Diagnose a retention problem

To: Leo — Fix the retention leak before doubling acquisition

Weekly actives are flat because rising acquisition and reactivation are offsetting worsening retention. Summer could contribute, but the clearest break in the data follows the week-5 onboarding change—not the later increase in paid spend.

What’s happening

1. We are replacing more users, not building a larger active base.

Weekly active users equal retained users + new users + returning users. Equivalently, weekly net growth equals new + returning − churned.

From week 1 to week 13: - New users rose 30%, from 6,034 to 7,847. - Returning users rose from 973 to 2,635. - Weekly churn rose 44%, from 7,116 to 10,279. - Retained users fell from 44,884 to 41,636.

The result: weekly actives moved just 0.4%, from 51,891 to 52,118. The share of the previous week’s actives retained fell from 86.3% to 80.2%. This is deterioration beneath a flat headline.

2. New users look better after one week, but substantially worse afterward.

Compare signup cohorts before and after the week-5 release:

Only the week-5 post-change cohort has an observed week-8 result. Blank cells are unobserved, not zero.

The week-4 decline is roughly nine percentage points, or 27% relative, and repeats across multiple mature post-change cohorts. Earlier cohorts flatten near 30% by weeks 7–8; the first mature post-change cohort flattens near 20%. That suggests a smaller durable habit-forming base, not merely delayed engagement.

3. Win-back is masking the problem, not fixing it.

Returning users jumped immediately after win-back emails began in week 6. Lifecycle attributes about 1,600 extra weekly returns to the campaign, but only 12% of email-returned users were active two weeks later, versus 41% of earlier organic returners.

Those populations are not comparable enough to establish a causal campaign effect. Nevertheless, most campaign returners are not sustaining activity. Repeated returns and lapses can support WAU without creating lasting growth.

Likely diagnosis—and what remains uncertain

In week 5, we removed goal-setting and weekly-frequency selection. Signup completion improved from 61% to 74%, but subsequent cohorts became much less durable.

The leading hypothesis is that we removed a commitment and planning step central to a fitness habit. Alternatively—or additionally—the easier funnel admitted more low-intent users, lowering average retention. Both could be happening.

Timing alone does not prove causality. We lack randomized evidence, acquisition-source breakdowns, and a prior-year seasonal comparison. Still, the abrupt cohort break starts before the week-9 paid-social increase and persists afterward. “It’s summer” is not a sufficient diagnosis. Also, new-cohort deterioration may not explain all aggregate churn; we should examine established users separately.

What we should do before spending more

1. Hold paid spend at its current level. Don’t double distribution into a deteriorating retention curve.

1. Test lightweight goal-setting immediately. Randomize new visitors between current onboarding and a short goal/frequency step that produces a concrete weekly plan. Measure week-4 retained users per onboarding entrant, not just signup completion or retention among completed signups. This captures the conversion–retention trade-off. Track first-workout completion and second-week adherence as early signals; Premium conversion and revenue as business guardrails.

1. Localize the leak. Segment equal-age cohorts by paid/organic source, campaign, onboarding exposure, and initial workout/plan behavior. Check existing-user retention around week 5. Reconcile the differing signup totals across the two exports before joining them.

1. Evaluate win-back with a randomized holdout. Optimize for incremental sustained activity and eventual revenue—not email-driven return visits alone.

Increase acquisition only after we demonstrate improved durable retention and acceptable channel economics. Right now, more acquisition would buy more arrivals; it has not demonstrated that it will buy lasting growth.

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.