Enterpret, a new company in the customer insights and feedback segment has launched, buoyed by a $4.3 million seed round led by Kleiner Perkins, with participation from Sequoia Capital India, Unusual Ventures, and angel investors. With offices in San Francisco, California and Bengaluru, Karnataka, India, Enterpret is focused on taking the rapidly increasing amounts of data coming in from multiple channels and using natural language processing (NLP), machine learning (ML), analytics, and data visualization to “continuously learn about our customer’s most critical pain points and solve them.”

Enterpret launched in beta about 8 months ago and early adopters include Notion, Cameo, InVideo and Loom. According to Varun Sharma, Enterpret’s co-founder, “The number of channels that companies interact with customers has expanded to include apps, social media, in-app chat services, and the new hot thing of community like Discord and Slack. The people building the products want to know what people like and don’t like, get the curated feedback, but never actually learn from customer feedback. That’s very hard to quantify because it is not a direct query or feedback.”

The company’s engine behind its analytics leverages a proprietary unsupervised ML approach, which allows the company to dynamically update any customer feedback schema from raw text. Use cases identified by Enterpret include:

• Prioritizing product roadmaps
• Answering the “why” behind the “what”
• Iterate quickly after product launches
• Validate hypotheses for growth experiments
• Respond to product quality issues faster

Enterpret is entering a sweet spot in the customer insights and feedback space, with Dash Research identifying the move to digital and the resultant number of channels and feedback sources as a main driver in the adoption of these CX technologies. The digital transformation was occurring even before COVID-19, but the pandemic layered more urgency onto this transition, as more consumers used digital channels with higher frequency than ever before. Shopping behaviors were altered, as face-to-face interactions became less common. People increasingly researched, shopped, and communicated on the web, mobile, or other digital channels. Additionally, the support channel types customers access have grown and the number of technologies used to offer unsolicited feedback or respond to requested feedback have also exploded. Solutions that help companies parse through the data needed to feed into strong CX programs are critical.