Asking users for solutions yields incremental ideas like "faster horses." Instead, ask them to tell detailed stories about their workflow. This narrative approach uncovers the true context, pain points, and decision journeys that direct questions miss, leading to breakthrough insights about the actual problem to be solved.

Instead of asking direct questions like 'what's important?', prompt customers to recount specific, recent experiences. This storytelling method bypasses generic answers, reveals the 'why' behind their actions, and provides powerful narratives for persuading internal stakeholders.

Anthropic developed an AI tool that conducts automated, adaptive interviews to gather qualitative user feedback. This moves beyond analyzing chat logs to understanding user feelings and experiences, unlocking scalable, in-depth market research, customer success, and even HR applications that were previously impossible.

While AI handles quantitative analysis, its greatest strength is synthesizing unstructured qualitative data like open-ended survey responses. It excels at coding and theming this feedback, automating a process that was historically a painful manual bottleneck for researchers and analysts.

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.

The traditional SaaS method of asking customers what they want doesn't work for AI because customers can't imagine what's possible with the technology's "jagged" capabilities. Instead, teams must start with a deep, technology-first understanding of the models and then map that back to customer problems.

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.

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.

The AI user research platform Listen discovered a key psychological advantage: people are less filtered and more truthful when speaking with an AI. This tendency to be more honest with a non-human interviewer allows companies to gather more authentic feedback that is more predictive of actual future customer behavior.