Ramp built an AI agent that sifts through Gong recordings, Salesforce notes, support tickets, and chats to answer any product question. This automates the work of an entire team, turning days of research into an eight-minute query to identify key customer pain points and roadmap priorities.

Instead of using restrictive surveys, companies can find breakthrough innovations by using AI to analyze unstructured customer stories. Asking open-ended questions like 'Tell me about your experience' allows AI to identify latent needs and emotions that surveys completely miss.

Instead of manually sifting through overwhelming survey responses, input the raw data into an AI model. You can prompt it to identify distinct customer segments and generate detailed avatars—complete with pain points and desires—for each of your specific offers.

Expensive user research often sits unused in documents. By ingesting this static data, you can create interactive AI chatbot personas. This allows product and marketing teams to "talk to" their customers in real-time to test ad copy, features, and messaging, making research continuously actionable.

Go beyond simple prospect research and use AI to track broad market sentiment. By analyzing vast amounts of web data, AI can identify what an entire audience is looking for and bothered by right now, revealing emerging pain points and allowing for more timely and relevant outreach.

The PM role is shifting to that of a 'product builder.' Instead of manually sifting through data, they can use AI agents to scrape sources like Gong, Slack, and Intercom. This provides an aggregated 'voice of the customer' and a data-backed strategy in minutes, not weeks.

The most reliable customer insights will soon come from interviewing AI models trained on vast customer datasets. This is because AI can synthesize collective knowledge, while individual customers are often poor at articulating their true needs or answering questions effectively.

Instead of manual survey design, provide an AI with a list of hypotheses and context documents. It can generate a complete questionnaire, the platform-specific code file for deployment (e.g., for Qualtrics), and an analysis plan, compressing the user research setup process from days to minutes.

AI's primary value in Voice of the Customer (VOC) work is not just analyzing new information. It's about extracting deeper, faster, and cheaper insights from the vast reserves of customer data companies already possess, much like fracking unlocks more oil from existing wells.