Executive Summary

The first booking is the entire game for a health app — patients who complete one return predictably. The current funnel loses them at specialty selection and slot confirmation.

Problem Statement

New users abandon the booking flow at a high rate before confirming a slot, despite high search intent.

Business Goal

Lift first-booking completion by 20% in two release cycles.

User Research

PLACEHOLDER — proxy: published research and app-store reviews; 4 informal interviews with first-time users.

Competitor Research

Practo, 1mg, Apollo 24/7 — compared specialty discovery, doctor cards, slot UX, payment friction.

Personas

The Anxious First-Timer, the Repeat Caregiver booking for a parent, the Insurance-driven user.

User Journey

Land → search by symptom → confused specialty list → doctor list → expensive top result → drop.

Pain Points

Symptom-to-specialty mapping is unclear; doctor cards lack trust signals; slot times are dense and confusing; payment step asks for too much upfront.

Opportunity Identification

Symptom-led triage that recommends specialty + 3 doctors at 3 price points, with verified-review trust signals.

Root Cause Analysis

Patients can't translate symptoms into specialties. The product asks them to be doctors before booking one.

Success Metrics

Primary: first-booking completion rate. Supporting: time-to-confirmation, drop-off by step, reschedule rate.

North Star Metric

% new users who complete a first consultation within 7 days.

Product Strategy

Compress the first booking to three decisions: symptom, doctor, time. Defer everything else to post-booking.

Feature Ideas

Symptom-led triage, 3-doctor recommendation set, verified review badges, calendar-style slot picker, post-booking payment with hold.

Prioritization

MoSCoW: triage = Must, calendar slots = Must, post-booking payment = Should, badges = Could.

Framework Used

Design Thinking for ideation, HEART for measurement, MoSCoW for release scope.

Wireframes

Expected Business Impact

Modeled +15–20% first-booking completion; downstream lift in D30 retention.

Risks

Triage misclassification could erode trust. Mitigation: clear disclaimers, easy 'change specialty' affordance.

Trade-offs

Smaller doctor result set reduces choice for power users; mitigated by 'See all' affordance.

Future Scope

Symptom history → recommendation memory; integration with insurance pre-auth.

Lessons Learned

When the user lacks domain vocabulary, decisions are friction. Translate, don't expose.