A guide to fair startup valuation by Early Metrics

Helping to raise Series A investment for tech companies.
The valuation of a company is a synthesis of multiple scenarios and therefore an art of approximation. This is all the more difficult for investors who are looking to identify the new ventures that will make a real difference in their portfolio. If we were to compare it to a chemistry experiment, startups are a gaseous substance: they move fast and unpredictably, making it difficult to take a telling snapshot of their situation and formulate hypotheses that stand the test of time. Indeed, classic valuation models are geared towards predicting the long-term behaviour of solids, ie. mature companies ready for listing or already listed. This conundrum has become most felt since the advent of Silicon Valley and, more recently, the booming of European and Asian startup hubs. Investing in seed and early stage ventures has never been more exciting but the question of fair valuation still remains, as the current tools are ill-fitted for this exercise.
About Techcelerate Ventures

Tech Investment and Growth Advisory for Series A in the UK, operating in £150k to £5m investment market, working with #SaaS #FinTech #HealthTech #MarketPlaces and #PropTech companies.
Startup Early metric rate venture Valuation method growth potential
https://techcelerate.ventures
Helping to raise Series A investment for tech companies.
About Techcelerate Ventures

Tech Investment and Growth Advisory for Series A in the UK, operating in £150k to £5m investment market, working with #SaaS #FinTech #HealthTech #MarketPlaces and #PropTech companies.
Startup Early metric rate venture Valuation method growth potential
| 1
Contents
Executive Summary
Introduction
Classic Valuation Methods
Blue Ocean Strategy for Startup Valuation 
Impactful Criteria on Fundraising Success
Conclusion
References
Acknowledgements
About Early Metrics
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| 3
Executive Summary 
The valuation of a company is a synthesis of multiple scenarios 
and therefore an art of approximation. This is all the more 
difficult for investors who are looking to identify the new 
ventures that will make a real difference in their portfolio. If 
we were to compare it to a chemistry experiment, startups 
are a gaseous substance: they move fast and unpredictably, 
making it difficult to take a telling snapshot of their situation 
and formulate hypotheses that stand the test of time. Indeed, 
classic valuation models are geared towards predicting the 
long-term behaviour of solids, ie. mature companies ready for 
listing or already listed. This conundrum has become most 
felt since the advent of Silicon Valley and, more recently, the 
booming of European and Asian startup hubs. Investing in seed 
and early stage ventures has never been more exciting but the 
question of fair valuation still remains, as the current tools are 
ill-fitted for this exercise. 
As a rating agency specialised in assessing the growth 
potential of startups and scale-ups, Early Metrics has seen its 
clients, investors and multinational companies alike, struggle 
with this valuation process time and time again when trying to 
invest in a young company. That is why we set out to conduct 
this research into how the valuation method of new ventures 
could be improved. 
By assessing the strengths and weaknesses of three most 
commonly used valuation approaches (DCF, multiples and 
VC method) we were able to identify the key pain points to be 
improved. By reviewing the available academic literature and 
correlating our findings to our database of over 2000 rated 
startups, we were able to define the adaptations that need to 
be brought to traditional methods to produce fair valuations. 
Preliminary findings on traditional valuation methodologies
We therefore found that it was still relevant to use valuation 
techniques such as the DCF and multiples approach, as 
long as certain considerations specific to new ventures are 
"Startups are 
like a gaseous 
substance: they 
move fast and 
unpredictably, 
making it 
difficult to take 
a telling 
snapshot"
included. As such, we strongly believe that by combining the DCF, multiples, venture 
capitalist method as well as the entrepreneur's expectation, it is possible to obtain a 
fair startup valuation. Using Early Metrics' statistical distribution of growth potential 
scores, we were also able to add a layer of refinement to the weighted average and 
to provide an extra level of accuracy. 
Adding non-financial criteria to valuation methodologies
However, beyond its estimated value, several non-financial criteria can impact a 
startup's potential to raise funds at an attractive valuation. That is why we decided 
to explore the impact of qualitative criteria on fundraising. Through our backtesting 
process, we collected information 12 and 24 months after Early Metrics' rating on 
469 startups looking for funds and then compared the data to the predictive analysis 
performed at the time of the rating. This allowed us to identify which parameters 
can significantly improve the chances of closing a funding a round that meets the 
entrepreneurs' goals. We also found that a startup's sector can impact its chances of 
fundraising. Lastly, we analysed the relevance of growth potential in fundraising and 
found that there is indeed a correlation between the Early Metrics score and their 
fundraising success. These results lead us to believe that the valuation process can 
be indeed affected by qualitative aspects of the venture.
We hope that by sharing our research and findings we will be able to bring greater 
transparency to the valuation of startups and that in turn this will lead to successful 
business relationships between investors and innovative startups.
4 | 2018 Early Metrics. All rights reserved.
| 5
Introduction
This white paper will evaluate how traditional valuation methods can be adapted 
in order to obtain a more reliable value for seed and early stage ventures. 
Firstly, we will give a brief overview of the key levers in valuation and of the 
difficulties that most face when trying to value early stage companies. We will then 
assess the strengths and weaknesses of the most common methods, namely the 
discounted cash flow (DCF), multiples, and venture capitalist approaches. Following 
this, we will look into the modifications that can be brought to these methods for the 
valuation of startups. Using the example of a fictitious company, we will exemplify 
how these adaptations can indeed lead to more comprehensive valuations. Finally, 
we will explore which non-financial criteria have the most significant impact on a 
venture's chances of fundraising at a desired valuation. Based on our database of 
backtested startup ratings, we will analyse the relationship between the venture's 
sector and fundraising success as well as the potential correlation between the 
growth potential of a venture and its fundraising ability. Moreover, we will rank the 
impact of several non-financial criteria on the startup's capacity to raise funds. 
Key levers in valuation
Before diving into the different available valuation methods, we thought it would 
be interesting to give a brief overview of the factors that draw investors to young 
ventures in the first place.  There are essentially four key levers in early stage 
investment: cost efficiency, growth potential, market dynamics and leverage. In other 
words, a venture capitalist tries to achieve a return on investment in four ways.
Cost efficiency:
Indeed, an investor might choose to 
get involved with a startup if there is a 
potential to cut costs and increase cost 
efficiency within it. In this regard, the free 
cash flow (FCF) and operating margin of 
the venture might be important factors in 
the investor's decision. 
Growth potential:
Young companies that have high 
chances of seeing an explosive growth 
and undergoing a successful exit can 
also yield high returns for investors. 
So even if a venture lacks some of the 
attributes needed to grow fast, investors 
might still choose to offer capital if they 
see it as an opportunity to bring in their 
expertise and boost the company's 
growth potential. 
Leverage:
Leverage is another major factor 
that impacts early stage investment..  
Debt can lower the cost of tax and 
consequently increase the value of 
equity. Therefore, being able to leverage 
debt can have an important effect on 
the attractiveness of an investment 
opportunity.
Market dynamics:
Additionally, investors may be influenced 
by investment market dynamics 
especially in sectors where the 
competition to find good targets is high 
between venture capital and private 
equity players. Investors often also use 
these dynamics to their advantage to 
increase their return based on general 
excitement that builds around specific 
markets or products. 
6 | 2018 Early Metrics. All rights reserved.
The Venture Capitalist
Samantha Jrusalmy, Partner at Elaia Partners
"We like to be the first ones to invest in a company rather than 
investing in more mature companies, that are less risky but 
offer a lesser return. The second reason why we do early stage 
investments is that we prefer this stage of a company's life from a 
human point of view because it is when everything is being created: 
since we choose only early stages startups, we are there all the steps 
of the way and it creates a bond between the entrepreneurs and us. 
We want to live awesome ventures with great entrepreneurs so we 
partner early and roll up our sleeves. Finally, it allows us to stay in the 
loop, with the startups to follow on more funding rounds. 
| 7
Lack of history:
One of the key factors that make new 
ventures difficult to value is the fact that 
they have a very short history. This may 
seem obvious, but a one to two-year 
long history implies it is much harder and 
riskier to use predictive methods based on 
financial data. Indeed, startups generate 
little to no revenue while they incur 
sizeable charges in order to set up their 
business. Therefore they generally have 
negative cash flows. 
Low survival rate:
New ventures generally have a very high 
risk of bankruptcy, especially in their 
first four years. The commercialisation 
and scaling up stages seem to be the 
toughest and most determinant in terms 
of survival. John Watson and Jim Everett's 
study (1996) of over 5196 ventures showed 
the average annual failure rate exceeded 
9%. Therefore, valuation methods must 
somehow reflect this important risk in 
the case of young companies. It is worth 
noting that, although bankruptcy risk is 
highly correlated to the age of a venture, 
startups of the same age can still be at 
very different maturity stages, ranging 
from just an idea company, to having a 
minimum viable product (MVP) or a fully-
fledged commercialised product. 
Valuation divergence due to dilution:
Another factor which complicates the 
valuation of startups is the risk of dilution 
of the company's equity. This is due to the 
fact that startups are highly dependent on 
private equity, rather than debt or public 
markets. Founders generally provide the 
vast majority of the starting capital before 
looking for external investors. Chances are 
that a new venture will go through several 
rounds of fundraising to acquire the 
necessary capital to develop their product, 
go to market and scale. This means that 
the first investors incur the risk of seeing 
the value of their shares decrease over 
time. Therefore, even if a venture is 
extremely successful at increasing their 
overall value at exit, the value growth will 
be lesser for the first investors. This leads 
to what Luis Villalobos refers to as the 
valuation divergence: the growth of value 
at exit of a startup compared to the growth 
of value perceived by initial investors 
is generally off by a factor of three to 
five. Investors generally try to protect 
themselves by negotiating warrants on 
first cash flows, veto rights, a ratchet or 
other special clauses. 
The difficulties of startup valuation
On top of the aforementioned levers, there are factors that are particular to young 
ventures which should be considered in the valuation process. In fact, these are the key 
reasons which make valuing startups more difficult than mature companies. 
Below we look at the main three startup features that complicate the process.
| 7 
The Accelerator
Ccile Brosset, 
Director at 
Bpifrance Le Hub
"Early stage investors have so much 
choice when it comes to picking a 
startup, so it's difficult for them to 
place the right bet. Startup valuation 
is also tricky as it's mainly based on 
immaterial things, with little hard data 
to use other than that of the market 
the startup operates in.
Classic Valuation Method #1
Discounted Cash Flow (DCF)
How it works
Income approach techniques seek to determine the value of  a company by 
assessing the value of the future cash flows to be received by the shareholders or the 
business. This value is discounted for the passage of time and risks at the return rate 
required by the investors.
The discounted cash flow or DCF is the most widely used income approach 
technique. It aims to forecast the value of cash flows to the firm based on its P&L, 
ignoring the effects of leverage. It also determines the value of the shareholders' 
wealth by subtracting the net debt. Simply put, the DCF is measured by combining 
money, time and risk. 
The DCF method should discount cash flows until the business stops. Indeed, 
most businesses are assumed to be a "going concern". Therefore a business plan 
is generally forecasted over 15 years and then a terminal value (TV) is computed, 
assuming the company has reached a mature stage. 
The formula to calculate FCF to the firm is:
    Free Cash Flow to Firm = EBIT x (1 - Tax%) + Depreciation and Amortisation 
                                                 - Net capital expenditure - Increase in working capital
 
Perpetual growth rate, also referred to as the terminal growth rate, represents an 
assumption that the company will continue to grow (or decline) at a constant rate 
into perpetuity. Typically, the rate ranges between the historical inflation rate (2% to 
5%) which can sometimes be approximated by the historical GDP growth rate when 
better suited. This rate is used to determine the terminal value of a company in the 
DCF approach, among other things, and gives an indication of a company's long-
term growth projection.
8 | 2018 Early Metrics. All rights reserved. 
| 9
For standard businesses, the terminal value can be estimated using the
 Gordon Shapiro formula:
TV = FCFn / (R - g)
Where:
 TV = Terminal value (at liquidation)
 FCFn = Normalised free cash flow to the firm (in terminal year) 
 R = Weighted average cost of capital (WACC)
 g = Perpetual growth rate
To then calculate the DCF, the formula is:
DCF = [CF1 / (1+R)1] + [CF2 / (1+R)2] + ... + [CFn / (1+R)n] 
Where:
CF = Cash flow
R= Discount rate (WACC)
Weaknesses
When it comes to using DCF to value a startup there are several limitations that arise. 
Firstly the lack of historical performance on which to base forecasts hurts the 
reliability of cash flow projection and the terminal value calculation. The youth of the 
company also implies that its future performance is very uncertain and its associated 
risks are naturally higher. Another limiting factor is the fact that new ventures are 
often loss-making and therefore have negative cash flows. 
As was mentioned in the introduction, the risk of bankruptcy is much higher for a 
new venture. Hence, it is impossible to base its terminal value on a 15 year forecast 
when it might not even survive 4 years.  Meanwhile, startups have great upside 
potential in case of success.
Lastly, stable growth is out of reach when looking at a startup's business plan. 
Indeed, companies that are between the Seed and Series B round of funding 
generally experience an extremely rapid growth. This speed of growth clearly cannot 
be sustained on the long term, therefore it cannot be used to predict the perpetual 
growth rate, an important variable in the calculation of terminal value. Therefore, the 
Gordon-Shapiro is ill-fitted for high-growth businesses. 
There is one more limitation to the DCF that is relevant not only for the valuation of 
startups but also that of standard businesses: it does not take into account market 
trends and the company's positioning. That is why it is worth combining the DCF 
method to the next approach we will analyse: the multiples approach. 
Classic Valuation Method #2
Multiples Approach
How it works
The multiples approach, also known as peer multiples method, estimates the value 
of a company by comparing it to similar companies. Whereas the DCF was an income 
approach, this is a market approach.  
To use this approach, the first step is to choose which market and companies to 
compare the business to. Then, the metrics which to base the comparison on are 
identified and lastly the value or price of each metric is calculated as a multiple. This 
allows for the measurement of a relative valuation which should reflect its long term 
prospects.
The aggregates used to compare peers usually include: the top line, EBITDA and 
the number of customers. The market price is also defined by looking at peers with a 
similarly structured P&L and business model (subscription, freemium, etc.). 
10 | 2018 Early Metrics. All rights reserved. 
Weaknesses
Although this approach is arguably better suited for young ventures, it still presents 
certain weaknesses. 
Firstly, many startups are setting new standards by inventing new products or by 
disrupting existing production standards or distribution channels. This means there is 
often no market to compare to for groundbreaking innovation. 
Secondly, at the risk of stating the obvious, listed peers are generally bigger and 
older companies than the startup in question, so they are not similar enough to be 
compared to each other. 
Then, metrics can be negative or too small to be used as a reference. Indeed, 
revenues are sometimes too low (or non-existent) to be used as a base. A startup's 
revenues also tend to evolve fast, which begs the question: which revenues should 
be taken into consideration? The previous year's? The TTM or MRR? Furthermore, 
other metrics aside from revenue generally remain negative, even for high-potential 
startups. 
| 11
Classic Valuation Method #3
Venture Capital Method
How it works
The venture capital (VC) method takes into account several of the considerations 
of the DCF and multiples approaches previously presented. However, this approach 
also relies heavily on the investor's market knowledge and, to a certain extent, 
intuition. 
Pricing a young startup based on its current value generally amounts to quite a 
small sum and is not necessarily representative of the potential of the venture. The 
VC method aims to mitigate this problem by giving a theoretical future value (or 
exit value) based on several scenarios. The first step is to look at the turnover and 
specific aggregates from the P&L and then to apply a multiple to these parameters. 
This results in an exit value, which is usually high as it only takes into account the 
startup's potential and not the risks. 
To then obtain a net present value of the targeted exit value computed, one must 
apply a discount rate in the form of a percentage on the overall value previously 
calculated. This rate is representative of the risks associated with the venture and it is 
primarily based on the maturity of the company and its bankruptcy risk. 
Weaknesses
Because the venture capital method partly relies on the multiples approach, it 
naturally shares its limitations, such as the difficulty to find comparable aggregates 
and relevant companies against which the venture in question can be assessed.
Moreover, this method can suffer from a lack of transparency especially if mistakes 
are made when defining key assumptions, such as revenue projections, since they 
can impact the validity of further steps and are difficult to spot. This can also be 
frustrating for entrepreneurs because, as an empirical method, it is not always the 
clearest. 
Lastly, the opacity of the discount rates can be problematic but misunderstandings 
can be avoided if the investors clearly define the IRR, i.e. their return objectives.
Other classic valuation methods
The three methods analysed earlier are certainly not the only ones available to value 
a company. 
Notable alternatives include the First Chicago method, which combines the 
Multiples and DCF methods applied to three scenarios (best, base and worst 
scenario), as well as the profitability index approach, which quantifies the amount of 
value created per unit of investment. 
However, the DCF, Multiples and Venture Capital methods remain the most 
commonly used ones and have the strongest backing in terms of academic 
literature. That is why we will not delve further into other methods. 
Instead, we will explore how the limitations of these three main approaches can be 
mitigated to obtain a more representative valuation for early stage ventures.
12 | 2018 Early Metrics. All rights reserved. 
| 13
Blue Ocean Strategy 
for Startup Valuation
When we set out to research better ways to 
value startups, we decided early on that it 
was unwise to try and reinvent the wheel. We 
were not looking to create a solution from 
scratch which would compete with much more 
established methods, used and recognised by 
the investment industry for decades. Instead, 
we focused on bringing small but significant 
adaptation to existing techniques and to combine 
them in a way that is most representative of a 
young venture's value. The traditional methods 
we chose to focus on have proven their relevance 
for standard businesses, but at the time of their 
conception they were just not meant to be used 
for young ventures. That is why we identified 
where their flaws lied in respect to valuing 
startups and defined the following adaptations to 
optimise them.
| 13 
Adapting the DCF to startups  
Before we delve into the adaptations of the DCF for startups, it is worth noting that 
challenging the business plan of a venture is an important step before even starting 
the valuation process. Indeed, if it is done properly, it can significantly improve the 
level of certainty of the projections. We recommend challenging the business plan 
of a startup by looking not only at trends, but also at measurable metrics. At Early 
Metrics, our analysts challenge a venture's business plan by formulating hypotheses 
based on the data of other business plans from comparable startups. This allows 
to get a clearer picture of the venture's financial health and level of preparation for 
future development. 
14 | 2018 Early Metrics. All rights reserved. 
Reducing the forecasting period
Given that startups generally experience explosive growth in 
their first five to ten years, they are far from reaching a growth 
in line with the market or global GDP. Therefore, the perpetual 
growth rate (PGR) is not a relevant indicator. New ventures are 
very far from reaching a stable pace of growth and their lack of 
history means a projection over 15 years would carry a high level 
of uncertainty. That is why we argue that it is best to limit the 
forecasting period to 5 years when valuing startups through the 
DCF method, in order to reduce the level of uncertainty.
Focusing on the top line and exit value
As it is not possible to calculate a young venture's PGR, some 
of the conditions of the Gordon-Shapiro formula are unmet. 
Therefore, the terminal value (TV) cannot be calculated as a 
normalised cash flow. To compensate for this, we suggest that 
the TV should be measured primarily based on the top line. 
Furthermore, we argue that the exit value of a venture should be 
considered as a potential cash flow to the shareholders.
Measuring risks particular to startups
As we mentioned earlier, seed and early stage companies have a 
high bankruptcy risk. Therefore, this risk and other factors specific to 
startups should be measured and taken into account into the DCF. 
By identifying and quantifying the risks related to the venture, it is 
possible to adapt the DCF method in a way that is more representative 
of the venture's value. The IRR should reflect these risks as well. 
| 15
CASE SCENARIO 
Startup X is a (fictitious) Scottish startup building new manufacturing robots to 
optimise the production of electric vehicles. The company has been running for 
two years and has attracted the attention of a VC fund in France specialised in 
Industry 4.0 solutions.
To help the fund decide whether to move forward with Startup X, Early Metrics 
does an Investment Scan which includes a growth potential rating and a 
financial valuation.
We obtain the following value using the DCF method adapted to startups:
Adapting the Multiples Method to Startups  
Building a database of qualified and comparable aggregates
As startups cannot be compared to listed companies in the same industry, the 
metrics used in the multiples method must be chosen differently than in traditional 
cases. For instance, we recommend to select peers who have a similar:
 product and in the same industry
 approach (technology or commercially led)
 maturity (seniority, revenue, product stage, etc.)
 growth potential
 business model
 P&L and cost structure.
Then, we argue it is best to use the Multiples method by combining several data 
points, such as a three-pronged approach based on P&L, business model and 
industry. This is particularly relevant for very innovative businesses who do not 
have any direct competitors and operate in a new industry. In other words, it allows 
us to create a relatively homogenous database of comparable aggregates and 
compensates for the lack of "similar stories" that can make the multiples approach 
seem inadequate for startups. Moreover, when selecting the metrics, it is worth first 
defining the drivers that specifically affect the value of the venture in question. 
Adapting to the right time scale
When looking at historical revenues, it is important to adapt the 
time scale to the venture in order to collect the most relevant and 
representative data. Indeed, startups change so fast that looking at 
the previous year's results may not be representative of their potential 
at all. Therefore, it is best to adapt the time scale of the historical 
revenues used in the valuation according to the company's product 
and commercial maturity. For instance, using financial results from 
the previous month can skew the perception of a young business as 
it can experience quick and large fluctuation month after month. We 
argue that it is most reliable to consider results over the previous two 
semesters when looking at a startup's financial history. 
Focus on positive metrics
Once the metrics have been selected, we argue that it is best 
to compute multiples on the metric that is the most likely to 
be above zero. In this regard, sales figures can be a reliable 
metric to focus on for early stage businesses. 
16 | 2018 Early Metrics. All rights reserved. 
| 17
CASE SCENARIO 
Since Startup X operates in the robotics and manufacting markets and has 
had a turnover of 570,000 in 2017, we compare it to other startups of similar 
maturity and active in the same sectors. 
We obtain the following value using the Multiples method adapted to 
startups:
Adapting the VC Method to startups  
Identifying and measuring layers of risk
In order to reduce the level of uncertainty and improve 
on the VC method, we recommend conducting an 
in-depth identification and measurement of the risks 
relevant to the startup in question. Indeed, when 
using this approach, investors usually apply an overall 
discount rate primarily based on the maturity of the 
venture or on the financing round stage of the startup as 
per Damodaran's academic work and other academic 
literature. However, funding stage is not the only metric 
that could impact a startup's value negatively. 
We argue that there are key risks that should be 
considered on top of the startup's age to determine 
its value, among which we can focus on liquidity, 
bankruptcy and dilution. The liquidity risk refers to the 
potential lack of marketability of a product if the market 
is not mature enough or demand decreases drastically. 
It is usually considered to be quite stable at 35%. Then, 
the bankruptcy risk of a company is largely reliant on 
the age of the startup and based on academic literature, 
such as  Damodaran's research. Lastly, the dilution risk 
stems from a companies need to raised capital through 
several funding rounds. The more rounds a startup 
wishes to do, the less the value of its stock. This is 
therefore detrimental to its valuation especially for the 
first investors buying shares in the company who will 
see their investment grow less than the overall company 
value. 
By considering these three risks, we can obtain a 
discount rate more closely tailored to the profile of the 
venture. 
18 | 2018 Early Metrics. All rights reserved. 
| 19
CASE SCENARIO 
Startup X has to face specific challenges such as certification to bring its 
product to market. So we defined the risks and opportunities particular to the 
startup and then measured their impact on future revenues in three scenarios. 
We obtain the following value using the VC method adapted to startups:
Considering the entrepreneurs' goals
Although it is rarely taken into account, an entrepreneur's goal for their company 
can be a good indication of a venture's potential. If the startup's founder has set a 
desired value in line with that measured by traditional methods (DCF, multiples, etc.) 
then the investor can be reassured in the fact that the venture is run by a person that 
has a realistic vision of its potential. On the other hand, it may be beneficial for an 
entrepreneur to aim a little higher than the conventional value calculated through 
classic methods. This could indicate that the management of the startup will work 
hard to surpass expectations and potentially make a difference compared to its 
competitors. Lastly, if the entrepreneur's valuation is completely off the mark and 
unrealistic, it could be considered as a red flag for investors.
CASE SCENARIO 
The team at Startup X aims to raise 4.2 million and give away 15% of their 
shares. They need a lot of capital to improve the design of the robots and scale 
their production. The company is also hoping to open a new site in Germany. So 
in this scenario, the investor will have strong bargaining power. 
By looking at Startup X's need for funding and dilution goal, we can 
determine how the investor's bargaining power would affect the valuation 
bracket:
20 | 2018 Early Metrics. All rights reserved. 
| 21
The Startup Founder
Sylvain Tillon, CEO at Tilkee
" 
The valuation of an early stage startup is a 
matter of power (that investors don't want to 
take generally), of gauging offer and demand, 
and sticking a finger in the air. More seriously, 
our valuation was calculated on the basis of the 
potential exit value of Tilkee and on our turnover 
(recurring revenue times five). This reflected the 
value of our startup quite well, which we capped 
in order to further the project on our terms: we 
refused to over-sell (contrary to what fundraisers 
advised) so that we could maintain a logic that 
made sense with our growth plans. We accepted 
a slightly lower valuation but chose investors that 
best suited us in terms of experience and vision. 
We also opted for a clear stock option system with 
achievable goals. For this we had an advantage, 
we didn't need funds in the short term: we were 
at breakeven and we had a bit of liquidity. This 
allowed us to be patient and demanding!
The Venture Capitalist
Samantha Jrusalmy, Partner at Elaia Partners
"We invest in companies, get a share of the capital, a board seat and, 
within six to seven years, we need to have an exit. If we are not convinced 
that we can achieve at least five times what we invested, then it's not a 
good deal for us. Our focus is financial performance so we look at ambitious 
and global projects. 
22 | 2018 Early Metrics. All rights reserved. 
Weighted average of methods
As we have seen so far, each valuation method has its strengths and weaknesses. 
By combining multiple approaches, it is possible to mitigate their limits and 
obtain a more representative value. After calculating a startup's value using the 
aforementioned methods, we recommend doing a weighted average of the obtained 
results. To weigh each method, we analyse the cost structure and nature of startup 
and then decide which approach is the most representative. 
It is rare for the DCF to be the most representative valuation for a startup. This 
approach works best for businesses that are highly predictable. If a startup signs 
long contracts with its clients and its management has worked extensively on its 
projections, making its business plan very reliable, then we could consider that the 
DCF should have a bigger weight in the averaged value. Although it is very unlikely 
for a young venture to meet both these conditions, the DCF is the only method that 
reflects the structure of costs so it is still interesting to consider.
When it comes to deciding which one of the multiples or the VC method is most 
representative, things get a little trickier. The VC approach calculates the future 
performance of a business (taking growth potential into account), while the peers 
multiples method measures results achieved so far. Therefore the VC method is 
better suited to startups with a big growth potential. The multiples approach, on the 
other hand, is better if revenue forecasts are very uncertain. Overall, the VC method 
can be seen as more refined because it considers the evolution forecast specific to 
the valued venture, hence producing a more tailored valuation. 
Each method produces a bracket or a range where the value should fall. By 
combining the results of multiple methods there is a risk ending up with quite a large 
bracket, which in itself is not very informative. To refine this, we use the Early Metrics 
database of rated startups and see where the company in question falls in the 
statistical distribution of ratings. In other words, we determine how this company's 
growth potential compares to others. Depending on the decile where the startup's 
rating falls, we are able to determine the most likely value within the previously 
obtained bracket.
| 23
CASE SCENARIO 
In the case of Startup X, the valuation method that is best suited is the venture 
capital or VC method as it takes into account specific risks and opportunities in 
the electric vehicle manufacturing sector. 
As part of Early Metrics' rating, Startup X's growth potential has been scored. 
Looking at where this score sits compared to that of other rated startups, we 
find that Startup X is among the top 10% of startups. This allows us to define 
the amount in the calculated bracket that most accurately reflects Startup X's 
value.
By combining the weighted average of valuations obtained through various 
methods and looking at the decile that Startup X's rating falls in, we obtain a 
final valuation:
Impactful Criteria on Fundraising Success
Overview of fundraising success
Early Metrics focuses on measuring the growth potential of technology startups and 
SMEs using a proprietary methodology. This methodology is centered around three 
axes of analysis: the management team (eg. ability to convince, past experiences 
of the founders), the product (eg. maturity, innovation level) and the market (eg. 
positioning, barriers to entry). Analysts at Early Metrics rate several non-financial 
criteria in each of these three pillars, collecting hundreds of data points which are 
then summarised in a score out of 100. 
Since its foundation, Early Metrics has rated more than 2000 startups in 15 sectors. 
A portion of this database (900 companies) has also been backtested after the 
rating, in order to assess the validity of our methodology and maintain a high level 
of quality in our rating model. This data has also allowed us to identify interesting 
trends relating to the valuation and fundraising potential of startups. 
To investigate which non-financial parameters have a strong impact on a startup's 
potential to fundraise at its desired value, we turned to our own data of backtested 
ventures. Our first step was to select from our database those which declared 
wanting to fundraise at the time of rating. This gave us a sample of 469 companies. 
We then looked at the overall success rate of these startups in raising funds in line 
with the entrepreneurs' expectations.
24 | 2018 Early Metrics. All rights reserved. 
Table 1: Overall fundraising success 12 and 24 months post-rating
Out of the startups that said they were looking for funds at the time of rating by Early 
Metrics, 35% managed to secure funding 12 months after being rated and 48% raised 
24 months after the rating. 
As our backtesting process relies on feedback provided by the startups, our samples 
at 12 and 24 months are not homogenous. Table 2 shows the data collected from the 
80 companies backtested both 12 and 24 months after rating, i.e. where the startups 
replied to our survey twice. 
| 25
Table 2: Fundraising success of homogenous sample at 12 and 24 months post-
rating
From the table above, we can see that the sample analysed at 12 and 24 months 
post-rating confirms the trend observed on the first sample (Table 1). Indeed, 53% of 
startups closed a fundraising round at or above their expected value. Among these, 
33% took 12 months or less to get funding. 
Analysis by industry
After analysing the overall success rate in raising funds of our database of rated 
startups, we decided to delve deeper into our data and explore the potential 
correlations between the industry of the young ventures and their potential for 
fundraising. 
To proceed in this analysis, we first had to filter out the sectors in which we lacked 
representative data. Below is the dataset by sector that resulted: 
 
Table 3: Fundraising success rate by sector
Among the 15 sectors researched in Early Metrics' database, three sectors were 
excluded from the analysis (AgriTech, EdTech, Tourism and Leisure) as we did not 
have a representative sample of startups in these (less than 15). 
The analysis of the sample just 
over 12 months, which is more 
homogenous, confirms the 
aforementioned trends. It also 
allows us to identify two surprising 
phenomena - the first being 
that the CleanTech industry also 
seems to be more successful than 
the average in securing funds. The 
second notable observation is that 
startups in the IT & Data sector as 
well as those in the eHealth sector 
seem to have a particularly low 
fundraising success rate in the first 
12 months following their rating. 
Although it was excluded in 
the overall analysis, it is worth 
noting that the Tourism and 
Leisure sector has a very strong 
fundraising success rate. Indeed, 
11 out of 14 startups (or 78%) 
managed to raise funds within 24 
months of the rating. This trend 
would have to be supported by 
further data to prove its validity, 
but it is certainly one to look out 
for. 
Graph 1: Analysis of fundraising timing by sector
Among the selected industries, three of them had an above average success rate: 
BioTech, Mobility, E-Commerce & Retail. On the other hand, two sectors underperformed 
on their overall success rate: Smart Cities as well as B2B Software. 
26 | 2018 Early Metrics. All rights reserved. 
| 27
Analysis by growth potential score
Beyond the sector of the business, we wished to analyse which other factor would 
impact the rate of success in fundraising. Firstly, we decided to investigate whether 
there is a correlation between the growth potential of a startup and its chances of 
fundraising successfully. 
We calculated the overall average rating for each sector, the average rating 
of startups that failed to raise what they hoped, and the average of those who 
succeeded. The results have been compiled in the table below with an index basis 
of 100: 
Table 4: Growth potential score by sector on 100 basis
The data above generally confirms the hypothesis that growth potential has an 
impact on fundraising success: the majority of startups that managed to raise funds 
had a better growth potential score than those who failed to raise. 
Table 4 shows that there are 
three outliers contradicting 
the trend (Biotech, EdTech, 
Fintech & InsurTech). This 
is also clearly visible in 
Graph 3, which highlights 
the differences between 
fundraising success rate 
and the delta of the scores 
of startups that raised 
successfully versus those 
that didn't.
Graph 2: Growth potential rating gap between 
startups that raised funds and those that did not 
by sector 
Graph 3: Analysis of the impact of growth potential (rating) and of the sector of the 
startup on fundraising success
For the Fintech & InsurTech as well as Biotech startups, we can assume that they 
do not align with the trend because they are highly regulated sectors and therefore 
involve a longer time-to-market, which can hurt their overall growth potential but not 
necessarily their fundraising success rate. Moreover, Biotech products are usually 
capital intensive projects as they require upfront investment from the startup in 
specific equipment and lengthy R&D. As investors are familiar with the challenges 
related to this sector, they do not penalise startups based on their lesser growth 
potential. We can also infer that Edtech also does not reflect the trend due to the 
limited size of the sample. 
So from the data above, we can conclude that growth potential is generally 
positively correlated to fundraising success, but the importance of the growth 
potential can be influenced by the sector in which the startup operates.
28 | 2018 Early Metrics. All rights reserved. 
| 29
Innovativeness of the project
How original a startup is. The innovation 
can be in the nature of an offer (a 
totally new product), technical (a novel 
production process), marketing (new 
business model) and/or a geographical 
innovation (copycat in a new market). 
Complementarity in skill sets
How much the skill sets of the various 
team members complement each other.  
The more variety there is in the team's 
capabilities, the easier it is for the startup 
to perform well in different aspects of its 
activities (product development, go-to-
market strategy, etc.). 
Influence in the press and social media 
How many followers a startup has on 
social media and how many mentions in 
the press (different thresholds apply to 
different maturity stages and sectors). 
Speed of execution
How fast a startup can bring a product 
to market. This can be affected by the 
skills of the team members as well as 
the regulatory environment or even the 
complexity of the product. 
Financial management skills
How experienced and skilled the team 
is in managing and monitoring the 
company's finances. 
Analysis of impactful qualitative criteria 
As part of our growth potential assessment of startups, analysts at Early Metrics 
evaluate a set of qualitative criteria. We have therefore asked ourselves which of 
these non-financial parameters could be good indicators of fundraising success. 
For each criterion and for the entirety of the sample, a score between zero and five 
was attributed. We then divided the sample in two: those that had raised funds at 
the amount expected by the entrepreneurs and those that had failed to do so. We 
then measured the relevance of each criterion in relationship to the achievement or 
failure to reach the target. The model also eliminates collinearity from the results. 
Following this, we identified among the available criteria those that enabled the 
prediction of the success or failure of a fundraising round. 
To carry out this process, we adopted a simple statistical approach based on a 
binary variable (success or failure of the fundraising). Moreover, the analysed criteria 
were selected in such a manner to optimise their number among the overall list of 
available parameters and to predict the occurrence of the binary event. 
Among the 25 criteria analysed, five of them have been identified as significant (ie. 
with a shown predictive power), non-linked (with correlations between the criteria 
as close to zero as possible) and allowing a reliable prediction of the success or 
failure of a fundraising. 
By focusing on these 5 qualitative criteria, it is possible to build a predictive model 
for the success of a funding round. If the startup does well in these five traits it will 
therefore have a greater negotiation power and better chances of reaching its goal. 
30 | 2018 Early Metrics. All rights reserved. 
The Accelerator
Ccile Brosset, Director at Bpifrance Le Hub
" 
I find this list of five criteria very relevant. Indeed at Bpifrance, 
we mainly look at the innovativeness of the project and the 
complementarity of the team's skill sets. One topic that could be 
added to these five is the network of the founders. Some teams can 
make it on their own but they're rare. For instance, Mathilde Collin, 
CEO at Front, managed to close a funding round of $66 million led 
by Sequoia in big part thanks to her personal business network. 
So it's very important to be able to surround yourself with the best 
people internally, by hiring the best candidates, and externally, by 
making strong allies.
The Venture Capitalist
Samantha Jrusalmy, Partner at Elaia Partners
"At the stage where we invest at, meaning pre-Seed, Seed and 
Series A, the main priority is the team. What we want to see is 
complementarity not only in the skills but also in the vision of the 
founding team members. At Elaia we only invest in disruptive projects 
that have a real technological asset but also that set barriers to entry 
from the very start. Since we have an expertise in tech investments 
and we can't assess performance based on traction or execution in a 
very young venture, we look at the innovativeness of the project which 
is also a way to "de-risk" ourselves. Knowing how to do a proper P&L 
and managing company's accounts can also put entrepreneurs in 
the spotlight, but this is not very relevant for pre-Seed startups since 
they have little financial data to handle. However, we do challenge the 
business plan extensively, mainly to understand the coherence of the 
figures rather than their total accuracy. 
The Startup Founder
Sylvain Tillon, CEO and founder at Tilkee
"To my mind, the chances of fundraising success of a startup are also linked to 
the whole team at large, not only to the management. I was quite surprised 
that no fund contacted our collaborators to know more about their motivation, 
their trust in the project, our management style...
| 31
Conclusion
Assessing the value of a startup is always a difficult task and in this white paper 
we only scratched the surface as to why that is. It is also a process that undeniably 
includes an element of subjectivity to some extent. Nonetheless, we have seen 
that bringing certain alterations to traditional methods and combining their results 
allows for a relatively reliable calculation of a startup's value. 
In particular, we argue that when using the discounted cash flow or DCF it is best 
to limit the forecasting period to five years, to calculate the terminal value based 
on the top line, and to calculate the risks specific to the venture. Alternatively, if the 
multiples method is taken, it is important to build a database of qualified metrics and 
take a three-pronged approach to compare peers across these variables. Moreover, 
we recommend focusing on positive metrics and looking at the financial data over 
the last two semesters rather than the past year to obtain a more accurate snapshot 
of the venture's potential. On the other hand, we believe the venture capitalist 
method can be improved by identifying and quantifying the major risks faced by 
startups such as risks of liquidity, bankruptcy and dilution rather than just applying 
a standardised discount rate based on the company's maturity. We also suggested 
considering the entrepreneurs' desired value in the overall process, as this can be 
an indication of their ambition and their ability to self-assess. By applying these 
adaptations and combining all these approaches, we argue that one can obtain a 
bracket of valuation that is more reflective of the startup in question compared to 
traditional methods. Thanks to Early Metrics' database of growth potential ratings, 
we have shown that we can apply an extra layer of filtering and refine the bracket in 
relationship to the startup's positioning compared to other rated businesses. 
Having data about the growth potential of startups has also led us to wonder 
how non-financial metrics could impact the fundraising success rate of young 
startups, and therefore affect their valuation. Looking at a sample of startups 12 
and 24 months after being rated by Early Metrics, we found that 53% of ventures 
in the sample closed a funding round at the value desired by the entrepreneurs. 
Among these, 33% took 12 months or less to get funding. Then, we analysed the 
ventures' fundraising success in relationship to the sector they operate in and found 
that in some sectors it is easier to attract capital than others. Among the selected 
industries, three of them had an above average success rate: BioTech & MedTech, 
Transport & Mobility, E-Commerce & Retail Enablers. Through further analysis of our 
database of ratings, we also observed that a better growth potential assessment 
does generally correlate positively to higher success rate in fundraising, at varied 
levels depending on the sector. Finally, we delved deeper into the qualitative data 
to find out which attributes are the best indicators of fundraising success, implying 
an attractive valuation. The five most impactful criteria were identified as speed of 
execution, influence on social media, complementarity of the team, innovativeness 
of the project and financial management skills. Although not directly related to the 
valuation methods analysed earlier, these qualitative metrics are important as they 
do ultimately impact the venture's chances of success, not only in fundraising but 
also in reaching maturity and expanding.
| 31 
This is a preliminary study on the non-financial criteria that weigh into valuation and 
fundraising, so we do acknowledge some limitations. For instance, our samples of 
startups analysed at 12 months after being rated by Early Metrics and then after 
24 months are not homogeneous. Indeed, the sample at 24 months is cumulative 
and includes the startups that raised in the first 12 months post-rating. The decision 
to combine the two was driven by the need to build a sample size of statistical 
relevance and allowed us to draw interesting results from the data. Moreover, we 
lacked data into certain sectors and therefore had to focus our research on fewer 
markets. However, we argue the study was still representative of a wide range of 
sectors. 
We hope that by sharing our research and findings we will be able to bring greater 
transparency to the valuation of startups and that in turn this will lead to successful 
business relationships between investors and innovative startups.
32 | 2018 Early Metrics. All rights reserved. 
The Accelerator
Ccile Brosset, Director at Bpifrance Le Hub
"At the end of the day, a valuation needs to be based on these two 
considerations: on business fundamentals that are believable and on the 
confidence that the management team can deliver this vision. I also think we 
need to move away from financial methods to go towards more pragmatic and 
down-to-earth approaches. 
| 33
References
Damodaran, A. (2009). Valuing Young, Start-Up and Growth Companies: Estimation 
Issues and Valuation Challenges. SSRN Electronic Journal. DOI: 10.2139/ssrn.1418687
Lipper, G. (2007) Is Valuation a Key Issue in Funding Startups? Kauffman eVenturing. 
Payne, W. H. (2007) Fundability and Valuation of Startups: An Angel's Perspective. 
Ewing Marion Kauffman Foundation. 
Payne, W. H. (2007) Valuation of Pre-revenue Companies: The Venture Capital 
Method. 
Ewing Marion Kauffman Foundation.
Villalobos, L. (2007) Valuation Divergence. Kauffman eVenturing. 
Villalobos, L. (2007). Investment Valuations of Seed and Early-Stage Ventures. 
Kauffman eVenturing. 
Villalobos, L. Payne, W. H. (2007) Startup Pre-money Valuation: The Keystone to 
Return on Investment. Kauffman eVenturing. 
34 | 2018 Early Metrics. All rights reserved. 
Acknowledgements
We would like to extend a special thank you to our distribution partner Bpifrance 
Le Hub for their involvement and continued support as well as to Ccile Brosset, 
Director of Bpifrance Le Hub, for sharing her point of view. Bpifrance Le Hub aims 
to boost French innovation by multiplying deals between corporates and startups 
(partnerships, investments or M&A) in the tech industry. Since its launch in April 2015, 
it has accelerated 86 startups, accompanied 80 corporates and intermediated 165 
commercial partnerships. It is part of the French public investment bank Bpifrance. 
We are also very grateful  to Samantha Jrusalmy, Partner at Elaia Partners, and 
Sylvain Tillon, CEO at Tilkee, for participating in our interviews and providing 
invaluable insights for this research. Thank you also to Andrs Rothschild, Manager at 
Accuracy, for his support.
Lastly, we would like to thank the team members at Early Metrics who made the 
production of this white paper possible: Antoine Baschiera, CEO and co-founder; 
Sebastien Paillet, CEO and co-founder; Edouard Thibaut, Head of Methodology; 
David Rhenals, Data Scientist; Elia Pradel, Ecosystem Manager France; Anthony 
Hallett, English Editor. 
| 35
About Early Metrics
Early Metrics is the international rating agency for startups and innovative SMEs. We 
provide corporates and investors with qualitative and financial insights to decide 
which ventures to partner with or invest in. Our scientific methodology focuses on 
qualitative KPIs to reliably assess the growth potential of any tech startup or scale-
up. With offices in London, Paris, Berlin and Tel Aviv as well as a database of 2000+ 
rated startups, Early Metrics provides its Fortune 500 clients and investors with 
transparent and independent knowledge into the most dynamic startup ecosystems. 
Startups also benefit from being rated by Early Metrics as they freely receive a rating 
certificate and feedback from expert analysts. 
Early Metrics is the bridge between the most forward-thinking decision makers and 
the most innovative newcomers.
Contacts
Martin Londe, Manager of Models and Financial Ratings
martin@earlymetrics.com
Anais Masetti, Research and Content Producer
anais@earlymetrics.com