This ex-Scale AI leader built a platform to automatically extracts insights from customer feedback
Summary
Conveniently, Arnav had software engineering experience, having worked as a developer at Uber for three years.Customer interactions are a precious, yet immensely underutilized, dataset for all enterprises, Varun told TechCrunch. If theyre unlocked meaningfully, they can build best-in-class products and drive business growth.Over the years, Varun and Arnavs tool expanded into a platform called Enterpret that connects to various feedback sources and applies algorithms to extract insights. Enterpret can highlight overarching themes and emerging problems in customer comments, and assist teams in figuring out things such as what products to build.Enterpret is able to pull in all customer interactions of a company in real time, like sales calls, support tickets, survey responses, X threads, and app reviews; give them a quantifiable structure; and then join the output with product usage and revenue data of the company to operationalize decision-making, Varun said.Companies can define rules to scrub scraped data of personally identifiable information, including IP addresses and names. Another rival, Zendesk-owned Klaus, automatically categorizes and scores customer interactions.San Francisco-based Enterprets strategy seems to be working well, though or at least, well enough to double the startups annual recurring revenue (ARR) between May and now. Enterprets raised a total of $25 million to date.Enterprets ambitious vision is rooted in the realization that customer feedback is the most valuable dataset of any company, Varun said.