rew Miller

For Conveo · Senior Product Engineer, NYC

Conveo’s next chapter: turn every reader into the next study

Why now, the four bets I’d test, and the loop they build.

Paste it into your AI agent to judge these ideas yourself.

The move: turn the people who read Conveo’s research into the source of its next studies. Readers ask, some questions are answered from past research, real gaps are grouped and ranked by the decision each blocks, the researcher decides, and the answer goes back to everyone who asked. It makes money because questions are already billable usage, gaps become studies, and more people get more reasons to renew.

Why now: a study gets bought when someone knows the question is worth paying for. One insights team on a podcast got 55 requests with room for 15; shared reports began inviting reader questions on Sep 19; speed and cost are becoming table stakes. What has to be true: readers ask real questions the research can’t answer yet, the researcher finds some of them worth a study, and those studies are new or better work, not just a reshuffle.

Bet 1, the lead: let every shared report suggest the next study. An agent answers reader questions from past research, collects the real gaps, and drafts a study for the researcher to approve. First step: ship it on one account’s shared reports, with the researcher approving every draft, then four accounts. It works if two accounts commit budget and a date to a study that began as their readers’ questions.

Three bets that make the loop stronger: shared studies with buyers, answers that hold up in AI assistants, and showing what changed because of the research. Each has a first step and a reason to drop it.

The big picture: if it works, every study brings in the readers who ask for the next one. A flywheel: reports get shared, readers ask and get answers with sources, gaps become studies the researcher approves, and askers hear that their question started a study. The growth experiments, and how we would know: readers ask more when answers come fast (typed questions per report grow monthly); hearing their question started a study brings people back (askers ask again within 30 days); researchers approve gaps that block a real decision (more, or better, studies per account).

About me: I'm a product engineer who takes products from should-this-exist to production, with AI in the loop at every step.