Turned onboarding answers into a personalized “getting started” experience on the home screen, reducing churn and boosting early app activation and engagement.
TL;DR
- What: Post-onboarding “getting started” feature that turns onboarding answers into a clear first week
- Why: Members finished onboarding, then churned, saying the app felt overwhelming and they didn’t know where to start
- Role: Director of Member Content (Member Experience) — activation + personalization
- Outcomes:
- 52.1% of activated users converted through the feature
- 7-day activation increased by 9%
- Challenge sign-ups increased by 8.5%
- Median active engagements increased in the first two weeks after registering
- Content completions in the post-onboarding experience increased by 57% (after iterating on the content featured)
The Problem
After onboarding, members landed on a dense home screen with too many options and no obvious first step. Decision fatigue led to significant post-onboarding drop-off.
The Goal
Make the first session feel personal and doable by translating onboarding answers into a small plan.
The Solution
A “getting started” module at the top of the home screen that:
- Shows a small, curated set of recommendations
- Includes at least one multi-day program, practice, or challenge to encourage repeat engagement
- Explains why items are included (light transparency without complexity)
- Reinforces that engagement improves future recommendations
How It Worked
Inputs From Onboarding
- Fitness experience
- Motivation level
- Focus area
- Interests
- Assessment results
Recommendation Engine
- Rules-based AI algorithm combining historical trends with Exos methodology
- Generated 400,000+ unique recommendation sets
“Slot” Logic
- Content type per slot determined by interests, fitness experience, and motivation level
- Content types included on-demand videos, audio, articles, programs, practices, challenges, and regulation tools
- Slot 1: what the member wants (focus area)
- Slot 2: what the member needs (biggest opportunity)
- Slot 3: what the member loves (interest)
Collaboration
- Data: recommendation logic + measurement
- Methodology: inputs and rules alignment
- Product and Engineering: placement, feasibility, and performance
What This Reinforced
Personalization does not need to be complex to feel powerful. A clear first step can outperform a full catalog.