Product-market fit is often described as a feeling — a moment when things click. But before the feeling, there is data: who is actually using your product, how, and for what job. The persona in your acquisition deck describes who you expected to acquire. The transaction data, session analysis, and cohort retention describe who is staying.
When those two pictures diverge — and they frequently do — PMs face a choice. They can suppress the divergence to protect the go-to-market narrative, the fundraising story, or the founding mission. Or they can bring the real user into the room and let it force the strategy conversation that is already overdue.
The exercises on this page are about recognizing that divergence and acting on it. The data patterns are different in each case — order timing, remittance behavior, cohort retention, KYC device signals — but the judgment is the same: the user who is generating revenue is not always the user in the deck, and the product that works for the real user is not always the product you set out to build.
You're a PM at Dunzo. Your 'small office supplies' category deck describes the user as 'operations manager at an SMB office, 9-5 Monday-Friday, ordering stationery and cleaning supplies.' You pull transaction data for the 'office supplies' category and find 38% of orders arrive between 10pm and 2am, and the most common items are disposable cups, garbage bags, and hand wash in bulk — not stationery. Delivery addresses cluster around PG accommodations and co-living spaces in Koramangala and Bandra.
Your task: At Monday's category review, do you re-pitch the category around the actual nighttime-household user, or finish the office-supplies roadmap in flight and revisit the persona after a dedicated research sprint?
your reasoning:
You're a PM at Niyo, the forex and travel banking app. The product deck targets 'young solo travelers, 24-32, going to Europe/US for the first time.' You run a transaction analysis on active accounts from the past 90 days. The top use case by volume isn't hotel payments or flight purchases — it's recurring small transfers of ₹5,000-15,000 to Indian bank accounts. Cross-referencing with KYC data, 42% of your high-frequency users are NRI professionals in the 32-45 bracket who are using Niyo to send money back to family, not to spend abroad.
Your task: At the next roadmap session, do you re-frame the product strategy around the NRI remittance use case, or stay with the solo-traveler persona since that's the go-to-market story that drove fundraising?
your reasoning:
You're a PM at Digit Insurance. The acquisition deck targets 'first-time digital insurance buyers, 24-34, buying motor cover for the first time.' You analyze the last 90 days of new policy purchases. 48% of 'new' customers flag a previous insurer in the KYC flow — they're renewal migrants from LIC, IFFCO Tokio, or HDFC Ergo, not first-time buyers. Their behavior is entirely different: they skip the explainer screens, go directly to premium comparison, and churn at 2x the rate in year 2 if the renewal pricing isn't within 8% of what they paid at their prior insurer.
Your task: At the next product review, do you re-frame onboarding and retention strategy around the renewal-migrant user, or keep first-timer as the anchor persona since that's the acquisition story?
your reasoning:
You're a PM at BharatMatrimony. The product team optimizes the profile creation and match-browsing flows for 'the person seeking a match, 25-32, tech-comfortable, making their own decisions.' You run a session analysis on profile creation for a sample of 500 recently created profiles. In 61% of cases, the device used to create the profile is more than 10 years older than the listed age of the profile-holder, and the browsing session that follows creation happens only during daytime weekday hours — a pattern inconsistent with a working-age user browsing for themselves.
Your task: At the next product review, do you re-pitch the profile and browsing experience around the parent-as-proxy user, or continue optimizing for the profile-holder as the assumed user?
your reasoning:
Where to go next
- Build the research methods that surface user truth earlier: User Research Methods
- Create personas that reflect real user segments: User Personas
- Understand the job-to-be-done behind the behavior: Jobs to Be Done
- Apply these insights to UX decisions: UX Principles