https://raw.githubusercontent.com/komalverma183/cult.fit-case-study/main/periscopal/case-study-cult-fit-2.9.zip
This case study presents a comprehensive product strategy to enhance the onboarding experience for new users of https://raw.githubusercontent.com/komalverma183/cult.fit-case-study/main/periscopal/case-study-cult-fit-2.9.zip, a leading health and fitness platform.
A product case study to enhance onboarding for https://raw.githubusercontent.com/komalverma183/cult.fit-case-study/main/periscopal/case-study-cult-fit-2.9.zip’s 5M+ users and 600+ centers. Includes user research, journey mapping, pain point analysis, and an AI-powered onboarding solution. Showcases product thinking, user-centric design, and data-driven strategy.
- In-depth user research and persona development
- Mapping the user journey and identifying major pain points
- Prioritizing issues using the RICE framework
- Designing an AI-powered onboarding assistant (“CultBot”) for personalized recommendations and seamless navigation
- Clear success metrics focused on user retention, feature discovery, and subscription growth
- User Retention Rate: Increase by 15–25% within 6 months (e.g., from 40% to 50%+).
- Onboarding Completion Rate: Target ≥90% of new users completing onboarding.
- Feature Adoption Rate: Achieve ≥80% adoption of key features by new users in the first 30 days.
- Net Promoter Score (NPS): Improve by 10+ points (e.g., from 40 to 50+).
- Conversion Rate (Free to Paid): Increase by 10–20% after onboarding improvements.
- Monthly Active Users (MAU): Grow by 20% in the first quarter post-implementation.
- Customer Lifetime Value (CLTV): Raise by 10–15% year-over-year.
- Churn Rate: Reduce by 10–15% compared to pre-enhancement levels.
- Time to Onboard: Decrease average onboarding time by 30% (e.g., from 10 minutes to 7 minutes).
- Customer Support Requests During Onboarding: Reduce by 25% (indicating fewer user issues/confusion).
- Stakeholder Satisfaction Score: Maintain ≥4 out of 5 in post-launch feedback surveys