Product Manager
Product analytics questions
212 questions on Product analytics for product managers, easiest first.
Easy 62
- North Star metriceasy
- Spot the vanity metriceasy
- Calculating conversion rateeasy
- Calculating churneasy
- DAU/MAU stickinesseasy
- The AARRR funneleasy
- What activation meanseasy
- Leading and lagging indicatorseasy
- Customer segmentseasy
- Calculating NPSeasy
- Gross revenue retentioneasy
- From churn to retentioneasy
- Events and propertieseasy
- User property or event propertyeasy
- Why write a tracking planeasy
- Users or eventseasy
- Conversion window in a funneleasy
- What a cohort iseasy
- Behavioural cohorteasy
- What Day 7 retention measureseasy
- Unbounded retentioneasy
- Weekly active userseasy
- Feature adoption rateeasy
- Time to valueeasy
- Frequency and depth of useeasy
- Why add qualitative researcheasy
- The leaky bucketeasy
- Behavioural segmentationeasy
- What RFM stands foreasy
- Power userseasy
- Event-based analyticseasy
- Dashboard or ad-hoc analysiseasy
- Keeping a metric dictionaryeasy
- The denominator of a rateeasy
- Points or percenteasy
- A small segment grows fasteasy
- When to use a heatmapeasy
- Watching session replayseasy
- Rows and columns in a cohort charteasy
- Retention and churneasy
- An engagement scoreeasy
- Path analysiseasy
- A product health dashboardeasy
- Product analytics tool or BI tooleasy
- How GA4 records dataeasy
- What UTM tags are foreasy
- When a free user has churnedeasy
- Customer health scoreeasy
- Onboarding completion rateeasy
- Requests versus usage dataeasy
- How fresh is the dataeasy
- Personal data in eventseasy
- Free-to-paid conversioneasy
- Trial-to-paid rateeasy
- Engagement and retentioneasy
- Typical session lengtheasy
- Working out NPSeasy
- The "very disappointed" testeasy
- The "aha" momenteasy
- Leading or laggingeasy
- Input metricseasy
- An ideal customer profileeasy
Medium 80
- Growing users, falling retentionmedium
- Defining success before launchmedium
- Reading retention curvesmedium
- Finding the leakiest funnel stepmedium
- Guardrail metricsmedium
- Writing a key resultmedium
- Working out GRRmedium
- Step conversion in a funnelmedium
- Two retention numbers for one cohortmedium
- Changing the conversion windowmedium
- Working out adoptionmedium
- Anonymous and logged-in usersmedium
- Where to track purchasesmedium
- Naming eventsmedium
- When a session endsmedium
- Average time to convertmedium
- Reading a power user curvemedium
- Newer cohorts retain worsemedium
- Resurrected usersmedium
- A drop in checkout conversionmedium
- A tiny cohort looks amazingmedium
- The friend-count magic numbermedium
- What a bounce ismedium
- Retention for a tax appmedium
- Do users come back to a featuremedium
- Events jump but users do notmedium
- Sampled reportsmedium
- A DAU query bugmedium
- Joining for retained usersmedium
- First purchase per usermedium
- Order of steps in SQLmedium
- Reading RFM scoresmedium
- Average of segment ratesmedium
- ARPU and ARPPUmedium
- Retention by acquisition channelmedium
- Uses per user is skewedmedium
- Segments that add up wrongmedium
- Engagement in a B2B toolmedium
- Account or user levelmedium
- Which cohort start datemedium
- Click-through ratemedium
- Counting by local daymedium
- Adding up daily activesmedium
- Clustering usersmedium
- Where most users are lostmedium
- A property with too many valuesmedium
- Days between orders with LAGmedium
- Customers lost or revenue lostmedium
- Expansion revenuemedium
- A revenue cohort above 100%medium
- Mobile converts lowermedium
- Is 20% retention goodmedium
- An early churn signal in B2Bmedium
- Who is active in a payments appmedium
- Product-qualified leadsmedium
- This month's trials look worsemedium
- Time to first invoicemedium
- Did the win-back email workmedium
- Who answers the NPS surveymedium
- Breaking down revenuemedium
- Two levers move at oncemedium
- Averaging retention across cohortsmedium
- Right usage frequencymedium
- Is this drop unusualmedium
- Testing tracking before releasemedium
- Notes on a dashboard chartmedium
- Choosing a funnel window from datamedium
- NPS from raw countsmedium
- Scoring a SUS questionnairemedium
- Defining activationmedium
- Where the funnel leaks mostmedium
- Overall retention hides progressmedium
- Using session recordingsmedium
- Searches that find nothingmedium
- Breaking a north star into driversmedium
- Health metrics alongside OKRsmedium
- Deciding what launch success meansmedium
- Measuring adoption in B2Bmedium
- A good feature no one findsmedium
- Horizontal or vertical SaaSmedium
Hard 70
- Choosing a metric for saved searcheshard
- Do the wins add uphard
- When a target stops workinghard
- From monthly to annual churnhard
- Growth accountinghard
- A suspicious jump in active usershard
- More notifications, more usershard
- Monthly plan or discounted annualhard
- Fast sales, leaky basehard
- Churn that depends on tenurehard
- Strong NRR, weak GRRhard
- Kano results split by segmenthard
- Calendar weeks in a retention charthard
- Steps done in a different orderhard
- Every segment up, total downhard
- A retention curve that flattenshard
- Empty cells in a cohort tablehard
- Users who skip a funnel stephard
- Top of funnel jumps, signups flathard
- Dubai and India daily countshard
- Working out net revenue retentionhard
- Working out gross revenue retentionhard
- A renamed property breaks reportshard
- Measuring churn with censored usershard
- Low users bounce back on their ownhard
- Engagement spike after a redesignhard
- An onboarding checklist on desktop onlyhard
- A filter that breaks a left joinhard
- A winning segment found by searchinghard
- Two ways to average conversionhard
- Measuring notifications properlyhard
- One feature takes from anotherhard
- A simple lifetime valuehard
- Payback on acquisition costhard
- Approximate distinct countshard
- Yesterday's DAU keeps risinghard
- Off-by-one in day countshard
- Reading p90hard
- A metric that moves fast enoughhard
- A launch in one country onlyhard
- Before and after a launchhard
- Averages that mislead about peoplehard
- A B2B funnel with many buyershard
- A feature few users reachhard
- Does the health score workhard
- A churn model that is too goodhard
- Five CSMs and a churn listhard
- A feature looks unused on Androidhard
- What a retention lift is worthhard
- Retention falls with no product changehard
- Two systems, two DAU numbershard
- Impressions that were never seenhard
- Comparing monthly and annual planshard
- Strong NRR, many customers leavinghard
- A few users do most of the activityhard
- One person on three deviceshard
- Up overall, down in every grouphard
- A before-and-after during Ramadanhard
- Watching what else could breakhard
- Forcing the activation actionhard
- An "average" personahard
- Choosing the wrong outcomehard
- Two segments, one roadmap slothard
- SMB or enterprise, not bothhard
- Two teams, clashing goalshard
- Picking the first segment to winhard
- Key results met, objective missedhard
- Many try it, few come backhard
- When a different segment loves ithard
- Did the feature drive revenue?hard