This ex-Scale AI leader built a platform to automatically extracts insights from customer feedback

In this hyperconnected world we live in, it’s easier than ever to send feedback to the companies we patronize. But just because businesses offer more ways to get in touch doesn’t mean they’re poring over every comment. According to a 2020 survey from Productboard, 90% of companies fail to successfully capture feedback from all channels while a third have no feedback-capturing process whatsoever.

Varun Sharma became very aware of this while leading customer success efforts at LinkedIn, analytics software firm Amplitude, and startup Scale AI. Product and customer experience teams were struggling to use customer feedback to make decisions despite their best efforts, Sharma says.

So, in 2020, Sharma recruited his brother, Arnav Sharma, to build a tool that might help solve the customer feedback headaches firms were experiencing. 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 they’re unlocked meaningfully, they can build best-in-class products and drive business growth.”

Over the years, Varun and Arnav’s 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. Varun says that, to comply with GDPR, Enterpret doesn’t maintain control over customers’ data.

Varun added that customers like Canva and Monday.com are also using Enterpret, which has analyzed millions of pieces of customer feedback to date, to detect early signs of churn and validate — or disprove, as the case may be — product hypotheses.

Enterpret isn’t without competitors in the space, like ScopeAI, acquired by Observe.AI in 2021 for its technology that helps companies analyze customer feedback. Another rival, Zendesk-owned Klaus, automatically categorizes and scores customer interactions.

San Francisco-based Enterpret’s strategy seems to be working well, though — or at least, well enough to double the startup’s annual recurring revenue (ARR) between May and now. Varun says that Enterpret’s contract value has doubled over the past 12 months, and the company recently closed a $20.8 million Series A round.

“Our ARR is in the seven figures,” Varun added. “The momentum is strong. We decided to raise capital to support the growth.”

The near-term plan is to put the cash from the Series A, which was led by Canaan Partners with participation from Kleiner Perkins, Peak XV Partners, Wing Ventures, and Recall Capital, on hiring and product R&D, Varun says. Enterpret’s raised a total of $25 million to date.

“Enterpret’s ambitious vision is rooted in the realization that customer feedback is the most valuable dataset of any company,” Varun said. “Our mission is to build the platform for all companies that aspire to be customer-centric.”