product overview
Chearful is a full-stack AI-powered HealthTech platform offering personalized therapy journeys for individuals, while enabling clinics, insurers, and corporates to deliver mental wellness at scale. It operates across three layers:
- B2C: A platform for users to find and book therapy sessions based on behavioral and contextual cues.
- B2B: A dashboard and scheduling solution for clinics to manage availability and bookings.
- Enterprise/API: White-labeled, compliant APIs enabling insurers and employers to offer embedded wellness support.
- Model: Pay-per-session (B2C), monthly SaaS (clinics), outcome-based enterprise pricing (API layer)
ownership
From Day 0, I owned the full product lifecycle — from discovery and solution architecture to delivery and growth. Key responsibilities included:
- Defined product vision, MVP scope, and modular platform roadmap
- Created customer personas via direct interviews and research
Led feature definition, pricing models, and GTM planning - Worked closely with engineering, UX, ML, and compliance to ship, scale, and iterate
- Reported progress using weekly KPIs, OKRs, and customer feedback loops
Market Sizing & Opportunity
The $66B global mental health market is growing fast, with $18B in digital therapy. We focused first on the $2.1B GCC market (UAE, KSA) due to insurer-driven demand, low digital competition, and fast wellness adoption. Post-MVP, we targeted North America for its higher ARPU, platform maturity, and expansion potential across B2C and enterprise channels. Competitors were present but lacked localized UX, API flexibility, and outcome-driven models creating clear room to grow.
Personas, Use Cases & Solution footprint
Individual Users (B2C)
Use Case: Quickly find the right therapist with privacy, minimal effort, consistent follow-up, and transparent pricing
Challenges: 60%+ drop-off during therapist selection, mismatches eroded trust, lack of clarity on fit or cost, and poor session continuity led to disengagement.
Solution Foortprint:
- AI-driven intake system using 110+ behavioral and preference signals for smart therapist matching
- Session personalization engine adapting to feedback, past outcomes, and engagement patterns
- Automated scheduling with synced availability, reminders, and smart nudges
- Transparent pricing UI based on therapist tier, timing, and usage behavior
- Rebooking logic triggered by gaps or missed follow-ups to improve retention
Outcome: 2x increase in conversion, reduced drop-offs, stronger user trust, and improved continuity through personalized, low-friction therapy journeys.
Clinics, Insurers & Employers (B2B / Enterprise/API)
Use Case: Deliver scalable, compliant therapy services with lower ops cost and trackable outcomes
Challenges: High therapist underutilization (40–50%), 30%+ no-shows, 40% admin time on manual ops, limited ROI visibility, lack of integration-ready tools, and high churn from cost fatigue and session gaps.
Solution Foortprint:
- AI-led automation for scheduling, payouts, and therapist availability (↓60% ops time)
- WebRTC infrastructure for secure, real-time session delivery
- Session bundling + auto-renewals, improving retention and repeat sessions by 40%
- White-labeled API platform for seamless insurer/employer integration
- Live dashboards for usage, engagement, and ROI tracking
- Dynamic cost optimization to reduce delivery costs and align with behavior
- Compliance-ready architecture meeting HIPAA, GDPR, and regional privacy standards
Outcome: Reduced delivery costs by 50%, boosted utilization and retention, and secured enterprise deals with compliance-backed, scalable solutions.
Impact & Reach
- Conversion Rate: 2x increase in 3 months post AI-led therapist matching
- Recurring Sessions: 23% → 31% in 4 months via session bundling and rebooking automation
- AOV: $25 → $37 with dynamic pricing and package flows
- Churn: ↓18% by fixing mismatches and automating follow-ups
- Retention: +33 pts in 5 months from continuity flows
- TTFV: ↓31% through instant match and simplified onboarding
- CSAT: ↑24% in 4 months after UX and matching improvements
- Feature Adoption: ↑40% post intake and dashboard revamp
- Therapist Utilization: 2.4x increase via smart scheduling and availability sync
- No-Show Rate: ↓20-30% with reminders and calendar sync
- Ops Cost: ↓30-40% from automated scheduling and payouts
- Enterprise Deals: 2 insurer rollouts in 6 months with API integration
Strategic Initiatives & Learnings
- Started B2C-first to validate AI matching and flows; scaled to B2B/API with modular rollout
- AI deeply embedded across matching, scheduling, rebooking, and pricing—worked only when tied to UX and feedback loops
- Built platform early (APIs, data infra, compliance), enabling faster insurer and clinic adoption
- Optimized for recurrence with bundles, auto-rebook, and usage-led pricing
- GTM driven by data, Mixpanel insights guided key changes
- Compliance-first (HIPAA, GDPR) helped close B2B deals
- Speed to value was key—cut TTFV to boost retention and referrals
- GCC launch validated model, reused infra for NA expansion
