Rehearse the interview. Then read the room live.

Sample answer from the fictional profileMerchant onboarding. When I took it over, onboarding took nine days on average and 40% of merchants who started never finished. Sales blamed the form, compliance blamed missing documents, and nobody had the numbers. I instrumented every step and found 60% of the drop-off was at document upload, mostly on mobile. So we split the flow: merchants could start selling with a limited account while documents were checked in the background. Onboarding went from nine days to two, drop-off from 40% to 18%, and that came to about 3,000 extra active merchants a quarter.

Sample answer from the fictional profileCompliance wanted every new merchant fully verified before a single transaction. Sales wanted instant activation. While it stayed stuck, we were losing about a third of sign-ups in the waiting period. Both were right about their own number. Compliance is measured on fraud losses, sales on activations. Before pushing, I pulled the data: 92% of fraud came from merchants above a certain monthly volume. So I changed the question from "verify first or activate first?" to "how much can an unverified merchant safely do?" We put a transaction cap on unverified accounts instead of a full block. Compliance owned the cap number, so it stayed their decision. Fraud losses stayed flat, activations went up 25%, and we wrote the cap into policy so the argument never came back.

Sample answer from the fictional profile, opening onlyTwo questions first. Did the drop start on a date, or has that region always been low? And is conversion measured the same way there, same funnel, same definition? If you don't have those, I'll assume it's a step change in the last few weeks. Then the causes I'd want on the table before testing any of them: a release that only hit that region, a payment method that stopped working, a pricing or tax change, a tracking break, a traffic-source shift, or a local competitor move. While we work through those, I'd contain it: pause any experiment running in that region, and put the region on a daily check so we see the moment it recovers…

Sample answer from the fictional profileThe main thing for me is to find out whether it's real before anyone starts fixing. I'd want to know if it started on one day or drifted across the week, and whether it's every country or one. First I'd check that tracking didn't break, because a step change on one day is very often a release. Then I'd cut the numbers by platform, country, and traffic source to see where the drop lives. After that I'd look at what shipped that week and roll back the most likely change while we confirm. This is basically what we did when onboarding drop-off jumped after a form change.