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 Task
Product Audit
Growth 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.
SEO
Direct
Paid
Low 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
M1–M2+5–6%Automation + responsiveness
Post-trial flow and Lead reactivation + Trust signals and Manager alerts
M3–M4+8–11%Video + analysis
Video profiles add 3–5%, analysis and Smart Match foundation
M5–M6+10%Steady state
Smart Match operational, subscription testing, NPS program launched
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%.
PM
Data
Backend
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%.
PM
Design
Backend
Frontend
Data
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%.
PM
Design
Backend
Frontend
Data
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.
PM
Data
Backend
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%.
PM
Backend (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.
PM
Design
Backend
Frontend
Data
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