BUKI | Product Audit
Product audit and growth strategy for the BUKI platform. Funnel analysis, conversion drop diagnosis, and 6-month execution plan | By Yevhenii Holovei
PO Test TaskProduct AuditGrowth Strategy
01.
Funnel Audit
Funnel Structure: Traffic → Lead → Contact → Trial → Payment
1
Traffic -- Low Risk
SEO (tutor and subject pages), direct, paid. Strong SEO asset with multiple acquisition channels. Risk depends on search relevance.
SEODirectPaidLow Risk
2
Lead / Prospect -- Medium Risk
Search → tutor list → profile → 3-step modal flow (level, frequency, duration → name, phone, email → time and goals). Each step is a drop-off point.
Medium Risk
3
Contact -- Low Risk
First lesson scheduled and confirmed. Transition to bukischool.com.ua (domain change). Completed form signals commitment level.
Low Risk
4
Trial -- Medium-High Risk
Free trial lesson via BUKI School (Zoom). Zero student accountability -- can cancel or forget without consequences. Most dangerous stage.
Medium-High Risk
5
Payment -- Medium Risk
Post-trial email sent with account balance showing "0 hours". Conversion depends on tutor quality and student readiness, not platform mechanics.
Medium Risk
Critical Problems
Zero Student Accountability (Trial)Critical
Free, obligation-free trials reduce perceived value. Students have no financial anchor confirming intent.
Weak Post-Trial Conversion Mechanics (Payment)Critical
Platform lacks conversion control. Dependency on tutor quality. Suspected off-platform arrangements between tutors and students harm revenue capture.
No Personalized Recommendations (Prospect)Warning
Tutors presented as a passive list with filters. Platform provides no intelligent narrowing based on student goals, level, or schedule.
Maximum Value Loss Point
Maximum value drain occurs at the Opportunity → Payment transition where single-lesson quality variability and platform powerlessness converge.
02.
Deep Dive: 20% Conversion Drop
4 Sub-Stages to Investigate
1
Submission → Manager Contact
Measured by median time-to-first-contact. Degradation here causes direct impact on conversion.
2
Manager Contact → Trial Scheduled
Tracked via booking confirmation rates by manager and tutor. Problems include acceptance rate failures or poor sales scripts.
3
Trial Scheduled → Trial Completed
Monitored through no-show rates, cancellations, and rescheduling frequency. Rising no-shows indicate student commitment issues.
4
Trial Completed → First Payment
% of trials converting to payment within 7 days. Identified as highest-risk due to passive conversion mechanics.
6 Hypotheses (by Probability)
| Hypothesis | Data Required | Probability |
|---|---|---|
| Time-to-contact degraded | Monthly median contact time | High |
| Traffic quality declined | Traffic source breakdown (paid/organic) | Medium |
| Tutor acceptance rate fell | Acceptance metrics + response times | High |
| Market seasonality | Historical seasonal patterns | Medium |
| Post-trial dropout increased | Trial-to-payment rate analysis | High |
| Form UX regression | Step-by-step completion rates | Medium |
Quick Wins (2–4 Weeks)
1
Time-to-Contact Optimization
Alerts for submissions unanswered >2 hours. Auto-acknowledgment SMS/email for immediate response signal. Effort: 3–5 days.
+3–5% Lead→Contact
2
Post-Trial Trigger Sequence
1–2 hours post-trial: rating request (SMS/Viber). 24 hours: satisfaction check with direct top-up link. 72 hours: urgency message about slot availability. Effort: ~1 week.
+5–8% Trial→Payment
3
Dormant Lead Reactivation
3-message email sequence over 7 days for unconverted leads: new tutors, educational content, personalized matches. Effort: ~1 week.
+2–4% reactivation
4
Tutor Response Acceleration
Auto-reminder to tutors at 4-hour mark if no response. Manager alert at 8 hours; option to reassign to available tutor. Effort: ~3 days.
+10–15% acceptance rate
03.
Growth Strategy: +10% Lead→Client
5 Initiatives & RICE Prioritization
| Initiative | Priority | Impact | Effort | RICE | Month |
|---|---|---|---|---|---|
Post-Trial Conversion Flow SMS → email → messenger after trial with booking triggers | Medium | +2–3% | 1 week | 160 | M1 |
Lead Reactivation Automated 3-email sequence targeting unconverted leads | Low | +1–2% | 1 week | 21 | M1 |
Trust Signals & Time-to-Contact Response time, online status, "X% continue after trial" on profiles | Medium | +2–3% | 2 weeks | 70 | M2 |
Tutor Video Profiles 30–60 sec video introductions. Proven by Preply model. | High | +3–5% | 4 weeks | 52 | M3 |
Smart Match + AI "Best match for you" block using AI and form intake data | Very High | +4–6% | 12 weeks | 20 | M4–M6 |
Sequencing Rationale
Despite low RICE score, Smart Match has the highest strategic value. First -- quick wins (M1–M2) to establish baseline with zero CAPEX. Then infrastructure (M3), then AI (M5–M6) -- when sufficient data has accumulated to train the model.
Expected Cumulative Impact
04.
Execution: 6-Month Roadmap
Month-by-Month Roadmap
M1
April -- Foundation & Quick Wins
Funnel dashboard (Lead→Contact→Trial→Payment). Post-trial triggers (SMS/email/Viber/Telegram within 1–2 hours). Reactivation of leads from previous 3 months. Metric: Trial→Payment +2%.
PMDataBackend
M2
May -- Trust & Responsiveness
Trust signal UI: response time badges, online status, booking counts, retention % on profiles. Manager responsiveness system. A/B test CTA on tutor profiles. Video onboarding prep. Metric: Time-to-contact ≤2 hours, Lead→Contact +3%.
PMDesignBackendFrontendData
M3
June -- Video Profiles
Video infrastructure (storage, encoding, playback). Tutor video onboarding (30–60 sec). Video profile integration. A/B test: profiles with video vs. control group. Metric: Trial booking rate +5%.
PMDesignBackendFrontendData
M4
July -- Analysis & Smart Match Foundation
Video profile performance analysis by segment (subject, level, geography). BRD/PRD for Smart Match. ML model requirements: learning from continuation rates, tutor responsiveness, calendar availability. Metric: cumulative +3–5% above baseline.
PMDataBackend
M5
August -- Smart Match v1
Recommendation block: top-3 tutors based on goals, level, schedule from form. AI prompt interface: text box for describing needs. Continuous model retraining pipeline. Metric: Choice-to-contact rate +5–7%.
PMBackend (ML)Frontend
M6
September -- Refinement & Next Steps
Smart Match optimization based on A/B test data. Subscription bundle testing (8+ lessons at discounted rate post-trial). NPS program after 3rd lesson. 6-month retrospective + Q4 roadmap revision. Metric: cumulative +10%, NPS baseline 75–80.
PMDesignBackendFrontendData
Team
| Role | FTE | Responsibilities |
|---|---|---|
| Head of Product | 1.0 | Strategy, OKR management, backlog prioritization, stakeholder alignment, sprint governance |
| Product Designer | 1.0 | UX research, interaction design, prototypes, trust signal UI, post-trial screen flows |
| Backend Engineer ×2 | 2.0 | Notification trigger systems, calendar API integrations, matching algorithms, tutor acceptance workflows |
| Frontend Engineer | 1.0 | Booking form refactoring, bukischool.com.ua post-trial interfaces, trust signal rendering |
| Data Analyst | 0.5 | Dashboard construction, A/B test analysis, weekly metrics review, alerting infrastructure |
| QA Engineer | 0.5 | Regression testing each sprint, booking flow edge cases, notification delivery validation |
Coordination pattern: weekly 15-minute metrics standup + monthly OKR check-ins with CPO/CEO.
Measurement System
North Star Metric+10%
Lead → Client conversion rate | Target: +10% over 6 months | Cadence: weekly% of leads becoming paying customers within 30 days of trial. Published in shared dashboard weekly.
Leading Indicators (weekly)
1
Time-to-first-contact
Target: <2 hours. Daily alerts when exceeded.
2
Tutor acceptance rate
Target: >85%. Alert when below 70%.
3
Trial completion rate
Target: +10% vs. baseline.
4
Post-trial payment rate
7-day window. Key conversion indicator.
5
Form completion rate
All 3 form steps.
6
Choice-to-contact rate
For Smart Match recommendations. Starting from M5.
Critical Technical Note
Dashboard must track users across two domains (buki.com.ua → bukischool.com.ua). Requires server-side event tracking or GA4 cross-domain configuration. Without this -- analytics provides an incomplete picture.
PO Test Task -- BUKI Product Audit & Growth Strategy | Author: Yevhenii Holovei | Target: +10% Lead→Client conversion