With the promotion of Daegu FC and other K League lower-division clubs experiencing a surge in fandom, small club operations teams (3-5 people) lack a CRM to systematically collect and analyze fan data after ticket sellouts, missing out on additional per-fan revenue (merchandise, F&B, sponsorship) during the season. The lost opportunity for additional revenue per club per season amounts to tens of millions of KRW annually, but there is no budget for a large-scale CRM.
Solution
Provide a fan data dashboard dedicated to K League clubs. (1) Automatically integrate ticket booking, merchandise purchase, and social media engagement data; (2) generate purchase conversion probability and recommended campaigns (merchandise bundles, season ticket upsells) by fan segment; (3) automatically generate fan profile reports for sponsor proposals. The differentiation is club-specific templates and integration with Korean payment data compared to existing large-scale CRMs.
Target: Marketing staff of K League 1 and 2 clubs (club operations teams of 3-10 employees), approximately 40 clubs affiliated with the professional football federation.
Revenue Model: SaaS monthly subscription: 290,000 KRW per club (approx. $217.50) per month, 20% discount for annual payment. Premium plan with automatic sponsor report generation: 490,000 KRW (approx. $367.50) per month.
Ecosystem Role: Supplier
MVP Estimate: 2_weeks
NUMR-V Scores
N Novelty
3.0/5
U Urgency
3.0/5
M Market
3.0/5
R Realizability
3.0/5
V Validation
3.0/5
NUMR-V Scoring System
N Novelty
1-5
How uncommon the service is in market context.
U Urgency
1-5
How urgently users need this problem solved now.
M Market
1-5
Market size and growth potential from proxy indicators.
R Realizability
1-5
Buildability for a small team with realistic constraints.
V Validation
1-5
Validation signal quality from competition and demand data.
N=.15 U=.20 M=.15 R=.30 V=.20
Feasibility (69%)
Tech Complexity
29.3/40
Data Availability
20.0/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity
/ 40
Difficulty of core implementation stack.
Data Availability
/ 25
Practical availability and cost of required data.
MVP Timeline
/ 20
Expected time to ship a usable MVP.
API Bonus
/ 15
Bonus for viable public API leverage.
Market Validation (64/100)
Competition
10.0/20
Market Demand
20.0/20
Timing
14.0/20
Revenue Signals
7.5/15
Pick-Axe Fit
7.5/15
Solo Buildability
5.0/10
Validation Breakdown
Competition
/ 20
Signal quality from competitor landscape.
Market Demand
/ 20
Demand proxies from search and mention patterns.
Timing
/ 20
Fit with current shifts in tech, behavior, and regulation.
Revenue Signals
/ 15
Reference evidence for monetization viability.
Pick-Axe Fit
/ 15
How well the concept serves participants in a trend.