Small-to-mid-size film distributors (annual revenue $750K–3.75M / 10–50 billion KRW) and film investment fund managers spend 3–5 hours per title downloading raw data from the Korean Film Council (KOFIC) integrated ticketing system and processing it in Excel to determine whether a release will break even. The empirical formula for predicting final audience numbers from the first 3 days of ticket sales exists only in individual managers' heads, making knowledge transfer impossible.
Solution
Automatically collects KOFIC daily box office data and generates final audience count prediction ranges at day 3, 7, and 14 post-release based on a 10-year release pattern database. Provides scenario analysis incorporating genre, season, and simultaneous competing release variables, plus investment break-even alerts.
Target: Marketing directors at small-to-mid-size film distributors, film investment fund managers, film industry media journalists
Revenue Model: Report Subscription at $44/account/month (59,000 KRW, tracking up to 5 titles/month); additional titles at $9 Per Transaction (12,000 KRW). 15% discount for Annual Subscription.
Ecosystem Role: Supplier
MVP Estimate: 2_weeks
NUMR-V Scores
N Novelty
3.0/5
U Urgency
4.0/5
M Market
4.0/5
R Realizability
4.0/5
V Validation
4.0/5
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 (68%)
Tech Complexity
29.3/40
Data Availability
18.8/25
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 (71/100)
Competition
10.0/20
Market Demand
19.4/20
Timing
14.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
10.5/15
Solo Buildability
7.0/10
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.