Previously, conducting large-scale surveys via expert calls was cost-prohibitive. AI-led interviewers remove human time constraints and dramatically lower costs, enabling investors to gather real-time market sentiment from hundreds of sources simultaneously.
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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.
M&A Science's "intelligence hub" differentiates from generalist AI like ChatGPT by grounding answers in a closed ecosystem of 400+ expert interviews. It provides sourced, experiential intelligence rather than generic internet-scraped guesses, making it a reliable tool for high-stakes professional work.
While summarization is useful, AI's unique power is creating a massive grid comparing perspectives from management, sell-side analysts, and expert calls on key business drivers. This helps investors quickly identify the most critical debates for deeper research.
The company developed an AI that conducts highly technical expert network interviews, automating a high-friction manual process. This enables new, scalable content creation like monthly channel checks across dozens of industries—a task too repetitive for human analysts to perform consistently at scale.
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 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.
While a query on an advanced AI agent like Manus might cost $5-20, which is high for AI, it provides insights that would traditionally cost thousands in market research fees. This dramatically changes the ROI calculation for marketing intelligence, making it broadly accessible.
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.
