Case study · 2025

PulseHealth Wellness  Retention Tuning for a Habit & Meditation App

From a 7-screen tutorial nobody read to a 2-screen onboarding that gets users to their first habit in 30 seconds.

Wellness / HealthtechProduct GrowthUX/UI Design

Impact

What changed.

01

Day-7 retention up from 22% to 38%

The combined effect of a faster onboarding and behavior-aware notifications nearly doubled day-7 retention across new install cohorts — recovering a major share of users that were previously leaking out in the first week.

02

Onboarding completion up from 41% to 78%

Shrinking onboarding from 7 screens to 2 — and reframing it around the first real action instead of feature explanation — almost doubled completion and pulled activation forward.

03

Push CTR up 2.6× after framework switch

Replacing generic broadcast notifications with behavioral, time-of-day-aware messages lifted push click-through 2.6× and made the channel a real retention lever instead of background noise.

Person using a wellness and habit tracking app on a phone

The challenge

Before

PulseHealth Wellness had built a strong top-of-funnel — sign-ups were healthy and the brand had earned a loyal early cohort. But day-7 retention sat at 22%, and the founder team knew it was hemorrhaging users right after install. The onboarding was a 7-screen tutorial almost no one finished. Push notifications were generic and badly timed. The team had instincts about what to fix but no rigorous test program to prove anything before shipping it to 120k monthly actives.

  • Day-7 retention stuck at 22% — the leak started in the first session
  • 7-screen onboarding tutorial with a 41% completion rate
  • Generic push notifications fired on a fixed schedule for all users
  • No cohort-level view of when and why users disengaged
  • No experimentation framework — every change shipped to 100% of users
  • In-app re-engagement was a single static banner with no targeting
  • Push CTR was under 2% — most notifications were ignored or dismissed
  • Founder team operating on instinct, not data, for product decisions

The solution

What we built

We ran a 4-month Product Growth retainer with one explicit goal: lift day-7 retention. We rebuilt onboarding from a 7-screen tutorial into a 2-screen flow designed to get the user logging their first habit within 30 seconds of opening the app. We then stood up an A/B testing program around push notifications, testing three frameworks against each other — time-of-day, message frame, and frequency. We layered in an in-app re-engagement nudge driven by cohort behavior signals (last open, last completed habit, time-of-day pattern), and ran a weekly cohort retention review with the founders so every shipped change was tied back to a measurable outcome.

PulseHealth Wellness — Retention Tuning for a Habit & Meditation App solution

Core workflow connections

How the system flows.

  • Cohort DefinitionRetention CurveDrop-off Point IdentificationHypothesis Backlog
  • Onboarding Rebuild2-Screen FlowFirst Habit in 30sActivation Event
  • Push A/B FrameworkTime-of-day TestMessage Frame TestFrequency TestWinner Rollout
  • In-app Nudge: Behavioral SignalCohort MatchNudge TriggerEngagement Lift Measurement
  • Weekly Retention ReviewCohort ComparisonTest Decision LogNext-week Backlog

Process

How we built it.

Step 01

Cohort Definition → Retention Curve → Drop-off Point Identification → Hypothesis Backlog

Step 02

Onboarding Rebuild → 2-Screen Flow → First Habit in 30s → Activation Event

Step 03

Push A/B Framework → Time-of-day Test → Message Frame Test → Frequency Test → Winner Rollout

Step 04

In-app Nudge: Behavioral Signal → Cohort Match → Nudge Trigger → Engagement Lift Measurement

Step 05

Weekly Retention Review → Cohort Comparison → Test Decision Log → Next-week Backlog

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