ACADEMIC TEAM CASE · TEAM 4 · 90 DAYS
MUSIC PRODUCT / GENRE-LED DISCOVERY
SoundVibe
Genre-Driven Core Experience
Genre as a path from choice to habit.
Not another music catalog. A clearer path to what someone wants to hear.
STRATEGY MODEL · NOT AN ACTUAL RESULTSV
SIDE A
PLAY WHAT MOVES YOUSIDE A
A / 01 / 03
01 / CASE SIGNAL01
People browse for too long. A listening habit has no chance to form.
In the academic case, users spend too much time browsing a generic catalog, while genres do not provide an easy starting point. The original brief also states that genre-level listening data is missing and must be instrumented first.
Hard to start
The catalog does not offer a short path to music that fits.
Genre does not guide
Preferences do not connect onboarding, discovery and return listening.
Limited measurement
Without genre-level data, skip rate, session depth and week-2 retention cannot be compared.
PRODUCT OPPORTUNITY
Use genre as the backbone of the experience: from the first choice to personalized discovery and continuous listening.
↗02 / PRODUCT SOLUTION
Genre Core: from choice to listening.
Genre onboarding
Choose a primary genre after sign-up and start quickly with a few curated playlists.
Genre discovery
A personalized feed and ready-to-play playlists help users listen instead of browsing.
Continuous flow
Autoplay and contextual return cues support longer sessions and habit formation.
03 / TESTABLE HYPOTHESES03
Three bets. Validate each one separately.
The uplifts below are projected effects in the academic strategy, not experiment results.
Choosing a genre early makes the first session more relevant.
+8%listening time targetA genre-based feed reduces discovery friction and deepens sessions.
+8%listening time targetAutoplay and contextual nudges help users return to familiar genres.
+4%listening time targetSTRATEGY TARGET+20%Scenario total across the three hypotheses, contingent on validating each phase.
04 / 90-DAY PLAN
Measure first. Then build recommendations.
PHASE 01Days 0-30
Foundation
Instrument genre events, choose a pilot genre from data, build onboarding and curate 4-5 playlists.
GO / NO-GO GATE
Gate: onboarding ≥85%; case scenario W2 retention ≥48%.
PHASE 02Days 30-60
Discovery
Test a genre feed, autoplay and a baseline variant; track skips and session time.
GO / NO-GO GATE
Gate: signal toward +8% listening time; no guardrail regressions.
PHASE 03Days 60-90
Scale
Only after validation, add secondary genres, contextual nudges and recommendation refinements.
GO / NO-GO GATE
Target scenario: 4.86M listening hours/month and 55% W2 retention.
05 / METRICS & DATA05
Total Listening Time is the strategy goal. Behaviour shows why.
Total Listening Time: move from the case baseline of 4.05M to a target 4.86M hours per month.
Week 2 retention, return by genre cohort and repeat listening.
Skip rate, time to first listen, session length and genre diversity.
Compare onboarding/feed with baseline; treat targets as hypotheses until tested.
06 / RISKS & RESPONSES
Personalization should invite discovery, not lock people into one genre.
Cold start
Use editorial playlists and trending content until enough listening history exists.
Too narrow a choice
Allow genre changes and reserve some recommendations beyond the primary genre.
Repetition and fatigue
Mix familiar tracks with related genres and refresh playlists.
Poor tagging
Audit genre metadata before automating recommendations.
SCENARIO BUSINESS IMPACT
+$580K/ mo · forecastThe team presentation models +$580K monthly revenue if engagement and retention targets are met. This is a financial assumption in the case, not actual SoundVibe growth.
TEAM ARTIFACTS
Strategy, product loop and decision gates.
Academic team case. Baseline figures are presented as case inputs; KPI targets, budget and business impact are forecasts. The supplied materials contain no genre-level analytics or A/B results, so this case presents a measurement and validation plan rather than proven growth.
SOURCES: TEAM 4 PRESENTATION AND CASE DESCRIPTION