Diagnose a retention problem

Leo — I wouldn’t double paid acquisition yet. We have a retention leak, not just a summer growth slowdown. More new users and campaign-driven returns are masking deteriorating retention. The clearest break coincides with the week-5 onboarding change, though we need an experiment to establish causality.

What’s actually happening

Weekly actives remain around 52,000 because inflows are replacing increasingly large losses:

New users rose 30%, but weekly churn rose 44%. The share of the prior week’s actives retained fell from approximately 86.3% to 80.2%. In week 13, 10,482 new and returning users barely exceeded 10,279 churned users: net growth was just 203.

Flat actives are therefore concealing a less durable user base.

The evidence points to an activation problem

1. New cohorts look better initially, then retain substantially worse. For signup cohorts 1–4, first-following-week retention averaged 55.1%; for cohorts 5–12, it averaged 58.0%. But by the fourth following week, retention falls from 33.8% for cohorts 1–4 to 24.8% for cohorts 5–9. At eight weeks, the earlier cohorts retain roughly 30%, versus 19.9% for cohort 5.

That is not simply fewer people trying Stride. More are getting through the front door, but fewer form a lasting habit.

2. The break aligns with removing goal-setting in week 5. Shorter signup raised completion from 61% to 74%, but removed the step asking users what they wanted to achieve and how often they would exercise. For a habit app built around a weekly plan, that step may have helped users commit to a relevant routine.

The timing makes this our leading hypothesis—not proven causality. We should also check acquisition mix and other changes. However, the paid-budget increase occurred in week 9, after the cohort deterioration began. “Summer” alone does not explain this sharp onboarding-aligned break.

3. Win-back is propping up the headline metric, not repairing retention. Returning users jumped from about 1,000 to 2,600 a week when emails launched in week 6. Yet only 12% of email-driven returners remained active two weeks later, versus 41% of earlier organic returners. These are different populations, so this is not a causal campaign comparison, but it clearly warns against treating every return as durable recovery.

What we should do before spending more

1. Hold acquisition spend steady while testing onboarding. Randomize the current short signup against a lightweight goal-setting step that produces a personalized weekly plan. Preserve the speed improvement where possible.

1. Optimize for durable activation, not signup completion. Make four-week retention a primary outcome, alongside first workout, plan adoption and repeat workout behavior. Measure retained users per signup and per signup starter so a longer flow cannot “win” merely by filtering people out. Track Premium conversion as a guardrail.

1. Locate the failure point. Segment cohorts by acquisition channel, campaign and onboarding exposure. Compare where users stop: before their first workout, after one workout, or when beginning the next weekly plan. Reconcile the signup and new-active counts before calculating acquisition efficiency.

1. Judge win-back on incremental lasting activity. Use a randomized holdout and measure two- and four-week retention, not email-driven returns alone. Test messages that restore a realistic plan rather than relying only on free Premium.

Decision: scale acquisition once we demonstrate improved multiweek retention and acceptable acquisition economics. Doubling spend now risks buying more users into a leaking habit loop—and making flat actives look healthier without fixing the underlying problem.

To: Leo, Head of Growth From: PM, Activation Subject: Diagnosis: Why WAU is flat (and why doubling paid acquisition right now will burn cash)

Leo, you suggested doubling paid acquisition to push through flat summer WAU. I’ve dug into the numbers, and the data tells a different story.

Weekly actives are flat (averaging ~52,000 for 13 weeks), but sign-ups are up 30% (from ~6,000 to ~7,800). The issue isn't seasonal churn—it's that our onboarding changes broke cohort retention, and our win-back campaigns are masking the leak.

Doubling down on paid acquisition right now will just pour more water into a bucket with a widening hole. Here is the diagnosis, the evidence, and what we should do instead.

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1. What’s actually happening?

#### A. Onboarding optimization created low-intent users (Week 5) In Week 5, we removed the goal-setting step to cut sign-up time from 3 minutes to 1. Completion jumped from 61% to 74%, and sign-ups grew.

However, look at the cohort data (`weeklysignupcohorts.csv`). For Cohorts 1–4 (pre-change), Week 1 retention hovered around 55%, and Week 4 retention was ~34%. From Cohort 5 onward, Week 1 retention jumped to ~58% (thanks to frictionless sign-up), but Week 4 retention cratered from ~34% down to ~25%.

By removing goal-setting, we optimized for top-of-funnel conversion at the expense of user intent. We are acquiring users who don't know why they are here or what plan fits them, leading them to drop off heavily by week 4.

#### B. Core retention is quietly declining Look at the growth accounting data (`weeklygrowthaccounting.csv`). Total `retained_users` (users active week-over-week) dropped steadily from ~44,800 in Week 1 to ~41,600 in Week 13, a loss of over 3,200 loyal weekly actives.

#### C. Win-backs are masking the bleeding So why is WAU flat if retained users dropped by 3,200? Look at `returning_users`. From Weeks 1–5, returning users averaged ~980 per week. Starting in Week 6 (when the win-back email launched), returning users spiked to ~2,600 per week.

The win-back campaign is successfully dragging churned users back, propping up our headline WAU. But it’s a leaky bucket: lifecycle data shows that only 12% of win-back users are active two weeks later (compared to 41% of organic returning users). They churn right back out.

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2. Why "Summer" isn't to blame

Your theory about summer (outdoors, holidays) would manifest as broad seasonal churn across all cohorts. But our data shows: 1. Older cohorts (1–4) maintained stable long-term retention. 2. The drop in retention is strictly tied to Cohort 5 onwards—the exact week we shipped the shorter sign-up flow.

It is product-led churn, not seasonal.

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3. What we should do instead of doubling paid acquisition

Before we scale ad spend, we need to fix activation and stop relying on expensive band-aids. Let’s execute a 3-step pivot:

1. Re-introduce intent-matching to onboarding (without hurting conversion): We need to qualify users so they receive the right weekly plan. Instead of a heavy 3-minute form, let’s test a lightweight, single-tap goal selector or defer personalization to the end of the first workout. We must restore Week 4 retention from 25% back toward 34%.
2. Refine the win-back targeting: Pumping win-back emails to all churned users after 21 days is bringing back low-intent users who churn in 14 days. Let’s restrict win-backs to users who reached a milestone or completed at least 3 workouts before churning, matching the profile of our 41% organic returners.
3. Optimize the Week 3–4 activation loop: We shipped 40 new routines in Week 3, but post-onboarding drop-off is neutralizing it. We need to focus activation efforts on guiding new users to these routines before they hit the Week 3 cliff.

Bottom line: Let's hold off on doubling paid acquisition for 4 weeks. If we fix the onboarding leak and improve post-signup intent, organic growth + recovered retention will naturally push us past our WAU plateau without wasting ad dollars on leaky traffic. Let's sync on this today.

Leo — I wouldn’t double paid acquisition yet. The flat WAU is masking a retention problem, not showing that summer is the whole story.

• The active base is eroding while inflows hide it. From week 1 to week 13, new users rose from 6,034 to 7,847 (+30%), but retained users fell from 44,884 to 41,636 (−7%). Weekly churn rose from 7,116 to 10,279. WAU stayed near 52,000 because more new users—and, from week 6, more returning users—offset that loss.
• New-user retention deteriorates sharply after week 4. For the first four signup cohorts, week-4 retention was 33–34%, and week-8 retention about 30%. For cohorts in weeks 5–8, week-4 retention was 24–25%; week-5 retention was about 22%, versus about 32% for the earlier cohorts at the same age. Week-1 retention actually improved (roughly 54–55% to 58%), then users fell away faster. So sign-ups are easier to get, but fewer people build a lasting workout habit.
• The timing points to a product change worth investigating. In week 5, we removed the goal-setting step. Sign-up completion rose from 61% to 74%, while the cohort retention pattern worsened immediately. That’s strong evidence to investigate whether the change brought in less-committed users or removed useful personalization—not proof that it caused the decline. Seasonality may contribute, but it doesn’t explain away the sharp cohort break.
• Win-back lifts WAU more than durable retention. Returning users rose from about 1,000 to about 2,600 a week after the week-6 campaign. But only 12% of email-returners were active two weeks later, compared with 41% of people who returned on their own. The campaign may be adding short-lived activity, not repairing the underlying habit problem.

What I’d do before scaling spend:

1. Test the onboarding change now. A/B test restoring goal-setting (or a shorter version) against the current flow. Measure signup completion alongside week-1 activation, week-4/8 retention, and workouts completed—not just registrations.
2. Improve the first-week habit loop. Give users a clear, personalized weekly plan and a timely next-workout prompt. Track results by signup week, onboarding version, and acquisition channel.
3. Put win-back on a holdout. Measure incremental, sustained activity and Premium conversion against users who don’t receive the offer; don’t count the initial return as success.
4. Hold off on doubling acquisition. The week-9 paid increase came after the retention decline had already begun. Scale only when newer cohorts retain better and paid users show acceptable downstream value.

Fixing the leak first gives us a better chance of turning additional acquisition into durable actives rather than more short-lived sign-ups.