To improve your agents’ performance, you need to review the calls your contact center receives. Turn to a company that uses AI-enabled voice analytics coupled with human review to ensure accuracy. Learn more at https://callcriteria.com.
Sign Up For High Precision AI Enabled Voice
Analytics For Contact Center QA
Anyone managing a contact center would know that manual review
of all calls is virtually impossible. Here is where AI technology
Call Criteria offers AI-enabled voice analytics for
businesses looking to improve the efficiency of their
call center operations.
The company based in Los Angeles, California
complements artificial intelligence with human reviews
to ensure high levels of accuracy.
Through voice analytics, Call Criteria
presents a viable, more economical
alternative to integrating the latest QA
technologies or hiring and maintaining an
internal QA team.
The technology allows you to sift
through large volumes of calls within a
short period of time and subject calls
that meet predefined criteria through
As Call Criteria's CEO Ryan Stomel explains, "The best way to ensure the
highest accuracy in call center analytics is by fusing human analysts and voice
analytics to review agent-customer interactions."
He continues, "With the use of voice-to-text
technology, companies are pulling the calls
that have various keywords stated in the
recording to identify the right calls to review
with human QA analysts.”
To keep accuracy high and make sure that all
steps are working as expected, continuous
improvements to the automated system are
essential. The company employs AI predictive
modeling to achieve this.
The process starts as usual with transcribing the calls using the company’s speech-to-text
algorithms. The system then proceeds with analyzing the transcripts and flagging keywords that you
defined. Time stamps are also added to facilitate easy review of the segments that have been
Human review follows. Depending on the need, the
analysts may review the specific keyword segment or
conduct a more thorough evaluation of the calls with the
goal of generating more accurate results. Finally, the
model is retrained using the results of the human review as
basis for the adjustments.
Specializing in quality assur