Box Office-Linked Pop-up Location Recommender

3.05

Derivation Chain

Step 1 Box office hit 'The King and the Man' with 7 million+ admissions

→

Step 2 Surge in movie IP pop-up store businesses

→

Step 3 Lack of data for pop-up operators to select optimal location and timing

Problem

Small planning agencies (1-5 people) operating movie and drama IP pop-up stores spend 2-3 weeks individually researching foot traffic, target age density, rent, and competing pop-up status when selecting a pop-up location. When the box office curve and pop-up opening timing are misaligned, more than 30% of openings occur after audience interest has waned, resulting in sales of only 40-50% of expectations.

Solution

Track movie and drama box office curves in real time and recommend optimal pop-up opening timing. Compare foot traffic (based on SKT/KT telecom data), target age ratio, rent, and current competing pop-up status for major pop-up spaces in Seoul and the metropolitan area on a map. Provide a simulation linked to remaining box office life: 'If you open at this location at this time, expected visitors: X'.

Target: Small agencies (1-5 people, including freelancers) planning and operating movie and drama IP pop-up stores

Revenue Model: Per Transaction Report: 29,000 KRW (approx. $22) per movie + 3 location comparisons. Monthly subscription: 99,000 KRW (approx. $74) for unlimited searches + real-time alerts. 20% discount for annual payment.

Ecosystem Role: Supplier

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

4.0/5

U Urgency

4.0/5

M Market

3.0/5

R Realizability

2.0/5

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 (66%)

Tech Complexity

29.3/40

Data Availability

17.1/25

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 (51/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

7.5/15

Pick-Axe Fit

10.5/15

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

Technical Requirements

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

Dashboard