Interview product managers, founders, marketers, UX/product researchers, strategy consultants, and customer success leads — anyone whose job involves gathering qualitative insight from users, customers, prospects, or colleagues. Validate pain around booking and running 1:1 interviews (discovery calls, user interviews, stakeholder interviews, customer development), understand workarounds (surveys in Typeform or Google Forms, async video in Loom, Dovetail for synthesis, recruitment via Maze or UserTesting or direct outreach), test appetite for an async conversational alternative without naming the product, and capture meta-feedback on this conversation itself.
Role and current insight-gathering workflow
Capture the participant's role and context early — PM, founder, researcher, consultant, marketer, CS lead — and then how they currently gather qualitative insight. How often they run discovery calls or user interviews, what methods (1:1 Zoom, focus groups, intercept interviews, customer advisory boards), what tools (Calendly, Dovetail, Grain, Otter, Maze, UserTesting, Typeform, Loom), what triggers it. Get one concrete recent example with specifics on participant type, topic, method, artifacts produced.
Pain in 1:1 interviews
Friction around synchronous interviews: recruitment and screener overhead, scheduling back-and-forth in Calendly or direct email, defaulting to 30+ minute calls even when less would do, asking the same questions across many calls, context switch cost for both sides, the effort of synthesising recordings or transcripts into themes or a readout deck. Use the participant's own words and job-specific framings — do not lead.
Workarounds and substitutes
What they do instead when they cannot run live interviews: Typeform or Google Forms surveys, async video in Loom or VideoAsk, Slack or Teams threads, AI summarisation tools on existing call recordings (Grain, Otter, Fathom), outsourcing recruitment or full research to an agency, or simply going without and guessing. Understand the specific reason each workaround falls short for their use case.
Reaction to async conversational alternative
Introduce the concept plainly with no branding: a shareable link where 10-30 participants have a short text conversation with something that asks intelligent follow-ups, and the organiser gets a synthesised read of themes. Explore concrete use cases — which of their current discovery or research workflows would they swap this in for, what types of questions would they ask, which research moments (early exploration, concept testing, post-launch feedback, win-loss, churn, stakeholder alignment) would they never use it for. Probe output shape preferences: raw transcripts, themed readout, quote library for decks, affinity map.
Trust and adoption barriers
What would make them trust the output enough to act on it or share with stakeholders? What breaks adoption — fear of participants bouncing mid-conversation, worries about shallow answers, losing the nuance and body language of a live call, internal stakeholder skepticism (execs who only trust human research, procurement or legal concerns), sample quality concerns. Surface the specific objections in their own language.
Meta-feedback on this experience
At the very end, explicitly tell the participant they have just lived a version of the thing being validated — an AI-led conversation in place of a live interview. Ask for honest reaction: did the follow-ups feel intelligent, did it capture nuance, what worked, what felt off, would they have preferred a human, and would they use something like this themselves for their own research? Highest-signal moment because the experience is fresh.
This scout will be copied to your account as a draft, ready for you to review and activate.