Museum Collaboration Performance Report

3.00

Derivation Chain

Step 1 K-POP × cultural heritage collaboration trend

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Step 2 Performance measurement service for collaboration agencies and museums

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Step 3 Automatic ROI report for collaboration campaigns

Problem

As K-POP and cultural institution collaborations like Blackpink×National Museum of Korea surge, both agencies and museums manually aggregate campaign performance (visitor changes, SNS buzz, merch sales) in Excel, wasting 8-12 hours per person per week. Performance data is scattered, leading to poor decision-making for the next collaboration.

Solution

Automatically collect SNS buzz (Twitter/Instagram hashtags), Naver search volume, and museum reservation API data to visualize pre/post collaboration performance on a dashboard. Provide benchmark comparison (vs. past collaborations) and automatic PDF report generation.

Target: Marketing teams (2-10 people) at small and medium entertainment agencies with annual revenue over 1 billion KRW (approx. $750,000), and exhibition planning teams at national/public museums and art galleries.

Revenue Model: SaaS monthly subscription: 99,000 KRW per month per project (approx. $74.25), 20% discount for annual payment. Premium (custom reports): 199,000 KRW per month (approx. $149.25).

Ecosystem Role: Infrastructure

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 (63%)

Tech Complexity

24.0/40

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 (50/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

7.5/15

Pick-Axe Fit

7.5/15

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.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [medium] Frontend [medium] Data Pipeline [medium]

Dashboard