as a prototype and is considered the father of video game consoles per the National Museum of American History. *Zuckerberg's Law describes the exponential growth of online social networks as per Saul Hansell in NY Times, 11/6/08. KP INTERNET TRENDS 2017 | PAGE 83 Source: Images: Wikimedia Creative Commons (Pong, Asteroids, Space Invaders, Pac-Man), Flickr user BagoGames (Mario Bros), Mobygames (John Madden Football), Electronic Arts (FIFA), Pokmon (Pokmon Red and Blue versions), World of Warcraft (Warcraft), Supercell (Clash of Clans), Minecraft (Minecraft Logo), Riot Games (League of Legends), King (Candy Crush Saga), Activision Blizzard (Overwatch), Pokmon Go (Pokmon Go) Gen X + Millennials = Gamified Since Birth 1970 2000 2010 1980 1990 Gen X Millennials KP INTERNET TRENDS 2017 | PAGE 84 Gaming = Large + Broad + Growing Business Revenue @ $100B, +9% Y/Y Interactive Gaming Revenue Estimates per Newzoo, Global, 2016 $3 $3 $4 $17 $25 $47 Middle East & Africa Eastern Europe Latin America Western Europe North America Asia Pacific Revenue ($B) Source: Newzoo Global Games Market Report (2016) Note: Excludes console / gaming PC hardware revenue. KP INTERNET TRENDS 2017 | PAGE 85 Gamers = All Ages 35 Year-Old Average, USA Gamer Demographics vs. Average Age, USA, 2003-2016 0 5 10 15 20 25 30 35 40 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Average Age% of GamersUnder 18 18-50 50+ Average Age Source: Entertainment Software Association (ESA) Essential Facts About the Computer and Video Game Industry 2003-2016 Note: Based on a survey of 4,000 U.S. households. KP INTERNET TRENDS 2017 | PAGE 86 Female Gamers = Players Since Early Days But Genres Vary 2000 (Year) Marked Rise of Casual Female Gamer % of Female Players by Game Genre, Global, 1/17 2% 6% 7% 16% 18% 36% 42% 69% 69% Sports Racing First-Person Shooter MMOs (Sci-Fi) Action Adventure MMOs (Fantasy) Casual Puzzle Family / Farm Sim Match 3 Match 3 Pioneered by Diamond Mine / Bejeweled, 2000 Family / Farm Sim Pioneered by Sims, 2000 Source: Quantic Foundry, Top Right Image: Popcap, Bottom Left Image: MoMA Note: Each genre analyzed contained between 3-5 game titles. The median sample size for each game title was 1,184. And the median sample size for each genre was 4,657. KP INTERNET TRENDS 2017 | PAGE 87 Gaming Tools = Pervasive Online Can Optimize Learning + Engagement Foundational for Internet Services KP INTERNET TRENDS 2017 | PAGE 88 Gaming Tools = Can Optimize Learning + Engagement Foundational for Internet Services Repetition Dynamic Difficulty Adjustment Solving Puzzles Planning Workflows Completing Projects Leveling Up Competing Exploring / Discovering Following Rules Collaborating Social Connection / Leadership Observing Interacting With / Analyzing Data Self Optimizing Creative Story Telling KP INTERNET TRENDS 2017 | PAGE 89 Source: Center quote from Len Schlesinger: "Failure doesn't mean the game is over, it means try again with experience," Global Leadership Summit (8/11/11), Images: Playpacmanonline.net Repetition = Learn from Losing Trial & Error Gaming Lifecycle Try again, with experience Respawn Fail Play Test Tactics KP INTERNET TRENDS 2017 | PAGE 90 Dynamic Difficulty Adjustment = Ultimate Trial & Error Experience Engaging Learning Process Machine-Learning Fine-Tunes Gaming Mechanics Source: Image: Games for Learning Institute KP INTERNET TRENDS 2017 | PAGE 91 Solving Puzzles = Pattern Recognition + Critical Thinking Defined Rules + Strategy (Short-Form) Minesweeper Unstructured Puzzles (Long-Form) L.A. Noire Detective Cases Source: Left image: Game Set Watch, Right image: L.A. Noire (Rockstar Games) KP INTERNET TRENDS 2017 | PAGE 92 Planning Workflows = Manage Time + Resource Efficiency Time Management Legend of Zelda: Majora's Mask Quest Progress Resets Periodically Resource Management Starcraft II 'Require More Minerals' Source: Left image: Zelda Informer, Right image: Activision Blizzard Battle.net KP INTERNET TRENDS 2017 | PAGE 93 Completing Projects = Track Finish Line from Start Focus on End Goal Pokmon 'Gotta catch 'em all!' Track Experience Skyrim Source: Left Images: Logos Wikia, Bulbapedia, Right Images: Skyrim, YouTube user HighlandMarker, Portforward.com, metagamebook, Stack Exchange KP INTERNET TRENDS 2017 | PAGE 94 Leveling Up = On-Going Progress Measurement Leveling Up Candy Crush Saga Gain Experience Completing Puzzles Quantified Mastery Max Level in World of Warcraft Source: Left Images: Apptipper, King, Right Image: Blizzardwatch KP INTERNET TRENDS 2017 | PAGE 95 Competing = Play Against Self + Others Sharpens Skills Competing Against Yourself Time Trials in Mario Kart 64 Competing Against Others Scoring Goals Online in Rocket League Source: Left Image: YouTube user Drew Weatherton, Right Image: GameSpot KP INTERNET TRENDS 2017 | PAGE 96 Exploring / Discovering = Open Closed DoorsHack to Improvement Discovering Easter Eggs Silent Hill 2 + Tony Hawk's Pro Skater 2 Discovering Glitches Secret Level in Super Mario Bros Source: Left Images: Nintendo, Right Images: Digital Trends, Games Radar KP INTERNET TRENDS 2017 | PAGE 97 A game is a system in which players engage in an artificial conflict, defined by rules, that results in a quantifiable outcome. - Salen & Zimmerman, Rules of Play: Game Design Fundamentals, 9/03 Following Rules = Structured Play Players = Free to Break Rules But = Consequences Source: Salen & Zimmerman, Rules of Play: Game Design Fundamentals, Left image: YouTube user Ross Campbell, Right image: YouTube user x Pepper KP INTERNET TRENDS 2017 | PAGE 98 Collaborating Social Connection / Leadership = Learn From / Work With Others Blizzard = Millions Playing Together Online, Global Key Multiplayer Franchises = World of Warcraft + Diablo + Starcraft + Overwatch 21 29 28 26 26 33 42 41 41 0 5 10 15 20 25 30 35 40 45 Q1:15 Q2:15 Q3:15 Q4:15 Q1:16 Q2:16 Q3:16 Q4:16 Q1:17 MAU (MM)Source: Activision, Morgan Stanley Note: Graph emphasizes Blizzard over Activision and King users due to the multiplayer nature of most Blizzard franchises. KP INTERNET TRENDS 2017 | PAGE 99 Observing = Learn From Watching Others Perform Live Streamed Gameplay Live Streamed Player Reactions Live Chat Interaction with Player Subscribe to Streamer 1.2 2.4 3.2 4.0 4.9 0.0 0.5 1.0 1.5 2.0 2.5 0 1 2 3 4 5 6 2012 2013 2014 2015 2016 Unique Monthly Streamers (MM)Hours Streamed (B)Hours Streamed Unique Monthly Streamers Twitch Hours Streamed vs. Unique Monthly Streamers Source: Left image: Twitch Streamer: cherrysamora, Twitch Annual Reports 2013-2016 Twitch Streaming 10MM DAU, 2/17 KP INTERNET TRENDS 2017 | PAGE 100 Interacting With / Analyzing Data = Many Games Have Strong Math Underpinnings Fantasy Sports Fans Engaged in Analytics, USA, 1988-2016 Live Stats Feed Into Video Games + Fantasy Sports 0% 5% 10% 15% 20% 25% 0 10 20 30 40 50 60 70 198819911994200320042005200620072008200920102011201420152016% of USA Population Over 18Fantasy Sports Players* (MM)USA Fantasy Sports Players % of USA Population John Madden Football Released Source: FSTA, Left image: Flickr user We Are Social, U.S. Census Bureau *Fantasy Sports Players are defined as U.S. individuals aged 18+ having played fantasy sports in the past year. Based on survey of USA individuals aged 18+, n=1,000. KP INTERNET TRENDS 2017 | PAGE 101 Self-Optimizing = Driven by Math (Statistics / Metrics / Rankings) In-Game Player Analytics / Dashboards Increasingly Found in Enterprise / Consumer Products / Services Madden 2017 Player Stats Looker Business Intelligence Dashboard Source: Top left image: YouTube user Brian Mazique, Bottom left image: Uproxx, Right Image: Looker KP INTERNET TRENDS 2017 | PAGE 102 Creative Story Telling = Can Be Master of a Universe Laying Building Blocks of a Virtual World Minecraft Choosing Gameplay Experience Mass Effect 3 Source: Left image: Gamepedia blog, Right image: Kotaku Minecraft KP INTERNET TRENDS 2017 | PAGE 103 Gaming Tools = Can Optimize Learning + Engagement Foundational for Internet Services Reputation / Rankings Digital Recognition Interactive Storytelling Interactive Learning Upgrades + Downloadable Content Secondary Markets Messaging Live Camera Angles Graphics Computation KP INTERNET TRENDS 2017 | PAGE 104 Reputation / Rankings = Deep Roots in Gaming Airbnb Superhost Program Recognizes Top Performing Hosts Early Gaming (1978) Mainstream Internet (Now) Space Invaders First Arcade Game to Record High Scores Source: Left image: Codexdex, Right image: Airbnb, Probnb KP INTERNET TRENDS 2017 | PAGE 105 Digital Recognition = Deep Roots in Gaming Activision 2600 Games Physical Badges for In-Game Achievements Facebook Give Digital Badges to Others Early Gaming (1980) Mainstream Internet (Now) Source: Left image: Atari Age, Right image: Facebook KP INTERNET TRENDS 2017 | PAGE 106 Interactive Storytelling = Deep Roots in Gaming Atari First Role Playing Game Netflix + Amazon / Twitch Experimenting with Interactive Shows Early Gaming (1980) Mainstream Internet (Now) Source: Left image: mprd.se, Right images: Netflix, Amazon KP INTERNET TRENDS 2017 | PAGE 107 Duolingo Leveling Up in Languages Lemonade Stand Teaching Economics 101 Interactive Learning = Deep Roots in Gaming Early Gaming (1979) Mainstream Internet (Now) Source: Left Image: Archive.org, Right Image: Duolingo, KP INTERNET TRENDS 2017 | PAGE 108 Tesla Over-the-Air Software Updates Sega Downloadable Content via Cable Upgrades + Downloadable Content = Deep Roots in Gaming Early Gaming (1993) Mainstream Internet (Now) Source: Left image: Gamecrate, Right image: Tesla KP INTERNET TRENDS 2017 | PAGE 109 Secondary Markets = Deep Roots in Gaming Runescape Secondary Markets for Items / Currency Apple iMessage 3rd Parties Offer Sticker Packs Early Gaming (2001) Mainstream Internet (Now) Source: Left image: RPGStash, Right image: Macstories KP INTERNET TRENDS 2017 | PAGE 110 Messaging = Deep Roots in Gaming 768MM DAU 12/16 1999 5MM DAU 1/17 2009 2013 9MM DAU 5/17 Early Gaming Mainstream Internet (Now) Source: WeChat 2016 Year End Report (12/16), Ali Rayl Interview (Head of Global Customer Experience at Slack) (1/17), Venture Beat (5/17), Top left image: Pingwest, Top right images: Tencent, Middle images: SiteProNews, Bottom left image: ifeng, Bottom right image: Corsair KP INTERNET TRENDS 2017 | PAGE 111 Live Camera Angles = Deep Roots in Gaming Madden Football Unique Game Perspectives Cable TV Cameras Unique Angles of Live Games Early Gaming (1996) Mainstream Media (Now) Source: Left image: Electronic Arts, Right image: Giants NFL KP INTERNET TRENDS 2017 | PAGE 112 Graphics Computation = Deep Roots in Gaming NVIDIA Launches GeForce 256 GPU Early Gaming (1999) Mainstream Internet (Now) Many Companies GPUs Used for Artificial Intelligence Source: Left Images: NVIDIA, VGA Museum, Right images: Google Deepmind, Amazon, IBM KP INTERNET TRENDS 2017 | PAGE 113 In Era of Perceived Disengagement = 'Engagement' + Measurement Rising KP INTERNET TRENDS 2017 | PAGE 114 Video Gaming = Most Engaging Form of Social Media Daily Minutes Spent per User Across Select Digital Media Platforms 51 50 35 30 21 0 10 20 30 40 50 60 Video Gaming (Consoles, 9/16) Facebook Ecosystem (4/16) King (Mobile Games, 5/17) Snapchat (5/17) Instagram (10/14) Average Daily Minutes Spent by Active UsersSource: Global Web Index (9/16), Facebook Q1:16 Earnings Call (4/16) & Q3:14 Earnings Call (10/14), Activision Q1:17 Earnings Call (5/17), Snapchat Q1:17 Earnings Call (5/17) Note: Video Gaming (Consoles): Global survey, n=17,990, of console users aged 16-64 asking "Roughly how many hours do you spend playing on game consoles during a typical day." Includes Xbox One, Nintendo Wii U, PS4, Xbox 360, PS3, Nintendo Wii King: Average time spent per DAU. King used to illustrate mobile gaming time spent given the global nature of the platform and large base of daily active users (peaked at 158MM as of Q1:15, 128MM in Q4:15 was last disclosure). Snapchat: Average of the 25-30 minutes of daily usage found in the S-1 filing. KP INTERNET TRENDS 2017 | PAGE 115 Mobile Daily Gaming Session Duration = +33% (3/17 vs. 7/15), Global, per Unity Games Mobile Average Daily Gaming Session Duration on Unity Games, Global, 7/15 3/17 Source: Unity KP INTERNET TRENDS 2017 | PAGE 116 When I play a video game, it's the only time I put away the phone and forget it exists. Video games command your attention in a way that nothing else can or will. - Gary Whitta, Screenwriter, Rogue One: A Star Wars Story, 5/17 Source: GamesBeat Summit 2017: How games, sci-fi, and tech create real-world magic (5/12/17) KP INTERNET TRENDS 2017 | PAGE 117 Perhaps Interactive Gaming Evolution / Growth / Usage Has Been Helping Prepare Society for Ongoing Rise of Human-Computer Interaction? KP INTERNET TRENDS 2017 | PAGE 118 Gaming Tools = Improving Human Performance Virtual + Augmented Reality / Simulations / Real-Time Analytics KP INTERNET TRENDS 2017 | PAGE 119 Immersive Gaming Tools = Improving Athlete Performance KP INTERNET TRENDS 2017 | PAGE 120 Video + Virtual Reality = Mental Reps Can Improve Performance STRIVR Labs + Stanford Football Utilize Video + Virtual Reality to Repeatedly Run Plays / Scenarios Source: STRIVR Labs, Inc. KP INTERNET TRENDS 2017 | PAGE 121 Video + Machine Learning = Visuals + Deep Analytics Can Improve Performance Second Spectrum 150K+ Tracked Events per Game,* 5/17 0 2 4 6 8 10 0 5 10 15 20 25 Q1:16 Q2:16 Q3:16 Q4:16 Q1:17 Videos per Team (K)TeamsTeams Video Sessions per Team Video Analytics of Key Plays Teams vs. Video Sessions per Team Source: Second Spectrum Note: Video session is defined as every time a user at a team watches a play using the Second Spectrum system. *Events are data surrounding key in-game actions such as pick-and-roll defenses, off-ball screens, shot probability or rebound probability. This allows players to query specific tactical actions during a game to gain better insight into how individuals / the team played. KP INTERNET TRENDS 2017 | PAGE 122 Audio + Guided Meditation = Mental Focus Can Improve Performance CJ McCollum, NBA Shooting Guard Uses Headspace to Maintain Focus, 6/16 There's a lot of stress in my joband a 10 minute Headspace meditation helps you take care of all of those things and more. - CJ McCollum, 4/17 Headspace Run Streak Reinforce Habits Source: Headspace KP INTERNET TRENDS 2017 | PAGE 123 Physically Interactive Media (PIM) = Real-Time Activity / Analytics Can Boost Intensity / Focus for Athletes Peloton 100K+ Bike Subscribers (95% Retention After 1 Year)400K+ Home Riders 1MM+ Home Workouts Streamed in 3/17 2 Workouts per Week per Subscriber Source: Peloton KP INTERNET TRENDS 2017 | PAGE 124 I could go ten hours at a stretch [playing soccer video games] and I'd often spot solutions in the games that I parlayed into real life. Zlatan Ibrahimovic, I Am Zlatan: My Story On and Off the Field, 6/14 Video Games = Simulations Can Improve Athlete Strategy + Performance From FIFA Online To the Real Game Source: I Am Zlatan: My Story On and Off the Field 2014, Left Image: New York Times (10/16), Right Image: The Sun KP INTERNET TRENDS 2017 | PAGE 125 Video Games = Stats Can Assist Athletes + Coaches Video Game Player Stats Real-Time Feedback Offline, 9/16 Hoffenheim Scout Discovers Roberto Firmino Using Football Manager Video Game, 11/16 Players + Coaches View Digital Stats as Important Performance Measure Source: Left Image: Twitter user Michy Batshuay, Right Image: Hardware Zone KP INTERNET TRENDS 2017 | PAGE 126 Game Year Teams Madden Actual Winner Score Winner Score Super Bowl LI 2017 Patriots vs. Falcons Patriots 27-24 Patriots 34-28 Super Bowl L 2016 Broncos vs. Panthers Panthers 24-20 Broncos 24-10 Super Bowl XLIX 2015 Patriots vs. Seahawks Patriots 25-24 Patriots 28-24 Super Bowl XLVIII 2014 Broncos vs. Seahawks Broncos 31-28 Seahawks 43-8 Super Bowl XLVII 2013 49ers vs. Ravens Ravens 27-24 Ravens 34-31 Super Bowl XLVI 2012 Patriots vs. Giants Giants 27-24 Giants 21-17 Super Bowl XLV 2011 Steelers vs. Packers Steelers 24-20 Packers 31-25 Super Bowl XLIV 2010 Saints vs. Colts Saints 35-31 Saints 31-17 Super Bowl XLIII 2009 Steelers vs. Cardinals Steelers 28-24 Steelers 27-23 Super Bowl XLII 2008 Patriots vs. Giants Patriots 38-30 Giants 17-14 Super Bowl XLI 2007 Colts vs. Bears Colts 38-27 Colts 29-17 Super Bowl XL 2006 Steelers vs. Seahawks Steelers 24-19 Steelers 21-10 Super Bowl XXIX 2005 Patriots vs. Eagles Patriots 47-31 Patriots 24-21 Super Bowl XXXVIII 2004 Patriots vs. Panthers Patriots 23-20 Patriots 32-29 Video Games = Stats Can Be Predictive Madden Super Bowl Winner Prediction Accuracy @ 71% (14 Years) Madden Football Super Bowl Predictions vs. Actual Results, 2004-2017 Source: Electronic Arts, ESPN, USA Today, Forbes KP INTERNET TRENDS 2017 | PAGE 127 Immersive Gaming Tools = Improving Performance Across Disciplines KP INTERNET TRENDS 2017 | PAGE 128 Gamification = Influencing Multiple Consumer Services Education Duolingo Personal Finance Acorns Energy Conservation Nest Personal Health Mango Health Exercise myfitnesspal Food Starbucks Dating Bumble Advertising Snapchat Source: Top Row Images: Duolingo, Mango, Acorns, Nest, Bottom Row: iPhone in Canada (Starbucks), Consumer fitness news (Myfitnesspal), 5why.com (Bumble), Snapchat KP INTERNET TRENDS 2017 | PAGE 129 Gamification = Influencing Multiple Businesses Military Training Healthcare Research Foldit Pilot Training Boeing Healthcare Training Simulated Surgery Neuroscience PTSD Therapy Work Productivity Betterworks Source: Top Left Image: Fold.it, Top Middle Image: US Army Sgt 1st Class Caleb Barrieau, Top Right Image: Betterworks, Bottom Left Image: Boeing, Bottom Center Image: Simulated Surgical Systems, Bottom Right Image: Archpaper.com KP INTERNET TRENDS 2017 | PAGE 130 Gamification = Influencing Complex Virtual Worlds + Real-World Simulations Improbable in Real World Simulate Cities + Power / Web Networks Improbable in Gaming Simulate Vast Virtual Worlds Source: Worlds Adrift: Bossa Studios, Improbable KP INTERNET TRENDS 2017 | PAGE 131 As Rapid Data Growth Continues = Gaming Tools / Interfaces / Processors Will Continue to Organize + Drive Usefulness KP INTERNET TRENDS 2017 | PAGE 132 Data Volume Growth Continues @ Rapid Clip % Structured / Tagged (~10%) Rising Fast 0 20 40 60 80 100 120 140 160 180 Zetabtytes (ZB)2005: 0.1 ZB 2010: 2 ZB, 9% 2015: 12 ZB, 9% % Structured / Tagged Information Created Worldwide = Expected to Continue Accelerating 2020: 47 ZB, 16% 2025E: 163 ZB, 36% Source: IDC DataAge 2025 Study, sponsored by Seagate (3/17) Note: 1 petabyte = 1MM gigabytes, 1 zeta byte = 1MM petabytes KP INTERNET TRENDS 2017 | PAGE 133 GPU Processing Power Ramp Continues NVIDIA Transistors, 1998-2016 Source: NVIDIA Note: 1 GFLOP = 1B FLOPS, or "floating point operations per second." 0 1,000 2,000 3,000 4,000 5,000 6,000 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Transistors (MM)Transistors 2002 = 5 GFLOPS Battlefield 1942 2007 = 350 GFLOPS Unreal Tournament 3 2016 = 10K GFLOPS Paragon KP INTERNET TRENDS 2017 | PAGE 134 Gaming Platforms = Evolving @ High Speed KP INTERNET TRENDS 2017 | PAGE 135 New Gaming Development Tools / Platforms = Evolving to Continue to Build Virtual Worlds Development Platforms In-Game Sandboxes Developers Players Have Virtual Experiences Build / Share / Explore Creations Build Virtual Worlds / Share Ideas Construct Virtual Worlds with New Dimensions Build / Share Creations Distribute Content Discover / Buy / Share Content Explore Virtual Worlds VR / AR Platforms Gaming Marketplaces Source: Unreal, Unity, HTC Vive, Oculus (Facebook) Microsoft, Minecraft, Roblox, Tencent, Steam (Valve), Sony KP INTERNET TRENDS 2017 | PAGE 136 New Gaming Development Tools / Platforms = Supporting Rapid Growth 0 1 2 3 4 5 6 7 Registered Developers (MM)0 10 20 30 40 50 60 May-16 Jun-16 Dec-16 Mar-17 MAU (MM)0 5 10 15 Peak Concurrent Users (MM)Unity = Registered Developers Roblox = Monthly Active Users Steam = Peak Concurrent Users* Source: Unity, Roblox, Steam (Valve), Forbes, Venturebeat, Bloomberg *Taken on the last available day of each month using waybackmachine.org. KP INTERNET TRENDS 2017 | PAGE 137 eSports = Expanding Gaming Ecosystem via Fans / Spectators KP INTERNET TRENDS 2017 | PAGE 138 eSports = 45 Year Evolution to Global Stage 1997 Red Annihilation Quake Tournament = Early eSports Competition 2000 Electronic Sports League + Korea eSports Assn. = Emerge as First eSports Leagues 2006 Justin.tv Founded = Precursor to Twitch.tv 2016 League of Legends 2016 World Championship = 43MM viewers 2009 League of Legends Released = Becomes One of Most Played Strategy Games (100MM MAU, 9/16) 2012 OnGameNet Begins Broadcasting League of Legends = First Major Korean Tournament on TV Evolution of Global eSports 1972 Stanford University AI Lab = First Ever Gaming Tournament (Spacewars) 1980 Atari Space Invader Competition = Early National Gaming Tournament Source: Spacewars image: Kokatu, Atari image: Ausretrogamer.com, Red Annihilation image: timetoast, Fortune (7/15), ESL logo: ESL, MLG, KeSPA Logo: Team Liquid, MLG Logo: MLG, Halo 2 Logo: Pinterest, Justin.tv Logo: startupgenome.com, Twitch Logo: Twitch, Riot Games (10/08), League of Legends Logo: League of Legends, Forbes (9/16), na.lolesports, OGN Logo: Twitch, eSports.inquirer.net, eSportsTV logo: mb.cision.com, League of Legends World Championship KP INTERNET TRENDS 2017 | PAGE 139 eSports = People Watch What They Play League of Legends Expands from Home to Staples Center, LA (Worlds 2016 Finals = ~20K in Stadium + 43MM Online) Source: Top left image: Mel Melcon Los Angeles Times, Bottom left image: Dexerto, Top right image: Red Bull, Bottom right image: YouTube KP INTERNET TRENDS 2017 | PAGE 140 eSports Trending vs. Traditional Sports = Very Strong with Younger Generations Millennials = 27% 'Significant Preference' for eSports vs. 27% for Traditional Sports Non-Millennials = 45% for Traditional Sports vs. 13% for eSports Which do you prefer, your favorite traditional sport or favorite eSport? 21% 27% 13% 13% 13% 13% 19% 18% 20% 13% 15% 11% 34% 27% 45% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% All Responses All Millennials All Non-Millennials % of Respondents that indicated at least a slight interest in eSportsSignificantly prefer favorite eSport Slightly prefer favorite eSport No preference Slightly prefer favorite traditional sport Significantly prefer favorite traditional sport Source: L.E.K. Sports Survey, Digital Engagement Part One: Sports and the "Millennial Problem" (2/17) KP INTERNET TRENDS 2017 | PAGE 141 eSports Monthly Viewers @ 161MM +40% Y/Y & Accelerating eSports Monthly Viewers, Global, 2012-2016 58 74 90 115 161 28% 22% 28% 40% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 0 20 40 60 80 100 120 140 160 180 2012 2013 2014 2015 2016 Y/Y Growth (%)eSports Viewers (MM)eSports Monthly Viewers Y/Y Growth Source: Newzoo Global eSports Market Report (2/17), Newzoo press release (1/16), Newzoo Casual Connect Europe Presentation (2/15) *eSports Enthusiasts watch eSports once a month and/or participate in tournaments. KP INTERNET TRENDS 2017 | PAGE 142 eSports League of Legends Championship Viewers @ 43MM +19% Y/Y League of Legends World Championship Global Viewership Largest eSports Viewer Base 2 8 32 27 36 43 0 1 9 11 14 15 0 5 10 15 20 25 30 35 40 45 50 2011 2012 2013 2014 2015 2016 Viewers (MM)Total Unique Viewers Peak Concurrent Viewers Total Unique Viewers vs. Peak Concurrent Viewers Source: Engadget, Polygon, The Verge, eSports Marketing, LoLeSports KP INTERNET TRENDS 2017 | PAGE 143 eSports Monthly Viewers = 79% <35 Years Old29% Female Monthly eSports Viewers by Age / Gender, Global, 2016 27% 53% 18% 2% 0 20 40 60 80 100 120 10-20 21-35 36-50 51-65 Global eSports Enthusiasts (MM)Male Female % of Total Monthly eSports Viewers Source: Newzoo 2017 Global eSports Market Report (2/17) KP INTERNET TRENDS 2017 | PAGE 144 eSports (Like Sports) = Money Follows Viewers + Winners Fan In-Game Purchases Boost Prize Pools Prize Pool for The International (DOTA 2), 2011-2017 $1.6 $1.6 $2.9 $10.9 $18.4 $20.8 $10.7 $0 $5 $10 $15 $20 $25 2011 2012 2013 2014 2015 2016 2017 YTD Prize Pool ($MM)Base Prize Pool Compendium* Source: ESPN, eSports Earnings, DOTA 2 (5/24/17) Note: * The International Compendium represents 25% of in-game purchases during a promotional period leading up to the event. Players can buy virtual items, levels, and other in-game content. As the total prize pool reaches different milestones all players who participated gain access to more exclusive content. 2017 YTD as of 5/25/17. KP INTERNET TRENDS 2017 | PAGE 145 Facebook = Expands eSports Relationships with ESL Streaming Deal, 5/17 NBA + Up with Take Two = 2K eSports League, 2/17 German Soccer Club, FC Schalke 04 = Acquires eSports Team, Elements, 5/16 Partnerships + Investments = Helping Bring eSports into Mainstream Philadelphia 76ers = Acquire eSports Teams, Dignitas & Apex, 9/16 Miami Heat = Invests in eSports Team, Misfits, 1/17 Expanding Connections with Sports / Media Platforms Italian Soccer Club AS Roma = Partners with eSports Team, Fnatic, 2/17 Riot Games + BAMTech = $300MM 6yr LoL Streaming Rights, 12/16 Source: ESPN, Engadget, Yahoo Sports, Live Production, Dot eSports, Forbes KP INTERNET TRENDS 2017 | PAGE 146 Gaming Experience => Technology Leadership + Innovation? KP INTERNET TRENDS 2017 | PAGE 147 Ten Years Ago (2007) = A Stanford Professor Said If you want to see what business leadership may look like in three to five years, look at what's happening in online games. - Byron Reeves, Professor of Communication, Stanford University, 6/07 Source: Byron Reeves KP INTERNET TRENDS 2017 | PAGE 148 ~Ten Years Later = Entrepreneurs Often Fans of Gaming Experience I like video games. In fact, that's what got me into software engineering when I was a kid. I wanted to make money so I could buy a better computer so I could play better video games. - Elon Musk, CEO Tesla & SpaceX, 10/16 As a child I played a lot of Avalon Hill board games. And each board game is actually a complex set of rules and circumstances So it was actually in fact my childhood gaming for being able to build a model of what a game was that was essentially the fundamental thing that informs my strategic sense. - Reid Hoffman, Co-Founder of LinkedIn, 8/15 I do think this dynamic around kids growing up, building games, and playing games, is an important one because I think this is how a lot of kids get into programming. I definitely wouldn't have gotten into programming if I hadn't played games. - Mark Zuckerberg, CEO Facebook, 5/15 Source: Elon Musk: Forbes Interview (10/1/16), Reid Hoffman: Interview on the Tim Ferris Show (8/31/15), Mark Zuckerberg: Facebook Q&A Session (5/14/15) KP INTERNET TRENDS 2017 | PAGE 149 Perhaps Interactive Gaming Evolution / Growth / Usage With Related Data Collection / Analytics / Real-Time Simulations + Engagement Has Been Helping Prepare Society for On-Going Rise of Human-Computer Interaction? KP INTERNET TRENDS 2017 | PAGE 150 1) Global Gaming = Mainstream / Evolving Rapidly / Still Early Days 2) Gaming Tools = Pervasive Online 3) Gaming Tools = Improving Human Performance 4) Gaming Platforms = Evolving @ High Speed 5) eSports = Expanding Gaming Ecosystem via Fans / Spectators 6) Gaming Experience => Technology Leadership + Innovation? Interactive Games = Motherlode of Tech Product Innovation + Modern Learning KP INTERNET TRENDS 2017 | PAGE 151 MEDIA = DISTRIBUTION DISRUPTION @ TORRID PACE KP INTERNET TRENDS 2017 | PAGE 152 Digital Leaders = Transforming Media With Better User Experiences + Lower PricesData + Scale KP INTERNET TRENDS 2017 | PAGE 153 Music = Why Streaming? Access / Choice / Discovery / Personalization / Mobile / Fewer Ads Source: Goldman Sachs Research, BPI Note: BPI Survey as of 12/15, n=1,000 (UK only). Questions: "Why did you decide to pay for a music streaming subscription?" and "Thinking about music streaming, to you, how important are the following?" 9% 19% 21% 22% 24% 27% 29% 42% Viewed Ad Offline Listening Bundled Recs from Friends / Family Listening Choice Mobile Access Get Rid of Ads Free Trial Convert Reasons for Paying for Music Streaming, 12/15 Importance of Streaming Product Features, 12/15 0% 20% 40% 60% 80% 100% Share Playlists Build Playlists Simultaneous Music Videos Curation / Recs Keep Up with Hits Support Artists Multi-Device Listening New Music Discovery Size of Catalog Very Fairly Not much Not at all KP INTERNET TRENDS 2017 | PAGE 154 Video = Why Cord-Cutting? Lower Price + Convenience Source: TiVo Q4 2016 Video Trends Report Note: Survey includes 18+ year olds in USA and Canada, n=3,079. Other categories omitted include "Not My Choice," "Share SVOD Login," "Moved In With New Roommate," "Other." 11% 13% 19% 27% 48% 80% Bulk of Viewing is Streaming Service Original Content Dropped Cable Upon Moving / Relocating Like to Binge Entire Seasons via Streaming Use Antenna to Get Basic Channels Use an Internet Streaming Service Too Expensive Reasons for Cutting Pay-TV Service, Q4:16 KP INTERNET TRENDS 2017 | PAGE 155 Digital Evolution of Music + Video = Ramping Rapidly KP INTERNET TRENDS 2017 | PAGE 156 $0 $5 $10 $15 $20 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 2015 Recorded Music Revenues ($B)Subscription & Streaming Download & Synchronization Physical Source: Recording Industry Association of America Note: "Subscription and Sttreaming" includes paid subscriptions (full and limited tier), SoundExchange, ad-supported streaming and other digital. "Download & Synchronization" includes download single / album, kiosk, download music video, ringtone / ringback, and synchronization. "Physical" includes LP / EP, vinyl single, 8-track, cassette (full / single), CD / CD single, music video, DVD audio and SACD. Recorded Music = Revenue +11% After 16 Years of -4% Annual Average Growth Subscription & Streaming @ 52% of Revenue vs. 0% Thirteen Years Ago, USA Recorded Music Revenues by Format ($B), USA, 1973-2016 KP INTERNET TRENDS 2017 | PAGE 157 Source: Spotify * Subscribers as of 3/2017, when Spotify announced they had reached the 50 million subscriber mark. Spotify = Catalyst for Internet-Driven Evolution of Music Industry 0 50MM Paid Subscribers / 126MM MAUs in <9 Years 0 500 1,000 1,500 2,000 2,500 3,000 0 10 20 30 40 50 60 2008 2009 2010 2011 2012 2013 2014 2015 2016* Spotify Global Revenue (MM)Spotify Paid Subscribers (MM)Spotify Paid Subscribers Spotify Global Revenue Spotify Subscribers (MM) & Revenue (MM), 2008 2016*, Global Q4:16 Monthly ARPU = 5.80 ($6.10) KP INTERNET TRENDS 2017 | PAGE 158 Source: Spotify, IFPI 2017 Global Music Report * Subscribers as of 3/2017, when Spotify announced they had reached the 50 million subscriber mark. Spotify = 20% of Global Music Industry Revenue vs. 0% in 2008 0% 5% 10% 15% 20% 25% 30% 0 10 20 30 40 50 60 2008 2009 2010 2011 2012 2013 2014 2015 2016* Spotify as % of Global Music RevenueSpotify Paid Subscribers (MM)Spotify Paid Subscribers (MM) Share of Global Music Revenue (%) Spotify Subscribers (MM), 2008 2016*, Global Q4:16 Monthly ARPU = 5.80 ($6.10) KP INTERNET TRENDS 2017 | PAGE 159 Source: Spotify Spotify = Users Listen to 41 Artists per Week, +40% (vs. 1/14) Owing to Recommendation Engine (Data + Algorithms) 0 10 20 30 40 50 1/14 1/15 1/16 1/17 Unique Artists Listened to per WeekTime Spotify Unique Artists Listened to Per Week, Average, Global, 1/14-1/17 KP INTERNET TRENDS 2017 | PAGE 160 Network TV* Minutes Delivered = 2011 Top 5 Networks -10% Average Netflix +669% Over 5 Years, USA Source: Matthew Ball REDEF Original 3/14/16, Nielsen, Sandvine, Netflix, SNL Kagan, BTIG Note: Inclusive of Broadcast + Basic Cable + Premium Cable, C7 Live + VOD + DVR. Does not account for multiple viewers (i.e. unique minutes delivered) or TV everywhere (though note that even if every TV Everywhere stream started in 12/15 was completed and 1 hour long, consumption would have increased national TV time by only 1.9%). 0 100 200 300 400 NBC Universal Disney 21st Century Fox Netflix CBS Time Warner Viacom Discovery A&E ESPN Monthly Minutes Delivered (B)2010-2011 (through Feb) 2015-2016 (through Feb) Monthly Minutes Delivered By Network Group, USA, 2010/11-2015/16 669% 11% 14% 30% 21% 35% 16% 33% 1% 1% KP INTERNET TRENDS 2017 | PAGE 161 $0 $600 $1,200 $1,800 $2,400 $3,000 0 20 40 60 80 100 Netflix Quarterly Revenue ($MM) Netflix Paid Subscribers (MM)Netflix Paid Subscribers (MM) Netflix Quarterly Revenue ($MM) 9/11 DVD / Streaming Split Source: Netflix Note: Netflix subscription DVD service launched 9/1998. Data before Q3 2001 represents all subscribers because paid subscribers not broken out. Netflix split streaming subs from DVD subs in Q3 2011; graph shows only streaming subs thereafter. ARPU shown ex-DVD. Netflix = Catalyst for Internet-Driven Evolution of Video Industry 95MM Streaming Subscribers in 10 Years Netflix Subscribers (MM) & Quarterly Revenue ($MM), 2/99 3/17, Global Q1:17 Streaming ARPU per Month = $9.14 9/99 DVD Subscription Launch 1/07 Streaming Launch KP INTERNET TRENDS 2017 | PAGE 162 0% 10% 20% 30% 40% 50% 0 20 40 60 80 100 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017* Share of USA Home Entertainment Revenue (%)Netflix Paid Subscribers (MM)Netflix Paid Subcribers (MM) Share of USA Home Entertainment Revenue (%) Source: Netflix Note: Share represented by Netflix domestic streaming revenue over total home entertainment revenue in USA. Domestic streaming not broken out as individual segment until 2012. Netflix split streaming subs from DVD subs in Q3 2011; graph shows only streaming subs thereafter. * Q1:17 represents Netflix annualized domestic streaming revenue figure. ARPU shown ex-DVD Netflix Streaming = From 0% to >30% of Home Entertainment Revenue in 10 Years, USA Netflix Subscribers, 2009 2017*, Global Q1:17 Streaming ARPU per Month = $9.14 9/11 DVD / Streaming Split 1/07 Streaming Launch KP INTERNET TRENDS 2017 | PAGE 163 Google Pioneered Search / Find / Obtain (SFO) for Content + Products Netflix + Spotify Pioneered Search / Find / Serve Up (SFS) for Media Source: Netflix; Spotify; Michelle Ufford, "Data-Driven at Netflix", talk given at PASS 10/31/16; Gomez-Uribe and Hunt (both Netflix), "The Netflix Recommender System: Algorithms, Business Value, And Innovation", ACM Transactions on Management Information Systems 6.4, 12/15 Note: Netflix estimated cost savings due to improved engagement and reduction of monthly churn, driving lower need for subscriber acquisition cost in the future. 98MM Different Netflixes... $1B cost savings / year from recommendations (12/15) 126MM Different Spotifys ~5B Discover Weekly streams in <1 year post-launch (5/16) From Give to GetWith Data + Algorithms KP INTERNET TRENDS 2017 | PAGE 164 Digital Evolution of Music + Video = Multiple Approaches KP INTERNET TRENDS 2017 | PAGE 165 Facebook / Instagram / Snap = Mobile Video Traffic Share Gainers Over 4 Years Source: Sandvine Global Internet Phenomena Report (2H 2012 and 2016) 0% 5% 10% 15% 20% 25% 30% 35% 40% YouTube Facebook Instagram Snap Netflix iTunes Google Cloud HTTP / SSL - Other Other 2012 2016 Share of Downstream Video Traffic (%), North America, 2H 2016 KP INTERNET TRENDS 2017 | PAGE 166 Netflix / YouTube = Fixed-Access Video Traffic Share Leaders 0% 5% 10% 15% 20% 25% 30% 35% 40% Netflix YouTube Amazon Video iTunes Hulu Xbox One FacebookBitTorrent HTTP / SSL - Other Other 2012 2016 Share of Downstream Video Traffic (%), North America, 2H 2016 Source: Sandvine Global Internet Phenomena Report (2H 2012 and 2016) KP INTERNET TRENDS 2017 | PAGE 167 Facebook Platform MAUs, Global, Months Since Launch Facebook (Facebook / WhatsApp / Messenger / Instagram) = Video Ramping Across Platform Source: Facebook, Instagram, Whatsapp, Financial Times, TechCrunch 0 500 1,000 1,500 2,000 2,500 0 12 24 36 48 60 72 84 96 108 120 132 144 156 MAU (MM)Months Since Founding Instagram Facebook WhatsApp Facebook Messenger KP INTERNET TRENDS 2017 | PAGE 168 Snap = Ramping Original Short-Form Content Snap 'Original Shows' Source: Snap Second Chance 8MM+ Views for 1st Episode, 5/17 Phone Swap 10MM+ Views for 1st Episode, 5/17 KP INTERNET TRENDS 2017 | PAGE 169 Generational Media Usage = Chasm Increasing Shifts to Internet-Enabled Media Continue KP INTERNET TRENDS 2017 | PAGE 170 7:16 7:12 7:06 4:14 2:44 2:17 Q4:16 Q4:15 Q4:14 Analog Digital Mobile Device Time per Day = +2x Over 2 Years Daily Time Spent by Media (Not De-Duped), USA, Q4:14-Q4:16 Source: Nielsen Total Audience Report Q4:16 Note: "Analog" includes Live / DVR / Time-shifted TV, DVR / time-shifted TV, AM / FM radio, DVD / Blu-ray, and game consoles. "Digital" includes Multimedia devices (viewing on Apple TV, Roku, Chromecast, smartphone, computer etc. connected to TV), internet on PC, video on PC, app / web on smartphone / tablet, and video on smartphone. KP INTERNET TRENDS 2017 | PAGE 171 Mobile Device Time per Day = 18-24 Year-Olds @ 49% Digital65+ Year-Olds @ 13%, USA 9:49 9:09 7:17 5:42 4:35 1:30 4:41 5:19 4:42 4:27 65+ 50-64 35-49 25-34 18-24 Analog Digital Daily Time Spent by Media & Age Bracket (Not De-Duped), USA, Q4:16 Source: Nielsen Total Audience Report Q4:16 Note: "Analog" includes Live / DVR / Time-shifted TV, DVR / time-shifted TV, AM / FM radio, DVD / Blu-ray, and game consoles. "Digital" includes Multimedia devices (viewing on Apple TV, Roku, Chromecast, smartphone, computer etc. connected to TV), internet on PC, video on PC, app / web on smartphone, and video on smartphone. KP INTERNET TRENDS 2017 | PAGE 172 Traditional Cable Conundrum = Channels + Consumer Prices + Programming Costs Rising Subscribers Falling KP INTERNET TRENDS 2017 | PAGE 173 Pay TV Household Growth = -1.3% Average for Last 12 Quarters While Programming Costs >2x+ since 2006 Source: Nielsen Total Audience / Cross Platform Reports, US Census Bureau, St. Louis Federal Reserve FRED Database Note: Pay TV households represented by Nielsen "Cable Plus" metric, which includes households who receive television via Wired Cable (No Telco), Telco, or Satellite. "Programming Costs" includes total program and production costs for Cable and Other Subscription Programming firms, 2006-2015, as per US Census Services Annual Survey for Employer Firms ($25B in 2015, up from $12B in 2006). Pay TV Households (MM), USA, 2010-2016 (5%) (3%) (1%) 1% 3% 5% 60 70 80 90 100 110 120 Q1:10Q2:10Q3:10Q4:10Q1:11Q2:11Q3:11Q4:11Q1:12Q2:12Q3:12Q4:12Q1:13Q2:13Q3:13Q4:13Q1:14Q2:14Q3:14Q4:14Q1:15Q2:15Q3:15Q4:15Q1:16Q2:16Q3:16Q4:16% Y/Y GrowthTotal TV Channels Received in USAPay TV Households (MM) % Y/Y Growth KP INTERNET TRENDS 2017 | PAGE 174 # TV Channels Watched <10% of Channels Received Pay TV ARPU 10-15x > Netflix Source: Nielsen, Matthew Ball & Tal Shachar, REDEF Original 3/9/16, DirecTV, AT&T, Charter, Dish Network, Comcast Note: TV channel data as of mid-year. DirecTV ARPU calculated by dividing the 2016 Video Entertainment revenue by the average number of Linear Video Connections during 2016. Charter ARPU calculated by dividing 2016 Video revenue by average Video Residential Primary Service Units during 2016. Dish Network ARPU calculated by multiplying the 2016 Pay-TV Average Monthly Revenue per Subscriber by 12. Comcast ARPU calculated by dividing the 2016 Residential Video revenue by the average Video Customers in 2016. Netflix ARPU is based off the Global Streaming revenue and average subscribers in 2016. All estimates are global. Average TV Channels Received vs. Watched per Household, USA, 2008-2016 0% 5% 10% 15% 20% 25% 0 50 100 150 200 250 % WatchedTotal TV Channels Received in USATV Channels Received % Channels Watched $103 $997 $1,064 $1,131 $1,439 Netflix Comcast Dish Charter DirecTV Annual ARPU, Selected Platforms, 2016 Pay TV Digital Platforms KP INTERNET TRENDS 2017 | PAGE 175 Digital Subscriptions = Rising Owing to Massive User Experience Improvements On-Demand / A La Carte Selection + Choice / Personalization / Payment Systems / 2-Way UGC / Mobile... KP INTERNET TRENDS 2017 | PAGE 176 Media Evolution (1950-2017) = Market of Millions Market of One x Millions Source: Amanda Lotz, The Television Will Be Revolutionized, New York: NYU Press, 2007, Wikimedia Commons, Google Image Commons, Crunchyroll, Shudder, Fandor, Seeso, Cheddar, Fullscreen Cater to Sub-Genres / Power Users / A La Carte + Subscription Network Era 1950s-1980s Cable Era 1980s-2010s Digital Era Current Broad Genres / Focus on Programming / Limited Bundle Choices Cater to All / High Viewership / No Personalization Digital Distributors Digital Studios KP INTERNET TRENDS 2017 | PAGE 177 Media = Distribution Disruption @ Torrid Pace 1) Digital Leaders = Transforming Media With Better User Experiences + Lower PricesData + Scale 2) Generational Media Usage = Chasm Increasing as Shifts to Internet-Enabled Media Continue 3) Traditional Cable Conundrum = Channels + Consumer Prices + Programming Cost RisingSubscribers Falling 4) Digital Subscriptions = Rising Owing to Massive User Experience Improvements (On-Demand / Selection + Choice / Personalization / Payment Systems / 2-Way UGC / Mobile...) KP INTERNET TRENDS 2017 | PAGE 178 THE CLOUD = ACCELERATING CHANGE ACROSS ENTERPRISES ALEX KURLAND @ KLEINER PERKINS KP INTERNET TRENDS 2017 | PAGE 179 1) Cloud Adoption = Reaching New Heights + Creating New Opportunities 2) Enterprise Software = Customer Expectations Mirroring Those of Consumer Apps 3) Security = More Applications More Vulnerabilities The Cloud = Accelerating Change Across Enterprises KP INTERNET TRENDS 2017 | PAGE 180 Cloud Adoption = Reaching New Heights + Creating New Opportunities KP INTERNET TRENDS 2017 | PAGE 181 Public + Private Clouds = Approaching Traditional Data Center Spend +37% to $36B vs. 2014 76% 72% 67% 63% 14% 17% 20% 22% 9% 11% 13% 15% 0% 25% 50% 75% 100% 2013 2014 2015 2016 % of Total IT Infrastructure SpendIT Infrastructure Spend, Global, 2014-2016 Traditional Data Center Public Cloud Private Cloud Source: IDC Worldwide Quarterly Cloud IT Infrastructure Tracker; Gartner; CloudHealth estimates KP INTERNET TRENDS 2017 | PAGE 182 Public Cloud Adoption Trends = AWS Maintains LeadAzure + Google Rising 57% 20% 10% 7% 57% 34% 15% 8% AWS Azure Google Cloud IBM 2016 2017 Public Cloud Adoption, 2016 vs. 2017 % of Respondents Running Applications 57% 34% 15% 8% 17% 21% 17% 9% 10% 12% 13% 8% AWS Azure Google Cloud IBM Running Apps Experimenting Planning to Use Public Cloud Adoption, 2017 % of Respondents Running, Experimenting, or Planning to Use Applications Source: Rightscale 2017 State of the Cloud Report Note: Based on survey of IT Professionals, n=1,002. KP INTERNET TRENDS 2017 | PAGE 183 Cloud Concerns = Shifting from Data Security + Cost Uncertainty Vendor Lock-In + Compliance / Governance 42% 38% 33% 21% 21% 18% 14% 7% 35% 21% 19% 27% 14% 20% 18% 22% Data Security Uncertainty of Costs and Savings Loss of Control (Upgrades, Timing of Backups) Compliance / Governance Reliability (SLA Requirements) Data Portability and Ownership Software Compatability Lock-In (ability to change vendors) 2012 2015 Share of Respondents Citing Criteria as Top-Three Concern, USA, 2012-2015 Source: Bain Cloud Computing Survey, 2015 (n=347); Morgan Stanley AlphaWise Survey of IT Managers (n=304) KP INTERNET TRENDS 2017 | PAGE 184 Cloud Evolution / Tools = Paving Way for Innovation Across Infrastructure Landscape Containers / Microservices = Simplify software development process / improve consistency between testing & production environments / reduce complexity of managing & updating apps due to modular approach Edge Computing = Pushing compute away from centralized nodes & closer to sources of data addresses many IT challenges when running data-centric workloads in cloud reduces latency / can have security + compliance benefits Elastic Analytical Databases = Likes of Google BigQuery / Snowflake / AWS Redshift Spectrum nearly infinitely scalable / usage based + have minimal maintenance requirements New Methods of Software Delivery = APIs / Browser Extensionscreating new wave of capabilities (+ companies) for both companies and end users Source: Lloyd Tabb, Looker Founder & CTO; Happiest Minds; Azuqua; TheServerSide; Forbes KP INTERNET TRENDS 2017 | PAGE 185 New Cloud Companies Emerging Providing Elegant + Intuitive Experiences for End Users Rubrik Managing data across cloud & on-prem infrastructure, approaching $100MM in annualized bookings Stripe Processing billions of transactions a year across 100K+ businesses in 100+ countries Looker Empowering data analysis for 40K users across every department, each averaging 2 new queries every day CloudHealth Actively managing more than 1.3MM policies globally for hybrid & multi-cloud environments Source: Company-provided & publicly available data; Snipcart KP INTERNET TRENDS 2017 | PAGE 186 Enterprise Software = Customer Expectations Mirroring Those of Consumer Apps KP INTERNET TRENDS 2017 | PAGE 187 Enterprise Software (2000 2017) = Users Expect Products to be as Well Designed / Easy-to-Use / Reliable as Consumer Apps Perpetual, On-Premise Software Cloud-Based SaaS Apps Mobile-First Smart Apps 2000 2017 Delivery Method On-Prem Cloud-based Pricing Perpetual License Subscription UX Generic Personalized Intelligence Constrained Unlimited (AI / ML) Growth Engine Sales Product Purchase Decision Top-Down Bottoms-Up Measure of Engagement & Customer Satisfaction N/A DAUs / MAUs / NPS KP INTERNET TRENDS 2017 | PAGE 188 Design = Increasingly Core to Enterprise R&D End-Users Demanding Consumer-Quality Product Experiences Change in Designer : Developer Ratio, Selected Enterprises, 2010-2017 Source: Company data, Figma Note: Ratios for entire orgs, unless noted otherwise. Atlassian historical ratio from 2012; Dropbox data for product org only; IBM historical ratio from 2012, data for product org only; Intercom data for product org only; LinkedIn historical ratio from 2010. 2010 - 2012 2017 1 designer : 1 designer : 25 developers 9 developers 1 designer : 1 designer : 10 developers 6 developers 1 designer : 1 designer : 8 developers 72 developers On Mobile 1 designer : 3 developers 1 designer : 5 developers N/A 1 designer: 1 designer : 11 developers 8 developers N/A KP INTERNET TRENDS 2017 | PAGE 189 Security = More Applications More Vulnerabilities KP INTERNET TRENDS 2017 | PAGE 190 Cloud-Enabled App Use in Enterprises = Rising Rapidly Cheaper to Build / Easier to Adopt / Harder to Secure Avg. # of Cloud Apps Used by Vertical, Global, April 2017 Avg. # of Cloud Services used by Category, Global, April 2017 This has serious security & compliance implications... 94% of all cloud apps used are not "enterprise-ready," per Netskope 1,206 1,170 1,092 907 893 0 200 400 600 800 1,000 1,200 1,400 Retail, Restaurants, & Hospitality Financial Services, Banking, & Insurance Manufacturing Healthcare & Life Sciences Technology & IT services Avg. Cloud Services Used per EnterpriseCategory # Per Enterprise % Not Enterprise Ready Marketing 91 97% HR 90 96% Collaboration 70 87% Finance / Accounting 60 95% CRM / Sales 43 94% Software Development 41 96% Productivity 37 95% Social 30 91% Cloud Storage 27 72% IT Service / Application Management 25 98% Source: Netskope April 2017 Note: 461 cloud apps in April 2017, one year ago = average of 917 from Feb-16 report & 935 from Jun-16 report; "Not enterprise ready" = received a rating of "medium" or below in the Netskope Cloud Confidence Index. KP INTERNET TRENDS 2017 | PAGE 191 Network Breaches = Increasingly Caused by Email Spam / Phishing Spam +350% vs. Q1:15 Monthly Average 0% 50% 100% 150% 200% 250% 300% 350% 400% 450% Spam Without Malicious Attachments Spam With Malicious Attachments Change in Amount & Type of Spam, Global, 2015-2016 Indexed to Q1:15 Monthly Average Source: AntiPhishing Working Group Phishing Activity Trends Report - Q4 2016; IBM X-Force Threat Intelligence Index 2017 % Change in Spam (Indexed to Q1:15 Monthly Average) KP INTERNET TRENDS 2017 | PAGE 192 Cyber Threats Severity Rising = 10MM+ Identities Exposed in 15 Breaches in 2016vs. 11 in 2014 0% 25% 50% 75% 100% 2012 2013 2014 2015 2016 % of Internet Traffic by Source% Human % Bot 0 2 4 6 8 10 12 14 16 2014 2015 2016 # Breaches with 10MM+ Identities ExposedBreaches with 10MM+ Identities Exposed, Global, 2014-2016 % of Internet Traffic by Source, Global, 2012-2016 Source: Incapsula 2016 Bot Traffic Report (100k Randomly Selected Domains); 2017 Verizon Data Breach Investigations Report KP INTERNET TRENDS 2017 | PAGE 193 CHINA INTERNET = GOLDEN AGE OF ENTERTAINMENT + TRANSPORTATION *Disclaimer The information provided in the following slides is for informational and illustrative purposes only. No representation or warranty, express or implied, is given and no responsibility or liability is accepted by any person with respect to the accuracy, reliability, correctness or completeness of this Information or its contents or any oral or written communication in connection with it. Hillhouse Capital may hold equity stakes in companies mentioned in this section. A business relationship, arrangement, or contract by or among any of the businesses described herein may not exist at all and should not be implied or assumed from the information provided. The information provided herein by Hillhouse Capital does not constitute an offer to sell or a solicitation of an offer to buy, and may not be relied upon in connection with the purchase or sale of, any security or interest offered, sponsored, or managed by Hillhouse Capital or its affiliates. KP INTERNET TRENDS 2017 | PAGE 194 China Macro = Positive Trends KP INTERNET TRENDS 2017 | PAGE 195 48% 49% 50% 51% 52% 53% 90 95 100 105 110 115 1/14 4/14 7/14 10/14 1/15 4/15 7/15 10/15 1/16 4/16 7/16 10/16 1/17 Manufacturing PMI Index Consumer Confidence IndexChina Consumer Confidence Index (LHS) China Manufacturing PMI (RHS) China Macro = Confidence Improving Since CH2:16 Source: China National Bureau of Statistics, Bernstein Research Consumer Confidence Index & Manufacturing PMI Index, China, 1/14 3/17 KP INTERNET TRENDS 2017 | PAGE 196 China Macro = Service Sector @ 52% GDP Share vs. 23% Thirty-Five Years Ago 0% 10% 20% 30% 40% 50% 60% 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011 2016 % of GDPService Sector Output as % of Nominal GDP, China, 1961 2016 Source: China National Bureau of Statistics, Morgan Stanley Research Note: Service sector defined as all industries outside of agriculture, forestry, animal husbandry and fishery industries (except support services to agriculture, forestry, animal husbandry and fishery industries), mining (except auxiliary activities of mining), manufacturing (except repairs for metal products, machinery and equipment), production and supply of electricity, steam, gas and water, and construction. KP INTERNET TRENDS 2017 | PAGE 197 5% 21% 48% 0% 10% 20% 30% 40% 50% 2005 2010 2016 % of MSCI China Market CapChina Macro = Private (Non-SOEs) Enterprises Increasingly Driving Wealth Creation + Economic Growth + Jobs Source: Morgan Stanley Research, MSCI *SOE = State Owned Enterprise. Private Enterprise (Non-SOE*) % Share of MSCI China Weighted Market Cap KP INTERNET TRENDS 2017 | PAGE 198 China Macro = Technology Companies Lead Public Market Wealth Creation 0% 20% 40% 60% 80% 100% Telecommunication Services Energy Utilities Industrials Consumer Staples Materials Overall MSCI China Financials Consumer Discretionary Health Care Information Technology 2016 2005 Source: Morgan Stanley Research, MSCI *SOE = State Owned Enterprise. Private Enterprise (Non-SOE) % of MSCI China Market Cap by Sector, 2005 vs. 2016 KP INTERNET TRENDS 2017 | PAGE 199 China Internet Users + Usage = Healthy User Growth Usage Outpacing Users KP INTERNET TRENDS 2017 | PAGE 200 Mobile Internet Users & Y/Y Growth, China, 2008 2016 Source: CNNIC Note: Internet user data is as of year-end. 0% 10% 20% 30% 40% 50% 60% 70% 0 100 200 300 400 500 600 700 2008 2009 2010 2011 2012 2013 2014 2015 2016 % Y/Y GrowthChina Mobile Internet Users (MM)China Mobile Internet Users Y/Y Growth China Mobile Internet Users = @ ~700MM, +12% Y/Y vs. 11% in 2015 KP INTERNET TRENDS 2017 | PAGE 201 Source: Hillhouse estimates based on daily media time spent data from ZenithOptimedia and mobile data from QuestMobile 0% 15% 30% 45% 60% 75% 90% 0 500 1,000 1,500 2,000 2,500 3,000 2012 2013 2014 2015 2016 % Y/Y GrowthDaily Time Spent (Hours MM)Mobile Internet Time Spent Mobile Internet Time Spent Y/Y Mobile Internet User Y/Y China Mobile Internet Usage Outpacing User Growth = +30% Y/Y for Usage+12% for Users Estimated Mobile Internet Daily Time Spent, China, 2012 - 2016 KP INTERNET TRENDS 2017 | PAGE 202 China Entertainment = Online Innovation Driving Robust User + Usage + Monetization Growth KP INTERNET TRENDS 2017 | PAGE 203 Source: Zenith Optimedia 0% 10% 20% 30% 40% 50% 60% 70% 0 50 100 150 200 250 300 350 2012 2013 2014 2015 2016 Internet as % of Media ConsumptionDaily Media Consumption (Minutes)Radio TV Magazine Newspaper Desktop Internet Mobile Internet Internet as % of Total Media China Media = Internet @ 55% of Time SpentMobile > TV (2016) Average Daily Media Consumption Minutes by Medium, China, 2012 - 2016 KP INTERNET TRENDS 2017 | PAGE 204 0 500 1,000 1,500 2,000 2,500 3,000 3,500 11/1412/141/152/153/154/155/156/157/158/159/1510/1511/1512/151/162/163/164/165/166/167/168/169/1610/1611/1612/161/172/173/174/17Average Daily Hours (MM)WeChat QQ Tencent Games Tencent Video Tencent News Tencent Music Tencent Other UC Browser Weibo Taobao / Tmall Youku Alibaba Other iQiyi Mobile Baidu Baidu Other Toutiao NetEase All Other TencentBaiduAlibabaChina Mobile Internet Daily Hours By App, 11/14 4/17 China Entertainment = Key Driver of Mobile Time Spent eCommerce + Games = Monetize Best Per Time Spent Source: QuestMobile Note: Only top 100 apps by time spent are categorized by company affiliation. Tencent, Alibaba and Baidu affiliates include strategically invested companies. KP INTERNET TRENDS 2017 | PAGE 205 China Online Entertainment = Consumers Increasingly Willing to Pay Led by Games + Livestreaming + Video $0 $10 $20 $30 $40 2011 2012 2013 2014 2015 2016 Annual Revenue ($B)Online Game Online Video Online Literature Livestreaming Digital Music Source: Game industry data per per Newzoo and Hillhouse estimates, excludes console or PC hardware related revenue. Online video data per iResearch (China) and Hillhouse estimates (USA), excludes advertising related revenue. Digital music data (excl. advertising) per iResearch (China) and RIAA (USA). Livestreaming (China) data per Hillhouse estimates. eBook data per Hillhouse estimates (China) and AAP and Hillhouse estimate (USA) $0 $10 $20 $30 $40 2011 2012 2013 2014 2015 2016 Annual Revenue ($B)Online / Console Game Online Video eBook Digital Music Online Entertainment User-Pay Revenue By Vertical, China, 2011-2016 Online Entertainment User-Pay Revenue By Vertical, USA, 2011-2016 KP INTERNET TRENDS 2017 | PAGE 206 $0 $5 $10 $15 $20 $25 $30 2012 2013 2014 2015 2016 2017E Video Game (excl. Hardware) Revenue ($B)China USA EMEA Asia (ex. China) Source: Newzoo * Excluding console / gaming PC hardware revenue. Global Interactive Game Revenue = China #1 Market in World* > USA (2016) Interactive Game Software Revenue by Region, Global, 2012 2017E KP INTERNET TRENDS 2017 | PAGE 207 Tencent Honor of Kings Mobile Multiplayer Online Battle Arena (MOBA) Leader 50MM+ DAU, $3B+ Annualized Bookings Driven by Social + Simple UI + Constant Product Improvement NetEase Portfolio of Leading Mobile Massively Multiplayer Online Role Playing Games (MMORPGs) Driven by Mobile First Mover Advantage + IP + Social Design + Quality Production China Online Gaming = Tencent + NetEaseMobile MOBA + MMORPG Game Leaders Source: Tencent, NetEase KP INTERNET TRENDS 2017 | PAGE 208 $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 $3,500 $4,000 Revenue ($MM)PC Mobile China Online Gaming = Tencent + NetEase Driving Mobile Innovation + Revenue $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 $3,500 $4,000 Revenue ($MM)PC Mobile Source: Tencent, NetEase, Goldman Sachs Investment Research Note: Assuming 1USD = 6.9RMB. NetEase Online Game Revenue, PC vs. Mobile, Q1:14-Q1:17 Tencent Online Game Revenue, PC vs. Mobile, Q1:14-Q1:17 KP INTERNET TRENDS 2017 | PAGE 209 Diverse Live Content Type Singing / Dancing / Talk Show / Game Play Local / Social Nearby Livestreams / Chat & Add Friends China Livestreaming = High Consumer Engagement + Willingness to Pay Interactive / Social / Gamified Like / Chat with Hosts & Audience / Buy Virtual Gifts to Support Performers 20+ Virtual Gift Categories priced from Rmb0.01 Source: Hillhouse research KP INTERNET TRENDS 2017 | PAGE 210 $0.00 $0.20 $0.40 $0.60 Online Music Radio Online Video TV Online Games Livestreaming Source: Hillhouse estimates based on Newzoo, iResearch, Questmobile, and select company disclosures Note: Revenue data includes subscription, advertising and paid download revenue streams. China Livestreaming = Compelling Monetization Estimated Revenue per Hour, China, 2016 KP INTERNET TRENDS 2017 | PAGE 211 China On-Demand Transportation = #1 Global Market Cars + Bikes KP INTERNET TRENDS 2017 | PAGE 212 China On-Demand Transportation (Cars + Bikes) = Global Leader @... ~67% Global Share (10B+ Annualized Trips, + >2x Y/Y) Source: Hillhouse Capital estimates, include on-demand taxi, private for-hire vehicles, as well as on-demand for- hire motorbike and bike trips booked through smartphone apps On-Demand Transportation Trip Volume by Region, Global, Q1:13 Q1:17 0 1,000 2,000 3,000 4,000 1Q13 1Q14 1Q15 1Q16 1Q17 Quarterly Completed Trips (MM)ROW SE Asia India EMEA N. America China Bike China Car Q1:13 Q1:14 Q1:15 Q1:16 1:17 KP INTERNET TRENDS 2017 | PAGE 213 China On-Demand Bike Sharing = Mobile Innovation Driving Significant Usage Ramp In-Bike GPS + Smartphone Bike Sharing Without StationsLocation-Based Virtual Red Envelope Drives Utilization QR Code + Mobile Payment Easy Unlock & Low Friction Payment Ubiquity + Low Cost (1/~$0.15 per 30 min) + Convenience Mass Adoption & Bike Utilization Mobike Product Innovation Source: Mobike KP INTERNET TRENDS 2017 | PAGE 214 0% 20% 40% 60% 80% 100% 120% 0 5 10 15 20 25 7/16 8/16 9/16 10/16 11/16 12/16 1/17 2/17 3/17 % M/M GrowthChina Bike Sharing MAU (MM)China On-Demand Bike Sharing MAUs M/M Growth Source: TrustData Note: Dip in M/M growth rate in 1/17 was driven by Chinese New Year. China On-Demand Bike Sharing = @ 20MM+ MAU100%+ M/M Accelerating Growth China On-Demand Bike Sharing MAU, 7/16 3/17 KP INTERNET TRENDS 2017 | PAGE 215 China On-Demand Bike Sharing = High Frequency 2/3 Users Ride 3+ Times Per Week Commute 50% Leisure / Exercise 29% Shopping 12% Business 3% School 1% Other 5% <1x 9% 1-2x 25% 3-5x 32% 6-10x 18% 10+ 16% Source: Transport Commission of Shenzhen Municipality study on bike sharing, based on operating data from four participating companies and survey data between 10/16 and 3/17, n=16,546 Highlights from Shenzhen Municipality On-Demand Bike Sharing Study, 5/17 On-Demand Bike Trips per Week Purpose of On-Demand Bike Trips KP INTERNET TRENDS 2017 | PAGE 216 On-Demand Bike Sharing = Positive Environmental Impact + High Customer Satisfaction Source: Transport Commission of Shenzhen Municipality study on bike sharing, based on operating data from four participating companies and survey data between 10/16 and 3/17, n=16,546 * Based on following assumptions 250k reduction in daily private car trips, avg. trip length of 10km, avg. fuel consumption of 6.9 L/100km, avg. CO2 emission of 2kg/L of fuel. Highlights from Shenzhen Municipality On-Demand Bike Sharing Study, 5/17 11MM Registered Users in Shenzhen, China 530K Available Bikes 2.6MM Daily Trips 5 Trips per Available Bike per Day 50% On-Demand Bike Trips Serving as Last-Mile Connection to Public Transit Trips 10% Bike Trips Replacing Private Car Driving Trips 100K+ Tons Reduction in Annual CO2 Emission* 95% Respondents Support Continued Development of Bike Sharing KP INTERNET TRENDS 2017 | PAGE 217 China On-Demand Bike Sharing = Complements On-Demand Cars @ 75% Shorter Trip Distance & 80% Lower Cost per Mile On-Demand Car Share (Didi) On-Demand Bike Share (Mobike / Ofo) Average Trip Distance 8 KM ~5 Miles 2 KM 1.2 Miles Average Trip Cost 20 RMB ~3 USD ~1 RMB ~0.15 USD Cost per Km ~2.50 RMB ~0.50 RMB Cost per Mile ~0.60 USD ~0.12 USD Source: On-demand car share data per Hillhouse estimate. On-demand bike share data per Transport Commission of Shenzhen Municipality study on bike sharing, based on operating data from four participating companies and survey data between 10/16 and 3/17, n=16,5466.92 KP INTERNET TRENDS 2017 | PAGE 218 China Mobile Payment Infrastructure = Enabling Rapid Growth + Monetization of Internet Usage KP INTERNET TRENDS 2017 | PAGE 219 China Mobile Payment Volume = +2x Y/Y to $5T+ Led by AliPay + WeChat Pay Source: Analysys *Excludes certain P2P and transfer payments. Assume constant FX rate of 1USD = 6.9RMB. $0 $1,000 $2,000 $3,000 $4,000 $5,000 $6,000 2012 2013 2014 2015 2016 China Mobile Payment Volume ($B)AliPay 54% WeChat Pay 40% Others 7% China Mobile Payment Volume, 2012 - 2016 China Mobile Payment Market Share*, Q1:17 KP INTERNET TRENDS 2017 | PAGE 220 China Mobile Payments = Convenience vs. Cash & Bank Cards Small Transactions Growing Especially Fast (<100RMB / $15) Source: PCAC, Bernstein Analysis Size of Mobile Payment Transactions, 2012 - 2016 Reasons for Using Mobile Payments, 2012 - 2016 0% 20% 40% 60% 80% 100% 2014 2015 2016 0% 20% 40% 60% 80% 100% 2014 2015 2016 KP INTERNET TRENDS 2017 | PAGE 221 AliPay + WeChat Pay on Mobiles = Digitizing Micro Payments On + Offline ~$0.15 for On-Demand Bike ~$0.15 for On-Demand Mobile Recharge $0.01+ for Article / Author Tipping $0.01+ for Livestreaming Tipping $0.50+ for Street Food Source: Hillhouse estimates KP INTERNET TRENDS 2017 | PAGE 222 0bps 100bps 200bps 300bps Cash* WeChat / AliPay China Bank Cards USA Debit Card USA Credit Card PayPal Merchant Discount Rate (basis points)China Mobile Payments = Low Relative Cost Helped by Regulated Interchange Rates Source: Hillhouse estimates based on published rate schedule, JPMorgan Research estimates and transaction take rate for PayPal in 2016 *Cash payment there is no merchant discount rate, ~40bps of marginal cost of processing cash payment is an estimate per European Commission study in 2014. USA debit and credit card merchant discount rate is an estimated offline average, online (card-not-present) merchant discount rate is higher. Average Merchant Discount Rate, Basis Points (100bps = 1%) KP INTERNET TRENDS 2017 | PAGE 223 Payment Wealth Management Financing Insurance Credit Rating / History Ant Financial 451MM Annual Active Users1 >300MM Cumulative Users2 >100MM Cumulative Consumer Finance Users3, >5MM Cumulative SME Borrowers4 380MM Cumulative Users5 130MM Cumulative Users6 Tencent >600MM MAU7 >80MM Cumulative Users8 >30MM Cumulative Users9 JD Finance 119MM Annual Active Users10 >20MM Cumulative Users11 >30MM Cumulative Users11 168MM Cumulative Users11 >35MM Cumulative Users11 Mobile Payments = Gateway for China Internet Leaders to Become Diversified Financial Services Platforms Source: Alibaba / Ant Financial, Tencent, JD Finance 1Number of users of Alipay with one or more successful transactions in 2015; 2As of 3/16; 3As of 4/17; 4As of 1/17; 5As of 2015; 6As of 3/16; 7For 12/16; 8As of 11/16; 9As of 5/17; 10As of 12/16; 10Number of users of JD Pay with one or more successful transactions in 2016; 11As of 5/17 YU'E BAO ANT CASH NOW ANT CREDIT PAY KP INTERNET TRENDS 2017 | PAGE 224 China eCommerce + Advertising = Innovation + Growth KP INTERNET TRENDS 2017 | PAGE 225 China eCommerce = Strong Growth +24% Y/Y @ $681B GMV71% Mobile 0% 100% 200% 300% 400% $0 $200 $400 $600 $800 2012 2013 2014 2015 2016 % MobileY/YGrowthB2CeCommerceGMV($B)Desktop Mobile Mobile Y/Y Growth Source: iResearch Note: Assuming constant FX 1USD = 6.9RMB China B2C eCommerce Gross Merchandise Value ($B), Desktop vs. Mobile, 2012 - 2016 KP INTERNET TRENDS 2017 | PAGE 226 China B2C eCommerce @ 15% of Retail Sales Penetration Ramping Faster Than Peers 0% 5% 10% 15% 20% 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 % eCommercePenetrationKorea UK China USA Germany Japan France Brazil B2C eCommerce as % of Retail Sales by Country, 2002 - 2016 Source: Euromonitor KP INTERNET TRENDS 2017 | PAGE 227 Alibaba = Massive Scale + Engagement + Innovation Source: Alibaba Note: MAU data as of 3/17, DAU/MAU ratio data refers to mobile Taobao app, as of 5/16. Daily time spent per DAU limited to Taobao app, per QuestMobile data in 4/17. GMV generated from recommendations data are indexed, 4/15 vs. 4/16. Taobao App with Livestreaming / Microblog / Personalization Cainiao Logistics Smart Label / Routing GMV Generated from Recommendations, 2015-2016 2015 2016 507MM Mobile MAUs, +24% Y/Y41% DAU/MAU Ratio 24+ Minutes Daily Time Spent per User KP INTERNET TRENDS 2017 | PAGE 228 JD.com = World Class Fulfillment + Delivery91% / 58% Orders* Delivered Within 2 Days / 1 Day, Up from 68% / 47% Four Years Ago Source: JD.com *Orders exclude third party sellers. **Defined as JD's 211 program any orders received by 11am will be delivered on the same day, and any orders received by 11pm will be delivered by 3pm on the following day. Bulk of orders are delivered within 3-18 hours. Customers also can request that orders placed by 3pm be delivered in the evening on the same day in selected cities. There is no extra charge for delivery under the 211 program for orders that satisfy the minimum size requirement. The program does not cover delivery to addresses through third-party couriers or products shipped directly from third-party sellers. Bulky items such as refrigerators are also eligible for same-day or next-day delivery in selected areas. Customers can also request expedited delivery within two hours by paying an extra charge in select cities. JD's 211 service covered 1,410 counties and districts across China as of 2016. 2017 YTD data as of Q1. 0% 20% 40% 60% 80% 100% 2013 2014 2015 2016 2017 YTD % of First Party Orders DeliveredWithin Two Days Within 24 Hours** JD.com % of First-Party Orders Delivered by Speed, 2013 2017 YTD KP INTERNET TRENDS 2017 | PAGE 229 0% 10% 20% 30% 40% 50% $0 $10 $20 $30 $40 $50 2012 2013 2014 2015 2016 % Y/YGrowthOnlineAdvertising($B)Online Advertising Y/Y Growth China Online Advertising Revenue = +30% Y/Y @ $40B Source: iResearch Note: Assuming constant FX 1USD = 6.9RMB. China Online Advertising Revenue, 2012 - 2016 KP INTERNET TRENDS 2017 | PAGE 230 Algorithmic Mobile Newsfeeds = Driving Usage + Advertising Growth (Toutiao / Baidu / Weibo / Tencent) 0% 50% 100% 150% 200% $0 $2,000 $4,000 $6,000 $8,000 2014 2015 2016 2017E % Y/YGrowthMobileNewsfeedAdvertising($MM)Mobile Newsfeed Advertising Y/Y Growth Toutiao / Baidu / Weibo / Tencent Mobile Newsfeeds with Personalization China Mobile Newsfeed Advertising Revenue & Y/Y Growth, 2014 2017E Source: iResearch Note: Assuming constant FX 1USD = 6.9RMB. KP INTERNET TRENDS 2017 | PAGE 231 1) Macro = Positive Trends 2) Internet = Healthy User GrowthUsage Outpacing Users 3) Entertainment = Online Innovation Driving Robust User + Usage + Monetization Growth 4) On-Demand Transportation = China #1 Global MarketCars + Bikes 5) Mobile Payment Infrastructure = Enabling Rapid Growth + Monetization of Internet Usage 6) eCommerce + Advertising = Innovation + Growth China Internet = Golden Age of Entertainment + Transportation KP INTERNET TRENDS 2017 | PAGE 232 INDIA INTERNET = COMPETITION CONTINUES TO INTENSIFY CONSUMERS WINNING KP INTERNET TRENDS 2017 | PAGE 233 India Economy (GDP) = Fastest Large Grower +7% Y/Y @ #7 Global GDP Rank Source: IMF, 4/2017 Note: Y/Y growth based on constant prices. $1,233 $1,281 $1,411 $1,799 $1,851 $2,256 $2,463 $2,629 $3,467 $4,939 $11,218 $18,569 $0 $5,000 $10,000 $15,000 $20,000 $25,000 Spain Russia Korea Brazil Italy India France UK Germany Japan China USA 2016 GDP (Current Prices, $) 2016 GDP ($B) and GDP Growth Rates (%), Selected Countries >$1T of GDP Y/Y Growth 1.6% 6.7% 1.0% 1.8% 1.8% 1.2% 6.8% 0.9% -3.6% 2.8% -0.2% 3.2% KP INTERNET TRENDS 2017 | PAGE 234 India Internet Users = +28% (2016-June) vs. 40% Y/Y Growth @ 27% Penetration355MM Users#2 Behind China India Internet Users (MM) & Penetration (%), Monthly Active*, Mid-Year (June) 2009 2016E 54 66 84 111 149 198 277 355 4% 5% 7% 9% 12% 15% 22% 27% 0% 5% 10% 15% 20% 25% 30% 0 50 100 150 200 250 300 350 400 2009 2010 2011 2012 2013 2014 2015 2016E Online Penetration (%)Internet Users (MM)Number of Internet Users Online Penetration Source: IAMAI. UN Population Division, Worldometer, KPCB estimates based on IAMAI data. Uses mid-year figures. *Note that "Monthly Active Users" are distinct from "Ever" users, which IAMAI defines as anyone who has ever accessed the internet. Owing to increasing activity levels, the number of "Monthly Active Users" may grow faster than "Ever" users. KP INTERNET TRENDS 2017 | PAGE 235 India = #1 Global Market (ex-China) Android Phone Time Spent Google Play Downloads > USA (2016), per App Annie Source: App Annie 2016 Retrospective Note: USA @ ~59% vs India 78% Android share of total mobile Internet traffic (Statcounter, 5/17) * Data excludes China 0 25 50 75 100 125 150 2014 2015 2016 Hours (B)India Brazil USA Indonesia Mexico 0 2 3 5 6 8 2014 2015 2016 Downloads (B)India USA Brazil Indonesia Russia Total Google Play Downloads, 2014-2016 Total Time Spent* on Android Phones, 2014-2016 KP INTERNET TRENDS 2017 | PAGE 236 1 1 2 2 2 2 3 3 4 4 4 5 6 10 13 15 17 18 23 22 22 27 29 26 23 28 32 26 27 0% 50% 100% 150% 200% 250% 0 5 10 15 20 25 30 35 Q1:10Q2:10Q3:10Q4:10Q1:11Q2:11Q3:11Q4:11Q1:12Q2:12Q3:12Q4:12Q1:13Q2:13Q3:13Q4:13Q1:14Q2:14Q3:14Q4:14Q1:15Q2:15Q3:15Q4:15Q1:16Q2:16Q3:16Q4:16Q1:17% Y/Y GrowthUnit Shipments (MM)Smartphone Shipments Y/Y Growth (%) India Smartphone Shipments = +15% Y/Y (Q1:17)+5% (2016)+29% (2015) India Smartphone Unit Shipments, Q1:10 Q1:17 2015: +29% Y/Y 2016: +5% Y/Y Source: Morgan Stanley, IDC KP INTERNET TRENDS 2017 | PAGE 237 -10% -5% 0% 5% 10% 15% 20% 25% 30% 0 10 20 30 40 50 60 70 80 Q1:10Q2:10Q3:10Q4:10Q1:11Q2:11Q3:11Q4:11Q1:12Q2:12Q3:12Q4:12Q1:13Q2:13Q3:13Q4:13Q1:14Q2:14Q3:14Q4:14Q1:15Q2:15Q3:15Q4:15Q1:16Q2:16Q3:16Q4:16Q1:17% Y/Y GrowthUnit Shipments (MM)Smartphone Shipments Feature Phone Shipments Y/Y Growth (%) Smartphone + Feature Phone Shipments = +6% Y/Y (Q1:17)-3% (2016)-2% (2015) India Mobile Phones Unit Shipments, Q1:10 Q1:17 2015: -2% Y/Y 2016: -3% Y/Y Source: Morgan Stanley, IDC KP INTERNET TRENDS 2017 | PAGE 238 India Smartphone + Data Costs = Declining But Still High for Majority of India's 1.3B Citizens KP INTERNET TRENDS 2017 | PAGE 239 India Smartphone Cost (excluding Data) = Unaffordable for Many @ 8% of Annual Average GDP per Capita 0% 5% 10% 15% 20% 25% 30% 35% 40% $0 $50 $100 $150 $200 $250 $300 $350 $400 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 ASP as % of Per Capita GDPSmartphone ASP ($)Smartphone ASP ($) ASP as % of GDP per Capita India Smartphone Average Selling Price (ASP, $) & ASP as % of GDP per Capita, 2007 - 2016 Source: Morgan Stanley, IDC. GDP per Capita data based on IMF, 4/17. KP INTERNET TRENDS 2017 | PAGE 240 India Wireless Data Cost* = Declining to More Affordable Levels @ 1.3% of Annual Average GDP per Capita (3/17) vs. 3% (3/15) $53 $53 $51 $52 $51 $48 $47 $45 $44 $42 $38 $33 $23 0.0% 1.0% 2.0% 3.0% 4.0% $0 $15 $30 $45 $60 Cost of Data as % of GDP per Capita (%)Annualized Cost of 1GB / Month Plan ($)Annual Price of 1GB of Data per Month As a % of GDP/Capita 2% GDP / Capita Threshold for Widespread Affordability, per Alliance for Affordable Internet Annualized Cost of 1GB / Month vs. % of GDP per Capita, Q1:14 Q1:17 Source: JP Morgan, Bharti Airtel, Idea Cellular, IMF, Alliance for Affordable Internet. *Industry average calculated using average cost of 1 GB of data from Bharti Airtel and Idea Cellular and exclude the impact of Reliance Jio. Chart is illustrative and assumes an average consumption of 1GB / month. Alliance for Affordable Internet data suggests that 2% of monthly income for 1GB of data is within affordable range. KP INTERNET TRENDS 2017 | PAGE 241 India Internet = Fierce Global Battleground (Hardware / Carriers / Software / Commerce) KP INTERNET TRENDS 2017 | PAGE 242 India Mobile Hardware (2012-Q1:17) = Intense Competition Massive Share Shifts 0% 10% 20% 30% 40% 50% 60% Q4:14 Q4:15 Q4:16 Q1:17 Smartphone Unit Shipments Market Share (%)China-Based Vendors India-Based Vendors Global Vendors India Smartphone Shipments Market Share by Vendor Country of Origin (%), Q4:14 Q1:17 Rise of India OEMs (2012-H1:14) Likes of Micromax / Lava / Karbonn Fight for Feature Phone Market Share via PriceASPs Fall ~40%Shares Rise Rise of China OEMs + Reliance (H2:14-Q1:17) Likes of Lenovo / Xiaomi / Oppo / Vivo Fight for Smartphone Market Share via Quality / Features / Online DistributionASPs StableShares RiseReliance Gains Share in 2016 on Launch of Jio 4G Service + LYF-Branded Smartphones... Competition Intensifies (H1:17) Xiaomi / Oppo / Vivo Share Gains Continue Smartphones Get Cheaper / Better... Lava / Micromax / Jio Fight for Low-Cost 4G Feature Phone Share... Source: IDC, Morgan Stanley, Lava, Micromax, Jio. KP INTERNET TRENDS 2017 | PAGE 243 India Wireless Carriers = Incumbents + New Entrants Fighting Aggressively for Share Over Past 4 Quarters 2015 1H:16 Top 3 India wireless carriers Bharti Airtel / Vodafone / Idea collectively maintain ~60% share of broadband subscribers + ~$2.80 $3.00 monthly ARPU (Voice + Data + Value-Added Services). Q2:16 Wireless incumbents begin to cut data rates in anticipation of Reliance Jio launch in 9/16. Data costs per GB decline from $3.50 to ~$3.15 (-10%) Q/Q. Voice costs decline 4% Q/Q. 9/16 Reliance Jio after investing $25B over 7 years rolls out 4G Pan-India Jio network + $0 Monthly ARPU (post 3/17 when ARPU rose to $4.70) Q4:16 Q1:17 Wireless incumbents begin to lose data subscribers. In response, they cut data prices further over next 2 quarters. As of 3/17, average cost of 1GB of data @ ~$2 among incumbents, -48% Y/Y...ARPU -20%. Including Jio, average cost of 1GB of data @ $0.33 (3/17). 3/17 Reliance Jio free-data period ends with ~67% paid migration (72MM convert to paid Jio Prime subscribers out of 108MM sign-ups) Source: JP Morgan, Public Filings, TRAI, Reliance Jio. Jio sign-ups are total number of Jio SIMs registered, while paying subscribers are a subset of sign-ups who have later converted to Jio Prime paid subscription. Data for incumbents based on average of Idea and Bharti Airtel. KP INTERNET TRENDS 2017 | PAGE 244 India Wireless Consumer Data Prices = -48%+ in Last Year* as Incumbent Carriers Responded to Jio's Low Pricing Data Prices per GB, Industry*, CQ1:14 CQ1:17 $4.4 $4.4 $4.3 $4.3 $4.2 $4.0 $3.9 $3.7 $3.7 $3.5 $3.1 $2.7 $1.9 $0.17 $0.0 $0.5 $1.0 $1.5 $2.0 $2.5 $3.0 $3.5 $4.0 $4.5 $5.0 3/14 6/14 9/14 12/14 3/15 6/15 9/15 12/15 3/16 6/16 9/16 12/16 3/17 Cost of 1GB Data ($)Price of 1GB of Data (Industry Incumbents) Price of 1GB of Data (Jio) Industry Incumbents -48% Y/Y Reliance Jio 3/17 Source: JP Morgan, Bharti Airtel, Idea Cellular, Reliance Jio. *Industry incumbent average calculated using weighted average cost of 1 GB of data realization from Bharti Airtel / Idea Cellular. Reliance Jio data assumed at 10 INR / GB based on March realization. KP INTERNET TRENDS 2017 | PAGE 245 India Broadband Subscribers* = +85% Y/Y (Q1:17)Accelerating Reliance Jio Rose to 39% Share vs. 0% (Q3:16) Owing to Low Price Launch 72 108 22 25 28 31 38 41 46 44 49 19 22 24 26 28 32 36 35 38 19 18 20 21 23 27 31 27 25 15 17 19 20 20 21 22 20 22 24 27 30 38 40 42 58 38 35 99 109 121 137 150 162 192 0 50 100 150 200 250 300 Q1:15 Q2:15 Q3:15 Q4:15 Q1:16 Q2:16 Q3:16 Q4:16 Q1:17 Broadband Subscribers (MM)Jio Bharti Airtel Vodafone Idea BSNL Other 236 India Broadband (>512 Kbps) Subscribers* by Service Provider, CQ1:15 CQ1:17 9/16 = Jio Release to General Public 277 Source: TRAI reports. *Subscribers are defined as all unique SIMs within a carrier's database, less test/service cards, employees, stock in hand, SIMs where the subscriber retention period has expired, and service suspended pending disconnection. Note that as of 3/17, Jio's subscribers mentioned here were on free data plans. Subsequent to this free trial period, 72MM so far have converted to paying subscribers. KP INTERNET TRENDS 2017 | PAGE 246 India Software Mobile Browser Usage Market Share = China (UC/Alibaba) @ 50%...USA (Google Chrome) @ 32%... 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% UC Browser Opera Chrome Android Nokia Others India Mobile Browser Usage Market Share, Q1:13 Q2:17 Source: Statcounter 2017 Note: Data reflects usage share across calendar year quarters. As Q2 is in progress, data for Q2 2017 reflects current share as of 5/30/17 KP INTERNET TRENDS 2017 | PAGE 247 India Software Top Downloaded Android Apps = USA @ 4 of 10China @ 2 of 10India @ 2 of 10 Google Play Store Rank (5/29/17) App Origin Category Rank on 5/30/16 (1 Year Ago) 1 WhatsApp (Facebook) USA Messaging 1 2 Facebook Messenger USA Messaging 3 3 ShareIt China Utility file transfer 5 4 Truecaller Sweden Utility dialer 11 5 Facebook USA Social 2 6 UC Browser (Alibaba) China Browser 4 7 MX Player Korea Utility video player 13 8 Hotstar India Entertainment 6 9 JioTV India Entertainment 301 10 Facebook Lite USA Social 9 Source: *Top 10 Non Gaming Apps, Google Play Store, India, 5/29/17 Note: Google Play Store ranks reflect rankings based on daily download volumes Blue indicates a Facebook app. Green indicates an app owned by Alibaba. KP INTERNET TRENDS 2017 | PAGE 248 India eCommerce = Many Players Fighting for Share... Source: Company logos KP INTERNET TRENDS 2017 | PAGE 249 Amazon India = Inventory (SKUs) & Sellers +3x Y/Y... Fulfillment Centers +30% Y/Y...Aggressive / Investing Heavily 0 30 60 90 120 150 0 20 40 60 80 100 09/15 12/15 09/16 Sellers (K)SKU (MM)SKU (MM) Sellers (000s) Amazon India SKUs & Sellers, 9/15 12/16 0 5 10 15 20 25 30 2012 2013 2014 2015 2016 Fulfillment CentersAmazon India Fulfillment Centers, 2012 2016 Source: Barclays Research, Amazon.com, MWPVL International Per public statements, Amazon has pledged to invest $5B into India KP INTERNET TRENDS 2017 | PAGE 250 India Internet Usage = Rising Owing to Cheaper / Faster Access KP INTERNET TRENDS 2017 | PAGE 251 India Wireless Internet Data Usage = Rising Dramatically as Access Costs Have Fallen 0 200 400 600 800 1,000 1,200 1,400 3/14 6/14 9/14 12/14 3/15 6/15 9/15 12/15 3/16 6/16 9/16 12/16 3/17 Millions of GB per MonthTotal Monthly Wireless Data Consumed (MM GB)*, 3/14 - 3/17 Total Monthly Wireless Data Consumed (MM GB) +9x Y/Y Source: Reliance Jio, Bharti Airtel, Idea, Reliance Communications, Vodafone India. *Note total data consumed based on publicly available data from Reliance Jio, Bharti Airtel, Idea, Reliance Communications, Vodafone and may not be collectively exhaustive. KP INTERNET TRENDS 2017 | PAGE 252 India Wireless Internet Data Usage = Bandwidth Intensive App Usage Growing Dramatically 0 200 400 600 800 1,000 6/16 9/16 12/16 3/17 Streams per Month (MM)Gaana Streams +3x Growth 0% 1% 2% 3% 4% 5% 6% 6/16 9/16 12/16 4/17 Daily Active Users as % of Total UsersHotstar DAUs 4x+ Growth Source: Gaana, SimilarWeb estimates for HotStar, 5/17 Note: DAU estimates are intended to reflect relative growth within reasonable confidence intervals using SimilarWeb's methodology. Hotstar DAUs, 6/16 4/17* (Video Streaming App) Gaana Streams, 6/16 3/17 (Music Streaming App) KP INTERNET TRENDS 2017 | PAGE 253 India Leadership = Focused Pro-Digital Policies KP INTERNET TRENDS 2017 | PAGE 254 India Leadership = Digital-Focused Government Policies Rolled Out with Speed + Scope 'Banking for All' 'Jan Dhan Yojana' = 8/14 ~280MM+ new bank accounts opened to deliver financial services directly to underbanked in effort to bypass corruption Startup India = 1/16 High level support of Indian startups via funding & fast tracking of regulatory support for new companies Digital India = 7/15 National rollout of high speed broadband access & digital delivery of land records, income tax filings & other government services 'Power for All' Rural Electrification = 7/15 Program to electrify 100% of villages by 2019, with 133MM rural households electrified to date~45MM remaining Demonetization = 11/16 ~85% of paper currency in circulation replaced overnight to clean 'black' money (estimated at 22%+ of total GDP) & boost digital payment adoption Infrastructure Enhancements = 2/17 $59B targeted to upgrade railways / airports / roads Narendra Modi Elected India Prime Minister = 5/14 Key Policies Nationwide Tax (GST) Reform = 3/17 Single indirect tax replacing 17 different state & central taxes, turning India into single national market & eliminating double taxation for consumers Skills & Entrepreneurship = 6/15 Dedicated ministry to upgrade youth skillsgoal to train 10MM new workforce entrants per year Other Notable Policies Source: Ministry of Finance, India (5/17). Rural Electrification Corporation (5/17). Reserve Bank of India (7/16). World Bank black money estimates (7/10). Ministry of Commerce, India (1/16), Ministry of Skill Development & Entrepreneurship (6/15), New York Times (11/16), Bloomberg (2/17). India Union Budget (2017-2018) KP INTERNET TRENDS 2017 | PAGE 255 India Internet Usage Growth Strong Owing In Part to Broader Availability of Low Cost Data Access... India Internet User Base @ +355MM is Large... Ongoing Smartphone + Access Price Declines Key to Onboarding Next 200MM Users Driving Free Cash Flow for Many Internet Businesses Challenging Owing to Fierce Competition Consumers Benefitting from Competition & Government Policies KP INTERNET TRENDS 2017 | PAGE 256 India Internet Innovation = Leapfrogging + Re-Imagining Leapfrogging Mobile Identity Bandwidth Payments Re-Imagining Entertainment Education Healthcare Marketplaces KP INTERNET TRENDS 2017 | PAGE 257 India Mobile Usage = A Global Leader vs. Desktop Usage ~80% of Internet Usage on Mobiles 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% NigeriaIndiaSouth AfricaIndonesiaThailandTurkeyUAEPolandChinaSaudi ArabiaMalaysiaMexicoGlobal AverageArgentinaSingaporeSpainPhilippinesUSAAustraliaS. KoreaUKVietnamItalyEgyptBrazilGermanyCanadaJapanFranceRussiaMobile as % of Web TrafficMobile Share of Web Traffic, 1/17 Source: Hootsuite, Statcounter, 1/17. KP INTERNET TRENDS 2017 | PAGE 258 India Identity = Aadhaar + eKYC Digital Authentication for 1B+ People Use Growing Rapidly @ 16MM Authentications per Day (3/17) vs 3MM Y/Y Aadhaar Authentication = eKYC Authentication Are You Who You Claim To Be? Proof of Address / Birth / Photos If Yes Binary Yes / No Answer Only Uses Biometrics (Fingerprint + Iris) + Unique 12-Digit Number to Verify Secure Dropbox for Basic Paper Records Can Only be Accessed if Aadhaar ID is Authenticated + User Gives Consent Aadhaar Authentications / Day, 9/12 - 3/17 0 1 2 3 4 5/16 6/16 7/16 8/16 9/16 10/16 eKYC / Day (MM)eKYC Verifications / Day, 5/16 10/16 - 2 4 6 8 10 12 14 16 18 AadharAuthentications / Day (MM)Source: UIDAI (Indian Government), iSpirit / IndiaStack, Note: Aadhaar authentication per day estimates provided by Prime Venture Partners, based on monthly authentication figures released by UIDAI KP INTERNET TRENDS 2017 | PAGE 259 ...India Identity = India Aadhaar Digital IDs Have Broad Coverage @ 82% of Population (1.1B People) vs. Zero 6 Years Ago#1 in World 0% 4% 8% 23% 46% 72% 82% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 0 200 400 600 800 1,000 1,200 2010 2011 2012 2013 2014 2015 2016 % of Total PopulationTotal AadhaarIDs (MM)Aadhaar IDs (MM) % of Total Population Total Aadhaar IDs (MM), 2010 2016 Source: UIDAI (Indian Government), iSpirit / IndiaStack, Prime Venture Partners, United Nations KP INTERNET TRENDS 2017 | PAGE 260 Sim Card Activation Before Digital ID = 1-3 Days Proof of Address / original photo IDs / attested photocopies + potential fraud After-Digital ID = 15 Minutes Aadhaar number + fingerprint / biometric eSign ...India Identity = Aadhaar IDs + eKYC Improving Foundational Access to Broad Services Bank Account & Digital Wallet Opening Before Digital ID = Physical visit to bank, paper-based KYC, lack of ability to scale, improper documentation After-Digital ID = Open account on mobile phone in secure / scalable way Pensions & Social Services Before Digital ID = Cash-based / leakage of payments to government officials / corruption / fraud After-Digital ID = 12-15% increase in final payouts to workers owing to reduced leakage Source: UIDAI (Indian Government), iSpirit / IndiaStack, Skoch Group Note: Image credits Hindu Business Line, NDTV, Reliance Jio, DBS India, Livemint (2017) KP INTERNET TRENDS 2017 | PAGE 261 India Bandwidth = Reliance Jio High-Speed Bandwidth Ramp @ 108MM Sign-Ups* in 7 Months...72MM Converted to Paying Subscribers Reliance Jio Sign-Ups and Subscribers (MM), 9/16 4/17 16 24 52 72 86 100 108 72 0 20 40 60 80 100 120 9/16 10/16 11/16 12/16 1/17 2/17 3/17 Reliance JioSign-Ups / Subscribers (MM)Reliance Jio Sign-Ups Jio Prime Subscribers Source: Cellular Operators Association of India (COAI), Reliance Jio, various press releases *Sign ups represent all those who have signed up for a Jio SIM card. Subscribers are those who remained with Jio after their free trial period ended on 3/31/2017 and became Jio Prime subscribers. KP INTERNET TRENDS 2017 | PAGE 262 India Payments = Evolution of Building Blocks for Digital Payment / Data Infrastructure for 1B+ Indians (2009 2017)... Phase Project Functionality Results 1) Identity Aadhaar (1/09) + eKYC (5/13) Single digital ID + authentication database 1B+ Aadhaar cards issued since 2010 ~16MM authentications/day (4/17) 2) Banking Jan Dhan Yojana (8/14) 'Banking for All' Bank accounts tied to Aadhaar for previously non- banked citizens 280MM+ accounts opened in 3 years... 50% of existing bank accounts Direct subsidies to citizen bank accounts have saved $775M owing largely to reduced corruption leakage (12/16) 3) Mobile Services Universal Payments Interface (UPI) (7/16) Instant money transfer between bank accounts via phone numbers ~$380MM monthly transaction volume (4/16) Use accelerated after demonetization (11/16) Bharat Interface for Money (BHIM) (12/16) Government App for UPI based payments 17MM+ downloads within 2 months of launch (2/17) Source: Kalaari Capital, Prime Venture Partners, Indiastack.org, Department of Financial Services, Government of India (2016) KP INTERNET TRENDS 2017 | PAGE 263 Paytm Registered Users (MM), 11/14 - 3/17 India Payments = Online Leader Paytm Ramping Users Rapidly Bolstered by Uptake of Online + Offline Commerce 22 50 100 122 180 215 0 50 100 150 200 250 11/14 4/15 8/15 4/16 12/16 3/17 Registered Users (MM)Paytm Source: Paytm. KP INTERNET TRENDS 2017 | PAGE 264 India Payments = UPI (Universal Payments Interface) Rapidly Enabling Bank-to-Bank Mobile Money Transfers $0 $5 $7 $15 $106 $249 $285 $359 0% 5% 10% 15% 20% 25% 30% 35% $0 $50 $100 $150 $200 $250 $300 $350 $400 8/16 9/16 10/16 11/16 12/16 1/17 2/17 3/17 UPI as % of Mobile Wallet VolumeUPI Monthly Transaction Volume ($MM)Monthly Digital Payments Volume in India via UPI ($MM), 8/16 3/17 UPI Transaction Value UPI Value as % of Total Mobile Wallets Source: Reserve Bank of India, Monthly Bulletin (Payments and Settlement Systems) Demonetization (11/16) KP INTERNET TRENDS 2017 | PAGE 265 India Internet Innovation = Leapfrogging + Re-Imagining Leapfrogging Mobile Identity Bandwidth Payments Re-Imagining Entertainment Education Healthcare Marketplaces KP INTERNET TRENDS 2017 | PAGE 266 Search, Social and Messaging, 34% Entertainment, 45% Shopping, 4% Finance, 2% News & Media , 2% Others, 13% India Entertainment = Weekly Mobile Time Spent @ 7x TV 45% Mobile Time = Entertainment Source: MMA Kantar India Mobile Usage Report, 2016 2 4 28 0 5 10 15 20 25 30 35 40 Time Spent with Media per Week (Hours), 2016 Print Television Mobile Percent of Time Spent on Mobile by Category, 2016 KP INTERNET TRENDS 2017 | PAGE 267 TV Soap Operas + Reality Shows On-Demand Web-Video Shows ex. AIB Roasts, Hotstar Scripted, family-focused dramas targeted @ older viewers + families with 'rinse & repeat' plots Produced for linear programming without user data / feedback Little to no user data, often based on small TV rating sample sizes / surveys India Entertainment Re-Imagined = Internet-First Shows Optimized for Mobile Replacing Longer / Linear Programming Optimized for TV THEN NOW Millennial focused / short-form content such as 'Hinglish' standup comedy Made for mobile / shared via messaging channels (Whatsapp, FB, etc) Instant user data + feedback (Views, Geos, Replays etc.) Dramatic growth assisted by 4G rollout of JioAIB Channel @ 100MM+ views Source: Google Play, Reliance Jio Annual Report Image: Wikipedia, Hotstar, JioTV KP INTERNET TRENDS 2017 | PAGE 268 India Education = Largest K-12 School System (250MM+ Students) in World With High Demand for After-School Education 0 50 100 150 200 250 300 India China US UK Students (MM)Total K-12 Student Enrollments by Country (MM), 2015 22% 26% 37% 0% 10% 20% 30% 40% 50% Primary Upper Primary Secondary % of Students% of Students Enrolled in Private Coaching 89% 8% 2% 2% 0% 20% 40% 60% 80% 100% Augmenting Basic Education Prep for Job Exams Entrance Exam Prep Others Reasons for Private Coaching % of Respondents Indian Private Coaching Industry, 2014 Source: Nielsel K-12 India Book Publishing Report,2016. UNESCO Education & Literacy China Statistics, 2015. U.S Department of Education, 2016. UK Department for Education National Statistics, 1/15. KP INTERNET TRENDS 2017 | PAGE 269 India Education Re-Imagined = Increasingly Accessible (via Mobiles) + Self-Paced + Personalized THEN Offline Private 'Tuition' Centers Mobile Self-Paced Learning ex. Byju's Offline lectures + in-person testing Directly based on income & geography 1:35+ student-teacher ratio One-size-fits-all approach Extreme focus on test taking Math + science with games + videos Anyone / anywhere with smartphone 40+ minutes average daily usage Personalized Learning outcomes* improved 15%+ NOW Source: Byju's, *data refers to improvements among students who took a test, watched the video and then took another tes Image: DailyMail KP INTERNET TRENDS 2017 | PAGE 270 India Healthcare = High (& Rising) Out-of-Pocket Spend <20% Insurance Penetration 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % of Private Expenditure on HealthIndia Out-of-Pocket Spend (% of Private Expenditure on Health), 2014 86% 82% 0% 20% 40% 60% 80% 100% Rural Urban % of PopulationPercent of Indian Population Not Covered by Insurance, 2014 $0 $20 $40 $60 $80 Expenditure per Capita ($)Health Expenditure per Capita in India ($), 2004 - 2014 Source: World Bank 2014 Census. KP INTERNET TRENDS 2017 | PAGE 271 Offline Labs & Pharmacies Online Health Hubs ex. 1Mg, Portea Long wait times for standard lab tests Limited drug inventory Geography dependent Up to 60-80% price variance for identical drugs owing to lack of price transparency In-home tests ordered online Access to aggregated inventories of multiple pharmacies in metro 40-50% lower prices for lab tests Instant drug price comparisons offer transparency, saving users 20 - 30% per prescription India Healthcare Re-Imagined = Increasingly Accessible (via DIY / Mobile) + Affordable (via Online Aggregation + Pricing Transparency) THEN NOW Source: 1Mg, Portea, CDSCO Report 2016 KP INTERNET TRENDS 2017 | PAGE 272 India Marketplaces = Organizing the Un-Organizable Replacing Middlemen with Smartphones + Direct to Consumer Marketplaces Hyperlocal Offline Markets ex. Fish Mandis Mobile / Direct-to-Consumer Ex. Freshtohome.com Multiple middlemen High price variance No consumer visibility into quality High quality produce sourced directly from fishermen Online distribution allows 20-25% lower prices for consumers THEN NOW Source: FreshtoHome Image: TheIndianIris KP INTERNET TRENDS 2017 | PAGE 273 India Internet Challenges = Fundraising Environment + Language KP INTERNET TRENDS 2017 | PAGE 274 India = Especially High Venture Capital Funding in H2:14 2015 Helped Drive Aggressive Start Up Valuations + Spending + Competition $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 $3,500 $4,000 Amount Invested ($MM)2013: $1.4B 2014: $5.1B 2015: $7.6B 2016: $4.7B Source: Tracxn, Inc42 Indian VC Funding by Quarter, Q1:13 Q1:17 KP INTERNET TRENDS 2017 | PAGE 275 India = 29 Languages Spoken by >1MM People6 >50MM (ex-English) 46% of Internet Users Primarily Consume Local Language Content 45 63 86 127 66 86 112 150 41% 42% 44% 46% 37% 38% 39% 40% 41% 42% 43% 44% 45% 46% 47% 0 50 100 150 200 250 300 2012 2013 2014 2015 % of Total Internet UsersInternet Users & Language of Content Consumption (MM)Consumers of Non-Local Language Content Consumers of Local Language Content % of Internet Users Consuming Local Language Content Indian Internet Users & Primary Language for Content Consumption, 2012 2015 Source: IDC New Media Market Model 3/17, Nation Master 2009, Indian Census 2001, CRDDP Survey, (Shariff, 2014), IAMAI 2/16, IAMAI Reports 2012-2016. KP INTERNET TRENDS 2017 | PAGE 276 India Macro Demographics = Bad & Good Other Challenges = 1) Job Creation 2) Business Basics 3) Education 4) Logistics 5) Gender Disparity KP INTERNET TRENDS 2017 | PAGE 277 India = Low Relative GDP per CapitaPoverty Levels While ImprovingRemain High GDP per Capita ($) Among Countries >50MM in Population, Current Prices, 2016 $0 $10,000 $20,000 $30,000 $40,000 $50,000 $60,000 $70,000 CongoEthiopiaMyanmarBangladeshPakistanIndiaVietnamNigeriaPhilippinesIndonesiaEgyptIranSouth AfricaThailandChinaMexicoBrazilRussiaTurkeyKoreaItalyFranceJapanUKGermanyUSAGDP per Capita ($)Source: IMF, 4/17. GDP per Capita data based on current prices. Selected for countries with population >50MM. KP INTERNET TRENDS 2017 | PAGE 278 India = Lots of Young People 64% of Population...72% of Internet Users <35 Years Old... 0% 8% 16% 24% 32% 40% 0 50 100 150 200 250 300 350 400 450 500 0-14 15-34 35-49 50-64 65+ % of Total PopulationPopulation (MM)Age Group Population by Age Group (MM) % of Population India Population by Age Group, 2015 Distribution of India Internet Users by Age Group, 2017 0% 5% 10% 15% 20% 25% 30% 35% 40% 6-14 15-24 25-34 35-44 45+ Distribution of Internet Users by Age Group (%)Age Group Internet Users by Age Group Source: UN Population Division., ComScore, 3/17. ComScore data based on panel and census and only includes Android. KP INTERNET TRENDS 2017 | PAGE 279 50% 55% 60% 65% 70% 75% 19551960196519701975198019851990199520002005201020152020E2025E2030E2035E2040E2045E2050EPercent of Population Between Ages 15 -64India China More Developed Regions India = Working Age Population Growth + Millennial Per Capita Income Compare Favorably with Other Countries Percent (%) of Population 15 64 Years Old, India vs. China vs. More Developed Regions, 1950 2050E 0 20 40 60 80 100 120 15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465+Index to Highest Income Age Group in Country (100)India USA China Per Capita Income Distribution, India / USA / China by Age, 2015 (Index to the Highest Income Age Category for Corresponding Country) Peak Working Age Population Source: UN Population Division, Euromonitor, Morgan Stanley. Projections data based on medium variant estimates. "More Developed Regions" comprised of N. America, Europe, Japan, Australia, New Zealand. Projections begin after 2015. UN provides projections on a 5-year time frame. KP INTERNET TRENDS 2017 | PAGE 280 India = 'Consumption Class' Growing Rapidly @ 27% of Households (66MM) vs. 7% Ten Years Ago India Households by Income Bracket, 2005 vs. 2015 (in constant 2015 dollars) 0 50 100 150 200 250 300 2005 2015 Households (MM)<$3K $3K-$7K $7K-$17K $17K-$34K >$34K 14M 66M Consumption Class = income levels at which consumers start to spend beyond basic necessities Source: Kalaari Capital, 3/17, NCAER, McKinsey. KP INTERNET TRENDS 2017 | PAGE 281 India Consumption = Mostly Focused on Basics"Roti, Kapda Aur Makaan" @ 54% of Personal Consumption Expenditure Personal Consumption Expenditure by Category, 2016 Basics Clothes and footwear (ex- sportswear) Clothes and footwear (ex- sportswear) Clothes and footwear (ex- sportswear) Clothes and footwear (ex-sportswear) Clothes and footwear (ex-sportswear) Cosmetics and personal care Cosmetics and personal care Cosmetics and personal care Cosmetics and personal care Cosmetics and personal care Jewelry Jewelry Packaged food Packaged food Packaged food Packaged food Packaged food Fresh food Fresh food Fresh food Fresh food Fresh food Non-alcoholic beverages Non-alcoholic beverages Non-alcoholic beverages Non-alcoholic beverages Non-alcoholic beverages Alcoholic beverages Alcoholic beverages Alcoholic beverages Alcoholic beverages Alcoholic beverages Tobacco Tobacco Tobacco Tobacco Tobacco Housing Housing Housing Housing Housing Financial services Financial services Financial services Financial services Financial services Utilities Utilities Utilities Utilities Utilities Household appliances Household appliances Household appliances Household appliances Other household goods Other household goods Other household goods Other household goods Other household goods Ground transportation/services and automobiles Ground transportation/services and automobiles Ground transportation/services and automobiles Ground transportation/services and automobiles Ground transportation/services and automobiles Handset and telecom services Handset and telecom services Handset and telecom services Handset and telecom services Handset and telecom services Food services Food services Food services Food services Food services Out of town trips Out of town trips Out of town trips Out of town trips Healthcare Healthcare Healthcare Healthcare Healthcare Education Education Education Education Education Insurance and social protection Insurance and social protection Insurance and social protection Insurance and social protection Insurance and social protection Others Others Others Others Others 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% India US$1,034 China US$3,136 Korea US$12,687 Japan US$20,785 USA US$38,293 Source: Euromonitor, Goldman Sachs Investment Research. KP INTERNET TRENDS 2017 | PAGE 282 India Job Creation = Employment Levels @ 55% of Working Age Population... Employment Trending Slower than Population Growth India Working Age (15-64 Years Old) Population vs. Employment, 1995 2050E 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1995 2000 2005 2010 2015 2020E 2025E 2030E 2035E 2040E 2045E 2050E Population Between Ages 15 64and Employment Level (MM)India Working Age Population Employment +280MM Working-Age Population Source: UN Population Division, Planning Commission of India, National Sample Survey, International Labor Organization. Population projections based on medium variant estimates. Projections begin after 2015. Working age population defined as ages 15-64. KP INTERNET TRENDS 2017 | PAGE 283 India Business Basics = Ease-of-Doing Business Lags Behind Many Countries Topics India China USA OECD Overall Ease of Doing Business (Rank out of 190) 130 78 8 -- Ease of Starting a Business (Rank out of 190) 155 127 51 -- # Procedures to Register Business (Number) 14 9 6 5 Time to Register Business (Days) 26 28 4 8 Cost to Register Business (% of Income Per Capita) 16.5% 0.6% 1.3% 3.1% Source: The World Bank, 2017 (http://www.doingbusiness.org/rankings). Rankings apply to 190 countries. Number of procedures, time to register, and cost as % of income per capita reported here based on statistics that apply to men. KP INTERNET TRENDS 2017 | PAGE 284 India Education = Average Years of Schooling Lags Peers Average Years of Schooling Among Selected Medium Human Development Countries, 2015 0 2 4 6 8 10 12 14 BhutanNepalCambodiaMyanmarCabo VerdeMoroccoPakistanBangladeshLaoHondurasKenyaCongoIndiaGuatemalaNicaraguaEl SalvadorIraqNamibiaVanuatuZambiaGhanaEgyptIndonesiaViet NamParaguayGabonBoliviaGuyanaBotswanaPhilippinesTurkmenistanSouth AfricaTajikistanKyrgyzstanChinaUSAAverage Years of SchoolingAverage Years of Schooling Among Medium Human Development Countries Source: Human Development Report, 2016 Mean years of schooling defined as average number of years of education received by people ages 25 and older, converted from education attainment levels using official durations of each level. KP INTERNET TRENDS 2017 | PAGE 285 India Logistics = Low Infrastructure Competitiveness Source: The World Bank Global Competitiveness Index, 2016-2017. Population data per CIA World Factbook. Numbeo Traffic Estimates. *The World Bank Global Competitiveness Report (GCR) is a yearly report published by the World Economic Forum. Since 2004, the Global Competitiveness Report ranks countries based on the Global Competitiveness Index, developed by Xavier Sala-i-Martin and Elsa V. Artadi. Infrastructure Rankings Across Asia, 2016 Rank City Country Traffic Index 2015 Population (MM) 1 Kolkata India 337 12MM 2 Dhaka Bangladesh 317 18MM 3 Mumbai India 308 21MM 4 Sharjah UAE 298 1MM 5 Nairobi Kenya 295 4MM 6 Manila Philippines 283 13MM 7 Jakarta Indonesia 280 10MM 8 Tehran Iran 272 8MM 9 Mexico City Mexico 272 21MM 10 Istanbul Turkey 263 14MM Top 10 Most Congested Cities Globally, 2016* 4.03 0 2 4 6 8 Nepal Pakistan Bangladesh Myanmar Mongolia Cambodia Philippines Vietnam India Indonesia China New Zealand Malaysia Australia Taiwan Korea, Rep. Japan Singapore Hong Kong Average Most Least World Bank Infrastructure Competitiveness Score KP INTERNET TRENDS 2017 | PAGE 286 India Gender Disparity = Female Labor Participation Rate @ 27%...Below World Average 0% 10% 20% 30% 40% 50% 60% 70% 2008 2009 2010 2011 2012 2013 2014 2015 2016 Labor Participation Rate (%)Female Labor Force Participation Rate, 2008 - 2016 India USA China Brazil Russia World Average Source: International Labor Organization, 2016 Note: ILO defines female labor force participation rate as the proportion of the female population of age 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. KP INTERNET TRENDS 2017 | PAGE 287 1) Economy = Strong Growth 2) Internet Users = Solid Growth 3) Mobiles = Choppy GrowthRecent Acceleration 4) Internet = Fierce Global Battleground (Hardware / Carriers / Software / Commerce) 5) Internet Usage = Rising Owing to Cheaper / Faster Access 6) Leadership = Focused Pro-Digital Policies 7) Internet Innovation = Leapfrogging = MobileIdentityBandwidthPayments Re-Imagining = EntertainmentEducationHealthcareMarketplaces 8) Internet Challenges = Financing EnvironmentLanguage Diversity 9) India Macro = Demographics = Bad & GoodChallenges = Job CreationBusiness BasicsEducationLogisticsGender Disparity India Internet = Competition Continues to IntensifyConsumers Winning KP INTERNET TRENDS 2017 | PAGE 288 HEALTHCARE @ DIGITAL INFLECTION POINT NOAH KNAUF @ KLEINER PERKINS KP INTERNET TRENDS 2017 | PAGE 289 Healthcare @ Digital Inflection Point Source: History of Nephrology, Welch Allyn, Medisave, Kinsa 100 Years Ago Human Touch 25 Years Ago Machine Assisted / Analog Today Technology Enabled / Digital KP INTERNET TRENDS 2017 | PAGE 290 1) Digital Inputs = Rapid Growth in Sources of Digital Health Data 2) Data Accumulation = Proliferation of Digitally-Native Data Sets 3) Data Insight = Generated Following Accumulation & Integration of Data 4) Translation = Impact on Therapeutics & Healthcare Delivery Digitization of Healthcare = Virtuous Cycle of Innovation 5) Outcomes = Measure Outcomes & Iterate Innovation Cycle Times Compressing KP INTERNET TRENDS 2017 | PAGE 291 Digital Inputs = Rapid Growth in Sources of Digital Health Data KP INTERNET TRENDS 2017 | PAGE 292 Measurement = Most Widely Used Medical Technology Now Digital / Connected 2D / Analog 3D / Digital Paper-Based / Analog Wearable / Digital Automatic / Digital X-Ray ECG Blood Pressure Manual / Analog 2000's 2017 2000's 2017 Hospital Monitoring In-Room / Analog Source: Medisave, GE Healthcare, iRhythm Technologies, Welch Allyn Remote / Digital KP INTERNET TRENDS 2017 | PAGE 293 Diagnostic Technology = Measured / Monitored Data Attributes Rising Rapidly 13 59 0 10 20 30 40 50 60 70 1993199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017**Lab Tests with Waived Status Under CLIA* (K)Commercially Available Lab Tests, 1993-2017 Source: CLIA/FDA Database of Waived Tests and Database of Analytes (5/17) * Lab Tests are considered to be CLIA waived if the test is simple and accurate enough that it is impossible to product incorrect results conducting them and does not do any harm to the human body. Tests become CLIA waived automatically if the FDA approves it for at-home use ** 2017 as of 5/17. Amylase . . . . . . . . . . 988 Distinct Analytes . . . . . . . . Zinc KP INTERNET TRENDS 2017 | PAGE 294 Wearables = Consumer Health + Wellness Data Capture Rising Rapidly Source: Rock Health 2016 Consumer Survey (12/16), IDC, Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios (9/16) * Based on analysis of 140 different wrist wearable devices Sensors in Wrist Wearables, 9/16 26 82 102 0 20 40 60 80 100 120 2014 2015 2016 Global Wearable Shipment Volumes (MM)13% 5% 6% 6% 7% 12% 18% 19% 26% 28% 33% 86% Others Thermometer Camera Altimeter Barometer Ambient Light Microphone Compass Gyroscope GPS Heart Rate Accelerometer % of Wrist Wearables* Global Wearable Shipments Wearables = Gaining Adoption ~25% of Americans own a Wearable, +12% Y/Y, 2016 KP INTERNET TRENDS 2017 | PAGE 295 60% 56% 54% 50% 39% 39% 37% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Google Microsoft Samsung Apple Amazon Facebook IBM % of Consumers Willing to Share Health DataConsumers = Willing to Share Health Data Leading Tech Brands Positioned Well for Digital Health, 2016 With which tech company would you share your data? Source: Rock Health 2016 Consumer Survey Note: Based on consumer survey with 4,015 participants; as % of respondents willing to share their health data with tech company at all. KP INTERNET TRENDS 2017 | PAGE 296 Data Accumulation = Proliferation of Digitally-Native Health-Related Data Sets KP INTERNET TRENDS 2017 | PAGE 297 Proliferation of Health Apps = Rapid Rise of Empowering Data in Consumer Hands Health & Fitness App Downloads*, Per App Annie +5% Y/Y in US, +15% Y/Y in ROW 0 200 400 600 800 1,000 1,200 1,400 2015 2016 Downloads (MM)USA Rest of World 36% 17% 12% 24% 11% Fitness Lifestyle & Stress Diet & Nutrition Disease & Treatment Other Health Apps by Category, Global, 2015 Source: App Annie, IMS Health (6/15) Note: Due to focus on iOS App Store and Google Play, Rest of World in the App Annie chart does not capture China's downloads on other app stores. The IMS chart includes iOS App Store and Google Play as of 6/15. * App downloads captures iOS App Store and Google Play KP INTERNET TRENDS 2017 | PAGE 298 Electronic Health Record (EHR) Adoption = Broad + Centralized Accumulation of Data Source: Office of the National Coordinator for Health Information Technology (12/16), Galen Healthcare (8/16) *Estimated per year clinical data element collection based on data elements collected over 6 years for 165,399 patients, average 49yrs old EHR Adoption Among Office-Based Physicians, USA 2004-2015 21% 87% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% EHR Adoption (%)Average Amount of Clinical Data Elements per Patient per Year*, 8/16 5.5 2.9 3.2 4.1 10.5 26.3 0 5 10 15 20 25 30 Unique Data Elements Per PatientClinical Results Scanned Images Vital Signs Problems (historical, current) Other (e.g. medications, allergens, etc.) KP INTERNET TRENDS 2017 | PAGE 299 Hospitals Providing Digital Access to Healthcare Information = +7x Since 2013 Source: ONC/AHA Annual Survey Information Technology Supplement: 2012-2015 (9/16) Note: Percentage of non-federal acute care hospitals that provide patients with the capability to electronically view, download, and transmit their health information 24% 14% 40% 28% 91% 82% 95% 87% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% View Download % of Non-Federal Acute Hospitals2012 2013 2014 2015 Hospitals that Enable Patient Digital Data Access, 2012 - 2015 KP INTERNET TRENDS 2017 | PAGE 300 Increasing Digitization of Inputs = Healthcare Data Growing at 48% Y/Y 153 Exabytes 0 20 40 60 80 100 120 140 160 180 200 Worldwide Healthcare Data (2013) Exabytesof Healthcare DataGrowth in Healthcare Data Source: IDC & EMC (12/13) Note: 1 Exabyte = 1B Gigabytes, 1 Petabyte = 1M Gigabytes Data Drivers Typical 500 Bed Hospital 500 Beds 8,000 Employees 400 Applications 500 Databases 1,000 Interfaces 10,000 Desktops 500 Owned/Controlled Tablets 2,000 Owned/Controlled Mobile Devices 50 Petabytes of Data per Hospital KP INTERNET TRENDS 2017 | PAGE 301 Data Insight + Translation = Early Innings of Impact on Therapeutics KP INTERNET TRENDS 2017 | PAGE 302 Rise in Inputs + Data = Medical Research / Knowledge Doubling Every 3.5 Years Cumulative PubMed Scientific Article Citations* 0.06 27 0 5 10 15 20 25 30 1907 1917 1927 1937 1947 1957 1967 1977 1987 1997 2007 2017 Annually Published Medical Citations (MM)Source: National Institutes of Health, U.S. National Library of Medicine (4/17), "Challenges and Opportunities Facing Medical Education" (Densen, Peter) Transactions of the American Clinical and Climatological Association (1/10) *Based on cumulative number of published medical citations on PubMed, **Based on peer-reviewed article on challenges in medical education Years to Double Medical Knowledge** 1950 50 years 1980 7 years 2010 3.5 years KP INTERNET TRENDS 2017 | PAGE 303 Clinical Trials = Follow Expansion of Research Insight But Clinical Impact Lags Owing to Length of Trials... 0 50 100 150 200 250 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Total Number of Registered Clinical Trials (K)Growth in Clinical Trials Average Clinical Trial Duration Phase 0 ~3.5 Years Phase 1 1.8 Years Phase 2 2.1 Years Phase 3 2.5 Years ~12 Years Average Time to Market (New Drug) Source: ClinicalTrials.gov database (5/17), FDAReview.org (2016) Number of Registered Clinical Trials posted on ClinicalTrails.gov. KP INTERNET TRENDS 2017 | PAGE 304 New Data Streams = Enhancing & Perhaps Accelerating Clinical Trials 63% 28% 55% 83% 8% 76% 46% 76% 94% 26% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Phase I to Phase II Phase II to Phase III Phase III to NDA/BLA NDA/BLA to Approval Phase I to Approval Probability of SuccessWithout Biomarkers With Selection Biomarkers Source: Biotechnology Innovation Group, Biomedtracker, Amplion (5/16) Note: Based on 9,985 phase transitions of trials between 2006 2015. 512 phase transitions incorporated selection biomarkers for patient stratification; phase transitions identified by mapping NCT numbers from ClinicalTrials.gov with Amplion's BiomarkerBase and Biomedtracker's transition database. Selection Biomarkers (Enabled by DNA Sequencing) for Enrolling Patients in Clinical Trials Improves Probability of Success KP INTERNET TRENDS 2017 | PAGE 305 Data Silos = Breaking Down Owing to Broad Efforts to Share Data Among Scientific Community 1.9 25.4 0 5 10 15 20 25 30 2009 2010 2011 2012 2013 2014 2015 2016 Total Number of Registered Clinical Trials with Posted Results (K)Growth in Publically-Available Clinical Trial Results Source: ClinicalTrials.gov database (5/17), Nature (7/14) Number of Registered Studies with Public Results posted on ClinicalTrials.gov. ClinicalTrials.gov launched results database in September 2008 so earliest available full year is 2009. In 2014, Nature launched a peer reviewed open- access scientific journal focused on publishing datasets in machine-readable format for sharing across the natural sciences. Nature encourages authors to submit to Scientific Data in parallel but requires authors to enter the following data in community-endorsed, public repository prior to publishing in Nature: + Mandatory deposition Suitable repositories Protein sequences Uniprot DNA and RNA sequences Genbank DNA DataBank of Japan EMBL Nucleotide Sequence Database DNA and RNA sequencing data NCBI Trace Archive NCBI Sequence Read Archive Genetic polymorphisms dbSNP dbVar European Variation Archive Linked genotype and phenotype data dbGAP The European Genome-phenome Archive Macromolecular structure Worldwide Protein Data Bank Biological Magnetic Resonance Data Bank Electron Microscopy Data Bank Microarray data Gene Expression Omnibus ArrayExpress Crystallographic data for small molecules Cambridge Structural Database KP INTERNET TRENDS 2017 | PAGE 306 As Data Accumulates & Silos Breakdown Research Insights Could Accelerate Source: Wired (11/09), National Academy of Engineering (David Eddy, 2015) Note: The UK Department of Health launched a trial study, Collaborative Atorvastatin Diabetes Study (Cards), and the American Diabetes Association asked David Eddy to conduct a simulation addressing the same issues before the UK results were released. Growing Evidence That Data = Cheaper + Faster Clinical Trials Traditional Trial vs. Simulation Traditional UK Department of Health Study Archimedes Data Simulation Number of Patients 2,838 50,000 Years of Data 7 Years 30 Years Length of Study 7 Years 2 Months Conclusion Out of 4 principal findings Archimedes predicted 2 exactly right, 1 within the margin of error, and 1 slightly below. Archimedes Simulation = a mathematical model to simulate (1) human physiology and disease, (2) care process models, and (3) healthcare system resources. Ran virtual trials of large, simulated populations in a fraction of the time and cost of a traditional study. KP INTERNET TRENDS 2017 | PAGE 307 Data Insight + Translation = Healthcare Delivery Could Change Faster With Consumer Engagement & Faster Innovation Cycles KP INTERNET TRENDS 2017 | PAGE 308 40% 48% 34% 42% 26% 38% 21% 31% 10% 23% 8% 56% 0% 10% 20% 30% 40% 50% 60% Own a Wearable Go Online to Find Physician Select Provider Based on Online Reviews Have Sought Remote Medical Care / Advice* % of RespondentsMillennial Gen X Baby Boomer Consumers = Increasingly Expect Digital Health Services Especially Millennials Source: Rock Health Digital Health Consumer Adoption (12/16) *Represents % of Millennials that have sought medical care/advice over live video, % of Gen X that have over text message, and % of Baby Boomers who have over phone Millennials include 18-34 year olds; Gen X include 35-54 year olds; Baby Boomers include 55+ year olds Digital Health Adoption Across Generations KP INTERNET TRENDS 2017 | PAGE 309 Consumers = Increasingly Use Digital Health Tools Consumers Using Digital Health Tools (Telemedicine, Wearables, etc.) 88% Using at Least One Tool, 1 in 10 are Super Adopters Source: Rock Health Digital Health Consumer Adoption (12/16) Based on consumer survey of n=4,015; number of digital health categories used by respondent 20% 28% 32% 11% 6% 2% 12% 19% 23% 23% 13% 10% 0% 5% 10% 15% 20% 25% 30% 35% 40% 0 1 2 3 4 5+ % of Respondents2015 2016 Non-Adopter Super Adopter KP INTERNET TRENDS 2017 | PAGE 310 Healthcare Practices = Being Re-Imagined Leveraging Data to Optimize Outcomes Source: PBS, Propeller Health, TechCrunch, Livongo, Ayasdi, Flatiron, Xconomy, Kinsa, Omada Patient Empowerment & Health Management Propeller Health + Bluetooth Inhaler Sensor = Improved Medication Adherence + Insights Livongo + Connected Glucose Meter = Personalized Coaching + $100/Month Savings for Payers Improvements to Clinical Pathways / Protocol Ayasdi AI + Mercy Health System Patient Data = Clinical Anomaly Detection + Improved Clinical Pathway Development Flatiron + Foundation Med (FMI) = 20,000 Liked Cancer Patients Records + Personalized Medicine Preventative Health Kinsa + Crowdsourced Temperature Data = Local Flu Predictions + Proactive Treatments for Populations Omada + Preventative Program = 4-5% Body Weight Reduction + Reduced Risk for Stroke and Heart Disease KP INTERNET TRENDS 2017 | PAGE 311 Digital Health = Could It Follow Tech-Like Rapid Adoption Curves? Source: The Economist (12/15), Pew Research Center (1/17) *Social Media Adoption based on founding date of MySpace (2003) and Social Media Penetration calculated by Pew Research Center Acceleration of Technological Adoption Curves 1867-2017 Electricity (46) Telephone (35) Radio (31) Television (26) PC (16) Cellphone (13) Internet (7) Social Media (5) 0 5 10 15 20 25 30 35 40 45 50 1867 1877 1887 1897 1907 1917 1927 1937 1947 1957 1967 1977 1987 1997 2007 2017 Years until used by 25% of American Population KP INTERNET TRENDS 2017 | PAGE 312 Evolution of Genomics = Case Study in Virtuous Cycle of Innovation InputData Accumulation InsightTranslation KP INTERNET TRENDS 2017 | PAGE 313 Genomics Digitizes = Gets Faster / Better / Cheaper Introduction of Digital Technology Accelerates Cost Reduction Faster Than Moore's Law Source: National Institute of Health, National Human Genome Research Institute (7/17), Biology Reference, Illumina $1K $10K $100K $1M $10M $100M Cost to Sequence (per Genome)2007: Digital Technology Leads To Cost Reduction Illumina (Solexa) Launches the Genome Analyzer Time to sequence a genome: 10 Months Moore's Law 2015: Step Function Reduction In Cost Illumina Launches the X10 Time to sequence a genome: 27 hours KP INTERNET TRENDS 2017 | PAGE 314 Accumulation of Genomic Data Leads to 19x Increase in Genomic Knowledge Source: PloS Biology (7/15), SNPedia (5/17) SNPs (Single Nucleotide Polymorphisms) represent nucleotides where the DNA of different people vary; variants can be predictive of disease risk, drug efficacy, and phenotypic differences 4.5 88 2 422 0 20 40 60 80 100 120 1 10 100 1K 10K 100K 1MM Known SNPs (Variants) in SNPedia(K)Cumulative Number of Human Genomes (log)SNPs Number of Human Genomes Insight (Measured in Known Variants) Tracks Number Of Genomes Sequenced KP INTERNET TRENDS 2017 | PAGE 315 Genomics Research & Insights Lead to Rapid Increase in Available Genetic Tests Source: Genetests (5/17) Genetic Disorders with Diagnostic Tests Available, 5/29/2017 114 5,007 0 1,000 2,000 3,000 4,000 5,000 6,000 Number of Disorders KP INTERNET TRENDS 2017 | PAGE 316 Genomics Insight Translates to Therapeutics Source: Personalized Medicine Coalition (2017) *Number of personalized medicines calculated based on PMC's Case for Personalized Medicine and the FDA's Table of Pharmacogenomic Biomarkers in Drug Labeling Number of Personalized* Medicines Up From Almost None in 2008, 2008-2016 5 36 81 106 132 0 20 40 60 80 100 120 140 2008 2010 2012 2014 2016 Number of Personalized Medicines KP INTERNET TRENDS 2017 | PAGE 317 Evolution of Genomics Technologies Enable Deeper Research Consumer Genomics Evolving Similarly Source: PubMed, Helix Based on PubMed queries for peer-reviewed articles on genotyping and sequencing SNP Arrays and Genotyping (v1.0) Identifies variations in specific, pre-defined single letters within a gene Next Generation Sequencing (v2.0) Looks for variations throughout the entire gene Research Consumer 844 0 200 400 600 800 1000 PubMed Genotyping Articles 8,904 0 2000 4000 6000 8000 10000 PubMed Sequencing Articles KP INTERNET TRENDS 2017 | PAGE 318 Digitization = Democratization Source: Helix (5/17) Digitization = Enabling New Business Models in Genomics More Empowered + Informed Consumers Query Often: Ecosystem of Products from Partner Organizations DNA Sequenced Once KP INTERNET TRENDS 2017 | PAGE 319 Healthcare @ Digital Inflection Point Source: History of Nephrology, Welch Allyn, Medisave, Kinsa 100 Years Ago Human Touch 25 Years Ago Machine Assisted / Analog Today Technology Enabled / Digital KP INTERNET TRENDS 2017 | PAGE 320 GLOBAL PUBLIC / PRIVATE INTERNET COMPANIES = IT'S BEEN A GOOD TIME TO BE A LEADER / INNOVATOR KP INTERNET TRENDS 2017 | PAGE 321 Global Internet Companies = An Epic Half-Decade for Public + Private Internet Companies KP INTERNET TRENDS 2017 | PAGE 322 2017 Global Internet Market Capitalization Leaders = Most Extending Leads Apple / Google-Alphabet / Amazon / Facebook / Tencent / Alibaba Rank Company Region Current Market Value ($B) 1 Apple USA $801 2 Google - Alphabet USA 680 3 Amazon USA 476 4 Facebook USA 441 5 Tencent China 335 6 Alibaba China 314 7 Priceline USA 92 8 Uber USA 70 9 Netflix USA 70 10 Baidu China 66 11 Salesforce USA 65 12 Paypal USA 61 13 Ant Financial China 60 14 JD.com China 58 15 Didi Kuaidi China 50 16 Yahoo! USA 49 17 Xiaomi China 46 18 eBay USA 38 19 Airbnb USA 31 20 Yahoo! Japan Japan 26 Total $3,827 Source: CapIQ, CB Insights, Wall Street Journal, media reports. Market value data as of 5/26/17. Note: For public companies, colors denote current market value relative to Y/Y market value. Green = higher. Red = lower. Yel low = private companies, where market value represents latest publicly announced valuation. Ant Financial and Didi Kuaidi valuation per latest media reports as of 6/16 and 4/17 respectively. Xiaomi valuation per latest media reports as of 4/17 Ant Financial treated separately from Alibaba as Alibaba retains no control of Ant and will receive a capped lump sum payment in the event of an Ant liquidity event. Cash includes cash and equivalents and short-term marketable securities plus long-term marketable securities where deemed liquid. KP INTERNET TRENDS 2017 | PAGE 323 Global Public Companies = An Epic Half-Decade for Internet Companies KP INTERNET TRENDS 2017 | PAGE 324 2017 Global Market Capitalization Leaderboard = Tech = 40% of Top 20 Companies100% of Top 5 Rank Company Region Industry Segment Current Market Value ($B) 2016 Revenue ($B) 1 Apple USA Tech Hardware $801 $218 2 Google / Alphabet USA Tech Internet 680 90 3 Microsoft USA Tech Software 540 86 4 Amazon USA Tech Internet 476 136 5 Facebook USA Tech Internet 441 28 6 Berkshire Hathaway USA Financial Services 409 215 7 Exxon Mobil USA Energy 346 198 8 Johnson & Johnson USA Healthcare 342 72 9 Tencent China Tech Internet 335 22 10 Alibaba China Tech Internet 314 21 11 JP Morgan Chase USA Financial Services 303 90 12 ICBC China Financial Services 264 85 13 Nestl Switzerland Food / Beverages 263 88 14 Wells Fargo USA Financial Services 262 85 15 Samsung Electronics Korea Tech Hardware 259 168 16 General Electric USA Industrial 238 120 17 Wal-Mart USA Retail 237 486 18 AT&T USA Telecom 234 164 19 Roche Switzerland Healthcare 233 51 20 Bank of America USA Financial Services 231 80 Total $7,207 $2,497 Source: CapIQ. Market value data as of 5/26/17 Note: For public companies, colors denote current market value relative to Y/Y market value. Green = higher, red = lower. KP INTERNET TRENDS 2017 | PAGE 325 2012 Global Market Capitalization Leaderboard = Tech = 20% of Top 20 Companies40% of Top 5 Rank Company Region Industry Segment 5/31/2012 Value ($B) 2011 Revenue ($B) 1 Apple USA Tech Hardware $540 $128 2 Exxon Mobil USA Financial Services 368 434 3 PetroChina China Energy 267 318 4 Microsoft USA Tech Software 245 72 5 ICBC China Financial Services 227 70 6 Wal-Mart USA Retail 224 447 7 IBM USA Tech Hardware 223 107 8 China Mobile China Telecom 203 84 9 General Electric USA Industrial 202 143 10 AT&T USA Telecom 200 127 11 Royal Dutch Shell Netherlands Energy 197 470 12 Berkshire Hathaway USA Financial Services 196 141 13 Chevron USA Energy 194 236 14 Google / Alphabet USA Tech Internet 189 38 15 Nestl Switzerland Food / Beverages 180 90 16 China Construction Bank China Financial Services 173 58 17 Johnson & Johnson USA Healthcare 171 65 18 Procter & Gamble USA Consumer Goods 171 84 19 Wells Fargo USA Financial Services 170 73 20 BHP Billiton Australia Metals / Mining 170 75 Total $4,512 $3,257 Source: CapIQ. Market value data as of 5/31/12. Note: For public companies, colors denote current market value relative to Y/Y market value. Green = higher, red = lower. KP INTERNET TRENDS 2017 | PAGE 326 Big Get Bigger = & Go After Other Bigs Often Led by Founder-Driven Innovation / Seeing Around Corners KP INTERNET TRENDS 2017 | PAGE 327 Internet Bigs Expansion / Growth = A Long Way from Where They Started Company Founding Year Original Business Current Businesses Apple 1976 Personal Computer Maker Smartphone / Computer / Tablet MakerContent / Media MarketplaceCloud Services Google - Alphabet 1998 Online Search Engine Online Search EngineAd EcosystemWeb BrowserMobile Operating System(s)Digital Video PlatformContent MarketplaceMobile + IoT / OTT Device MakerNavigation ToolsProductivity SoftwareCloud ServicesAR / VR Software + HardwareMoonshot Chaser Amazon 1994 Online Bookseller (USA) Global B2B B2C / C2C CommerceContent EcosystemDigital Video / Music PlatformeReader / Tablet / IoT / OTT Device MakerCloud ServicesLogisticsAd Ecosystem Facebook 2004 Social Network (USA) Global Social NetworkInstant Messaging PlatformImage Sharing PlatformAR / VR Software / HardwareAd Ecosystem Tencent 1998 Instant Messaging Platform (China) Instant Messaging PlatformGamingContent EcosystemSocial NetworkAd EcosystemPaymentsDigital Video / Music PlatformCloud Services Alibaba 1999 B2B Commerce Platform (China) Global B2B / B2C / C2C Commerce PlatformNew RetailAd Ecosystem PaymentsCloud ServicesLogistics Data PlatformDigital Media & Entertainment PlatformContent EcosystemContent CreatorWeb Browser Source: Company filings KP INTERNET TRENDS 2017 | PAGE 328 Global Technology Financings = Strong Relative to History Slowing @ Margin KP INTERNET TRENDS 2017 | PAGE 329 Global Technology Financings = Strong Relative to HistorySlowing @ Margin $3 $3 $8 $7 $5 $14 $26 $19 $28 $89 $157 $58 $28 $22 $36 $40 $36 $42 $34 $25 $33 $48 $50 $44 $107 $96 $89 $30 $0 $50 $100 $150 $200 Technology IPO Volume ($B) Technology Private Financing Volume ($B) NASDAQ Annual Technology IPO and Technology Private Financing Volume ($B)Global USA-Listed Technology IPO Issuance & Global Technology Venture Capital Financing, 1990 2017YTD VC Funding per Company ($MM) $3 $3 $2 $5 $4 $4 $5 $5 $6 $8 $14 $18 $11 $8 $8 $9 $8 $9 $8 $9 $7 $7 $10 $8 $9 $13 $15 $18 $19 Source: Morgan Stanley Equity Capital Markets, 2017YTD as of 5/12/17, Thomson ONE 2017YTD as of 5/12/17. All global U.S.-listed technology IPOs over $30MM, data per Dealogic, Bloomberg, & Capital IQ. VC Funding per Company ($MM) calculated as total venture financing per year divided by number of companies receiving venture financing. *Facebook ($16B IPO) = 75% of 2012 IPO $ value. **Alibaba ($25B IPO) = 69% of 2014 IPO $ value. ***Snap ($4B IPO) = 74% of 2017 YTD $ value. KP INTERNET TRENDS 2017 | PAGE 330 Global Technology Mergers & Acquisitions = Robust Relative to History KP INTERNET TRENDS 2017 | PAGE 331 Global Technology Merger & Acquisition Volume = Robust Relative to History Global Technology M&A Deals, 2010-2016 $100 $138 $72 $145 $179 $365 $336 273 331 229 245 356 414 439 0 100 200 300 400 500 600 $0 $50 $100 $150 $200 $250 $300 $350 $400 $450 2010 2011 2012 2013 2014 2015 2016 Number of TransactionsM&A Volume ($B)M&A Volume Number of Transactions Source: Morgan Stanley, Thomson Research KP INTERNET TRENDS 2017 | PAGE 332 There are pockets of Internet company overvaluation but there are also pockets of undervaluation... Very few companies will win those that do can win big... Over time, best rule of thumb for valuing companies = value is present value of future cash flows. Value of a Business KP INTERNET TRENDS 2017 | PAGE 333 Global Public / Private Internet Companies = It's Been a Good Time to be a Leader / Innovator 1) Global Internet Companies = An Epic Half-Decade for Public + Private Internet Companies 2) Global Public Companies = An Epic Half-Decade for Internet Companies 3) Big Get Bigger = & Go After Other BigsOften Led by Founder-Driven Innovation / Seeing Around Corners 4) Global Technology Financings = Strong Relative to HistorySlowing @ Margin 5) Global Technology Mergers & Acquisitions = Robust Relative to History 6) Value of a Business KP INTERNET TRENDS 2017 | PAGE 334 SOME MACRO THOUGHTS KP INTERNET TRENDS 2017 | PAGE 335 USA, Inc.* = Understanding Where Your Tax Dollars Go * USA, Inc. Full Report: http://www.kpcb.com/blog/2011-usa-inc-full-report KP INTERNET TRENDS 2017 | PAGE 336 USA Income Statement = -19% Average Net Margin Over 25 Years USA Income Statement, F1986 F2016 Source: Congressional Budget Office, White House Office of Management and Budget Note: USA federal fiscal year ends in September. Non-defense discretionary includes federal spending on education, infrastructure, law enforcement, judiciary functions. * Individual & corporate income taxes include capital gains taxes. F1986 F1991 F1996 F2001 F2006 F2011 F2016 Comments Revenue ($B) $769 $1,055 $1,453 $1,991 $2,407 $2,303 $3,267 +5% Y/Y average over 25 years Y/Y Growth 5% 2% 7% -2% 12% 7% 1% Individual Income Taxes* $349 $468 $656 $994 $1,044 $1,091 $1,546 Largest driver of revenue % of Revenue 45% 44% 45% 50% 43% 47% 47% Social Insurance Taxes $284 $396 $509 $694 $838 $819 $1,115 Social Security & Medicare payroll tax % of Revenue 37% 38% 35% 35% 35% 36% 34% Corporate Income Taxes* $63 $98 $172 $151 $354 $181 $300 Fluctuates with economic conditions % of Revenue 8% 9% 12% 8% 15% 8% 9% Other $73 $93 $115 $152 $171 $212 $316 Estate & gift taxes, duties / fees % of Revenue 10% 9% 8% 8% 7% 9% 10% Expense ($B) $990 $1,324 $1,560 $1,863 $2,655 $3,603 $3,854 +4% Y/Y average over 15 years Y/Y Growth 5% 6% 3% 4% 7% 4% 4% Entitlement / Mandatory $416 $597 $787 $1,008 $1,412 $2,026 $2,429 Risen owing to rising healthcare costs + % of Expense 42% 45% 50% 54% 53% 56% 63% aging population Non-Defense Discretionary $165 $214 $267 $343 $497 $648 $600 Education / law enforcement / % of Expense 17% 16% 17% 18% 19% 18% 16% transportation / general government Defense $274 $320 $266 $306 $520 $699 $584 2006 increase driven by War on Terror % of Expense 28% 24% 17% 16% 20% 19% 15% Net Interest on Public Debt $136 $194 $241 $206 $227 $230 $241 Recent benefit of historic low interest rates % of Expense 14% 15% 15% 11% 9% 6% 6% Surplus / Deficit ($B) ($221) ($269) ($107) $128 ($248) ($1,300) ($587) -19% average net margin, 1991-2016 Net Margin (%) -29% -26% -7% 6% -10% -56% -18% KP INTERNET TRENDS 2017 | PAGE 337 USA Income Statement = What Net Losses in 45 of 50 Years Look Like USA Annual Profits & Losses, 1967 2016 ($1,600) ($1,400) ($1,200) ($1,000) ($800) ($600) ($400) ($200) $0 $200 $400 USA Inc. Annual Net Profit / Loss ($B)Source: Congressional Budget Office, White House Office of Management and Budget Note: USA federal fiscal year ends in September. * Individual & corporate income taxes include capital gains taxes. Non-defense discretionary includes federal spending on education, infrastructure, law enforcement, judiciary functions. KP INTERNET TRENDS 2017 | PAGE 338 When Spending > Income Debt Rises = Net Debt / GDP @ 77%Higher than 97% of USA's History USA Net Debt / GDP Ratio, 1790 2016 0% 20% 40% 60% 80% 100% 120% 1790 1815 1840 1865 1890 1915 1940 1965 1990 2015 USA Net Debt / GDP (%)Historical Net Debt / GDP (%) World War II = ~105% World War I = ~30% Civil War = ~30% 2016 = 77% Source: Congressional Budget Office Long-Term Outlook (3/17), Wall Street Journal KP INTERNET TRENDS 2017 | PAGE 339 @ Current Course / Speed (& If Government Projections are Correct) USA Net Debt / GDP Ratio Will Break WWII Record by 2035 USA Net Debt / GDP Ratio, 1790 2047E 0% 20% 40% 60% 80% 100% 120% 140% 160% 1790 1815 1840 1865 1890 1915 1940 1965 1990 2015 2040 USA Net Debt / GDP (%)Historical Net Debt / GDP (%) Projected Net Debt / GDP (%) 1946 = ~105% 2034E = ~105% Source: Congressional Budget Office Long-Term Outlook (3/17), Wall Street Journal KP INTERNET TRENDS 2017 | PAGE 340 USA = 9th Highest Public Debt / GDP Level Relative to Other Major Economies Rank Country % of GDP 2015 Public Government Debt ($B) 1 Japan 248% $10,083 2 Greece 177 347 3 Lebanon 138 68 4 Italy 133 2,342 5 Portugal 129 257 6 Jamaica 120 20 7 Cyprus 109 20 8 Belgium 106 478 9 United States 105 18,870 10 Singapore 105 302 11 Spain 99 1,124 12 France 96 2,236 13 Jordan 93 33 14 Canada 91 1,335 15 United Kingdom 89 2,458 16 Egypt 89 280 17 Croatia 87 40 18 Austria 86 302 19 Slovenia 83 30 20 Ukraine 80 37 Source: IMF Note: Ranking excludes countries with public debt less than $10B in 2015. Public debt includes federal, state and local government debt but exclude unfunded pension liabilities from government defined-benefit pension plans and debt from public enterprises and central banks. KP INTERNET TRENDS 2017 | PAGE 341 45% 63% 24% 15% 16% 16% 15% 6% 0% 20% 40% 60% 80% 100% 1991 2016 US Mandatory Entitlements (%)Entitlements / Mandatory Defense Non-Defense Discretionary Net Interest Cost USA Entitlements = 63% of Spending vs. 45% 25 Years Ago Interest Expense Down as % Owing to Interest Rate Declines USA Expenses by Category, 1991-2016 $1.3T $3.9T 10% 8% 6% 4% 2% 0% USA 10Y Treasury Yield (%)Change by Category, 1991-2016 Debt: +$11T / +427% Entitlements: +$1.8T / +307% Non-Defense Discretionary: +$387B / +181% Defense: +$264B / +83% Net Interest Cost: +$46B / +24% 10Y Treasury Source: Congressional Budget Office, White House Office of Management and Budget, US Treasury Note: Yellow line represents yield on 10-year US Treasury bill from 12/31/91 to 12/31/16. KP INTERNET TRENDS 2017 | PAGE 342 USA Entitlements = +$1.8 Trillion Over 25 Years Paced by Medicare + Medicaid Growth $267 $910 $114 $692 $53 $368 $163 $459 $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 1991 2016 USA Mandatory Entitlements ($B)Social Security Medicare Medicaid Income Security USA Mandatory Outlays by Category ($B), 1991-2016 15% 19% 28% 45% 19% 9% 27% 37% $597B 45% of Expenses $2.4T 63% of Expenses Source: Congressional Budget Office, White House Office of Management and Budget Note: Numbers may not sum due to rounding. KP INTERNET TRENDS 2017 | PAGE 343 0% 20% 40% 60% 80% 100% 1990 2016 % of Median Household IncomeRemaining Household Median Income Entitlements / Household $6K $18K $23K $38K Entitlements = 20% of median household income USA Entitlements = Equivalent to 32% of Average Annual Income per Household vs. 20% 25 Years Ago Median Household Income vs. Effective Entitlement $ Paid per Household, USA, 1990-2016 Entitlements = 32% of median household income Source: Congressional Budget Office, US Census Bureau Note: Based on median income math. Median income in current $ as of year specified. Effective entitlement dollars per household represents total entitlements over total US households (current $ as of year specified). KP INTERNET TRENDS 2017 | PAGE 344 Household Debt = Back @ Peak (Q3:08) Level & Rising Now vs. Q3:08 = Mortgage Debt (-7%) / Student Loans (+120%) / Auto Loans (+44%) 0% 5% 10% 15% 20% $0 $3 $6 $9 $12 $15 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 U6 Unemployment Rate* (%)Total Household Debt ($T)Mortgage Home Equity Revolving Auto Credit Card Student Loan Other U6 Unemployment* $13T $13T Household Debt By Category ($T) & U6* Unemployment (%), USA, 2003-2017 Source: Federal Reserve Bank of New York Consumer Credit Panel / Equifax, Quarterly Household Debt and Credit Report, Q1:17; St. Louis Federal Reserve FRED Database * U6 Unemployment Rate defined as total unemployed persons plus all marginally attached workers plus persons employed part time for economic reasons. KP INTERNET TRENDS 2017 | PAGE 345 USA Rising Debt Commitments = Non-Trivial Challenges that Need to Be Addressed KP INTERNET TRENDS 2017 | PAGE 346 Immigration = Important for USA Technology Job Creation Immigration Full Report: http://www.kpcb.com/blog/immigration-in-america-the-growing-shortage-of-high-skilled-workers KP INTERNET TRENDS 2017 | PAGE 347 USA = 60% of Most Highly Valued Tech Companies Founded By 1st or 2nd Generation Americans1.5MM Employees, 2016 Immigrant Founders / Co-Founders of Top 25 USA Valued Public Tech Companies, Ranked by Market Capitalization Source: CapIQ as of 5/31/17. "The 'New American' Fortune 500" (2011), a report by the Partnership for a New American Economy, as well as "Reason for Reform: Entrepreneurship" (10/16); "American Made, The Impact of Immigrant Founders & Professionals on U.S. Corporations." *While Andy Grove (from Hungary) is not a co-founder of Intel, he joined as COO on the day it was incorporated. **Francisco D'souza is a person of Indian origin born in Kenya. ***Max Levchin / Luke Nosek / Peter Thiel's startup Confinity merged with Elon Musk's startup X.com to form Paypal in March 2000. Rank Company Mkt Cap ($MM) LTM Rev ($MM) Employees 1st or 2nd Gen Immigrant Founder / Co-Founder Generation 1 Apple $800,898 $220,457 116,000 Steve Jobs 2nd-Gen, Syria 2 Alphabet / Google $679,533 $94,765 73,992 Sergey Brin 1st-Gen, Russia 3 Microsoft $540,127 $87,247 114,000 -- -- 4 Amazon.com $475,958 $142,573 341,400 Jeff Bezos 2nd-Gen, Cuba 5 Facebook $440,900 $30,288 18,770 Eduardo Saverin 1st-Gen, Brazil 6 Oracle $186,230 $37,429 136,000 Larry Ellison / Bob Miner 2nd-Gen, Russia / 2nd-Gen, Iran 7 Intel $170,748 $60,481 106,000 --* -- 8 Cisco $157,502 $48,510 73,390 -- -- 9 IBM $143,264 $79,390 380,300 Herman Hollerith 2nd-Gen, Germany 10 Priceline $91,597 $11,014 20,500 -- -- 11 Qualcomm $84,982 $23,243 30,500 Andrew Viterbi 1st-Gen, Italy 12 NVIDIA $84,395 $7,542 10,299 Jensen Huang 1st-Gen, Taiwan 13 Texas Instruments $80,822 $13,764 29,865 Cecil Green / J. Erik Jonsson 1st-Gen, UK / 2nd-Gen, Sweden 14 Adobe Systems $70,193 $6,153 15,706 -- -- 15 Netflix $70,007 $9,510 3,300 -- -- 16 Salesforce.com $64,611 $8,863 25,000 -- -- 17 PayPal $61,492 $11,273 18,100 Max Levchin / Luke Nosek / Peter Thiel / Elon Musk*** 1st-Gen, Ukraine / 1st-Gen, Poland / 1st-Gen, Germany / 1st-Gen, South Africa 18 Applied Materials $48,896 $12,942 15,600 -- -- 19 Yahoo! $48,570 $5,409 8,500 Jerry Yang 1st-Gen, Taiwan 20 Automatic Data Processing $45,345 $12,213 57,000 Henry Taub 2nd-Gen, Poland 21 Activision Blizzard $43,923 $6,879 9,400 -- -- 22 VMware $39,538 $7,093 18,905 Edouard Bugnion 1st-Gen, Switzerland 23 Cognizant Technology $39,339 $13,831 261,200 Francisco D'souza / Kumar Mahadeva 1st-Gen, India** / 1st-Gen, Sri Lanka 24 eBay $37,774 $9,059 12,600 Pierre Omidyar 1st-Gen, France 25 Intuit $35,501 $5,089 7,900 -- -- KP INTERNET TRENDS 2017 | PAGE 348 USA = ~50% of Most Highly Valued Private Tech Companies Founded By 1st Generation Immigrants...>48K Jobs, 5/17 Source: Based on analysis by National Foundation For American Policy, "Immigrants and Billion Dollar Startups", Stuart Anderson, 2016, subsequently updated by Aimee Groth, Quartz, 4/17. Valuation data from Wall Street Journal, CB Insights, headcount from LinkedIn (5/17). Note: Due to varying definitions of unicorns, may not align with various unicorn lists. As of 5/17 there are 100 US-based, venture-backed unicorns (including rumored valuations), 50 of which have at least one first-generation immigrant founder. Company Immigrant Founder / Co-Founder Country of Origin Market Value ($B) Uber Garrett Camp Canada $68 Palantir Peter Thiel Germany 20 WeWork Adam Neumann Israel 17 SpaceX Elon Musk South Africa 12 Stripe John Collison, Patrick Collison Ireland 9 Slack Stewart Butterfield, Serguei Mourachov, Cal Henderson Canada / Russia / UK 4 Credit Karma Kenneth Lin China 4 Tanium David Hindawi Iraq 4 Instacart Apoorva Mehta India 3 Wish (ContextLogic) Peter Szulczewski, Danny Zhang Canada 3 Moderna Therapeutics Noubar Afeyan, Derrick Rossi Armenia / Canada 3 Bloom Energy KR Sridhar India 3 Oscar Health Mario Schlosser Germany 3 Houzz Adi Tatarko, Alon Cohen Israel 2 Avant Al Goldstein, John Sun, Paul Zhang Uzbekistan / China / China 2 Zenefits Laks Srini India 2 ZocDoc Oliver Kharraz Germany 2 AppNexus Mike Nolet Holland 2 Sprinklr Ragy Thomas India 2 The Honest Company Brian Lee South Korea 2 Zoox Tim Kentley-Klay Australia 2 Jawbone Alexander Asseily UK 2 JetSmarter Sergey Petrossov Russia 2 Quanergy Louay Eldada, Tianyue Yu Lebanon / China 2 Mu Sigma Dhiraj Rajaram India 2 Company Immigrant Founder / Co-Founder Country of Origin Market Value ($B) Razer Min-Liang Tan Singapore $2 Unity Technologies David Helgason Iceland 2 FanDuel Nigel Eccles, Tom Griffiths, Lesley Eccles UK 1 Medallia Borge Hald Norway 1 Apttus Kirk Krappe UK 1 Robinhood Baiju Bhatt, Vlad Tenev India / Bulgaria 1 Rubrik Bipul Sinha India 1 Infinidat Moshe Yanai Israel 1 Warby Parker Dave Gilboa Sweden 1 Actifio Ash Ashutosh India 1 Anaplan Guy Haddleton, Michael Gould New Zealand / UK 1 Gusto Tomer London Israel 1 Proteus Digital Health Andrew Thompson UK 1 AppDirect Daniel Saks, Nicolas Desmarais Canada 1 Carbon3D Alex Ermoshkin Russia 1 CloudFlare Michelle Zatlyn Canada 1 Compass Ori Allon Israel 1 Eventbrite Renaud Visage France 1 Evernote Stepan Pachikov, Phil Libin Azerbaijan / Russia 1 Offerup Arean Van Veelen Netherlands 1 Tango Uri Raz, Eric Setton Israel / France 1 Udacity Sebastian Thrun Germany 1 Zscaler Jay Caudhry India 1 Zoom Video Eric Yuan China 1 ForeScout Noga Alon, Hezy Yeshurun, Oded Comay, Doron Skikmoni Israel 1 KP INTERNET TRENDS 2017 | PAGE 349 High Level, For All the Angst, Consider This KP INTERNET TRENDS 2017 | PAGE 350 World = Getting Better in Many Ways Down = Poverty + Child MortalityUp = Democracy + Literacy 0% 20% 40% 60% 80% 100% 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000 Extreme Poverty Not in Extreme Poverty % of People in Extreme Poverty, Global, 1820-2015 0% 20% 40% 60% 80% 100% 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000 Mortality Rate by Age 5 Survival Rate by Age 5 Child Mortality Rates, Global, 1800-2015 0% 20% 40% 60% 80% 100% 1816 1836 1856 1876 1896 1916 1936 1956 1976 1996 No Democracy Democracy % of People Living in Democracy, Global, 1816-2015 0% 20% 40% 60% 80% 100% 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000 Illiterate Population Literate Population Literacy Rate, Global, 1800-2014 Source: Max Roser, Our World in Data; World Bank; Bourguignon and Morrison, "Inequality Among World Citizens", American Economic Review 92.4, 2002; Gapminder; Polity IV; UN Population Division; Wimmer and Min, "From empire to nation-state: Explaining war in the modern world, 1816-2001," American Sociological Review 71.6, 2006; OECD; UNESCO Note: Extreme poverty defined as income level below $1.90 (int'l dollars) / day. Child mortality rates measured before and after 5 years old. Democracy based on Polity IV database. Literacy rate based on ages 15+ globally. KP INTERNET TRENDS 2017 | PAGE 351 Some Macro Thoughts 1) USA, Inc.* = Understanding Where Your Tax Dollars Go 2) Immigration = Important for USA Technology Job Creation 3) High Level = For All the Angst, Consider This ** USA, Inc. Full Report: http://www.kpcb.com/blog/2011-usa-inc-full-report ** Immigration Full Report: http://www.kpcb.com/blog/immigration-in-america-the-growing-shortage-of-high-skilled-workers KP INTERNET TRENDS 2017 | PAGE 352 CLOSING THOUGHTS KP INTERNET TRENDS 2017 | PAGE 353 Century Economic Growth Drivers Pre-18th Cultivation & Extraction 19th-20th Manufacturing & Industry 21st Compute Power + Human Potential Economic Growth Drivers = Evolve Over Time KP INTERNET TRENDS 2017 | PAGE 354 Internet Trends 2017 1) Global Internet Trends = SolidSlowing Smartphone Growth 4-9 2) Online Advertising (+ Commerce) = Increasingly Measurable + Actionable 10-80 3) Interactive Games = Motherlode of Tech Product Innovation + Modern Learning 80-150 4) Media = Distribution Disruption @ Torrid Pace 151-177 5) The Cloud = Accelerating Change Across Enterprises 178-192 6) China Internet = Golden Age of Entertainment + Transportation 193-231 (Provided by Hillhouse Capital) 7) India Internet = Competition Continues to IntensifyConsumers Winning 232-287 8) Healthcare @ Digital Inflection Point 288-319 9) Global Public / Private Internet Companies 320-333 10) Some Macro Thoughts 334-351 11) Closing Thoughts 352-353 KP INTERNET TRENDS 2017 | PAGE 355 This presentation has been compiled for informational purposes only and should not be construed as a solicitation or an offer to buy or sell securities in any entity, or to invest in any KPCB entity or affiliated fund. The presentation relies on data and insights from a wide range of sources, including public and private companies, market research firms and government agencies. We cite specific sources where data are public; the presentation is also informed by non-public information and insights. We disclaim any and all warranties, express or implied, with respect to the presentation. No presentation content should be construed as professional advice of any kind (including legal or investment advice). We publish the Internet Trends report on an annual basis, but on occasion will highlight new insights. We may post updates, revisions, or clarifications on the KPCB website. KPCB is a venture capital firm that owns significant equity positions in certain of the companies referenced in this presentation, including those at www.kpcb.com/companies. Any trademarks or service marks used in this report are the marks of their respective owners, who are not participating partners or sponsors of the presentation or of KPCB or its affiliated funds, and such owners do not endorse the presentation or any statements made herein. All rights in such marks are reserved by their respective owners. Disclaimer