AI Customer Interview Analyzer
Build an AI customer interview analyzer for founders that transcribes calls, extracts pain points, clusters themes, and ranks what to build next. Full guide with AI prompts.
Talking to customers is the one piece of advice every founder hears and the one workflow no tool actually serves. A solo founder or small product team runs five user calls, ends up with five hours of recordings, a messy Notion doc, and a vague feeling about what to build next. The synthesis — pulling out the real pain points, the repeated feature requests, the objections that killed a deal — happens in their head, at midnight, and most of it evaporates by the next sprint.
Built for Solo Founders, Developers.
The UX research software market is projected to grow from USD 520.1M in 2026 to USD 1,247.6M by 2034, a ~11.6% CAGR (Fortune Business Insights via OpenPR).
Suggested stack: Next.js + Vercel, AssemblyAI or Whisper, Claude (extraction + clustering), Supabase (Postgres + pgvector + Auth), Inngest, Stripe Billing. Weekend scope: about 12 hours.
The Problem
Synthesis is the bottleneck, not collection. Recording a call is easy; turning ten calls into a prioritized decision is the part that doesn't scale for a solo operator.
The Solution
An AI customer interview analyzer built for founders, not research departments. Drop in a call recording or transcript and it does the work a researcher would: transcribes, tags…
Market Research
The UX research software market is projected to grow from USD 520.1M in 2026 to USD 1,247.6M by 2034, a ~11.6% CAGR (Fortune Business Insights via OpenPR).
Competitive Landscape
Dovetail — The category leader and research repository standard. Powerful tagging, highlights, and insights, but built for research teams: Professional starts around $29/user/mo…
Business Model
Free ($0) — 3 interviews/month, transcription + basic theme tagging. Enough to feel the magic and seed word-of-mouth.
Recommended Tech Stack
Next.js + Vercel — Dashboard, upload flow, and server actions for the analysis pipeline. Fast to ship, cheap at small scale.
AI Prompts to Build This
Copy these build prompts into Claude, Cursor, or your AI coding tool. Create a free account to unlock the full research behind them.
1. Project Setup
Create a Next.js (App Router) app called "AI Customer Interview Analyzer". Set up: - Supabase auth + Postgres schema for: users, workspaces, interviews, transcripts, insights (with type: pain_point | feature_request | objection), themes, usage_events - An upload flow that accepts audio/video files and transcript text - Dashboard routes: Upload, Interview Detail, Insights (themes view), Settings - A landing page aimed at founders: "Turn customer calls into a prioritized roadmap" with an upload CTA Use TypeScript, server actions, and environment variables for all API keys.
2. Core Feature — Transcribe, Extract, Cluster
Build the analysis pipeline: 1. On upload, send the file to AssemblyAI for speaker-diarized transcription. 2. Send the transcript to Claude with a structured prompt that returns JSON: an array of insights, each with { type, quote (verbatim), summary, confidence }. Types: pain_point, feature_request, objection. 3. Embed each insight and store it in Postgres (pgvector). 4. Cluster insights across ALL interviews in the workspace by semantic similarity, and produce a ranked report: themes ordered by how many distinct interviews mention them, each with its top 3 verbatim quotes. Keep extraction deterministic by giving Claude a fixed taxonomy and examples.3. Insight Report + Export
Add a prioritized insight report for AI Customer Interview Analyzer: - A "What to build next" view that ranks themes by interview frequency and recency, with a one-line rationale and supporting quotes for each. - One-click export of any theme to Markdown formatted for a PRD or Notion doc, including the verbatim customer quotes. - A weekly digest that surfaces new themes detected since last week and pushes them to Slack or Linear. Gate cross-interview clustering and exports behind the Founder and Team tiers.