B

Local Festival Digital Guestbook

3.40

Derivation Chain

Step 1 Revitalization of traditional festivals like Sancheong-gun Jisinbapgi
→
Step 2 Local governments' need for festival visitor data collection
→
Step 3 Digital tools for collecting and analyzing festival visitor data

Competitor references

No usable source links are available for this idea. Its signal notes and scores need independent verification.

Problem

Local governments across Korea host over 1,200 regional festivals annually (like Sancheong-gun's Jisinbapgi folk ritual), but visitor counts are tallied manually with ±30% accuracy. They fail to systematically collect visitor satisfaction, revisit intent, and spending pattern data, resulting in weak budget justification for the following year. Outsourcing surveys costs $3,750–$7,500 (~5–10 million KRW) per engagement, which is unaffordable for smaller municipalities.

Solution

Provides a QR-based digital guestbook where visitors complete a brief survey (5-point satisfaction, spending range, revisit intent) while earning stamps. A real-time dashboard visualizes visitor counts, satisfaction, and spending patterns, and auto-generates standardized reports for Ministry of the Interior and Safety submissions.

Target: Festival coordinators in Culture & Tourism departments of small-to-mid municipalities (pop. 50K–200K), aged 30–50; festival management/event agencies
Revenue Model: Per-festival pricing — $290 (~390,000 KRW) for a 3-day festival (up to 5,000 visitors), $0.07 (~100 KRW) per additional visitor, 30% discount for annual packages of 3+ festivals
Ecosystem Role: Consumer
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
3.0/5
M Market
3.0/5
R Realizability
5.0/5
V Validation
2.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (81%)

Tech Complexity
40.0/40
Data Availability
20.6/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.

Market Validation (50/100)

Competition
8.0/20
Market Demand
9.4/20
Timing
10.0/20
Revenue Signals
7.5/15
Pick-Axe Fit
7.5/15
Solo Buildability
8.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.

Technical Requirements

Frontend [low] Backend [low] Data Pipeline [low]
Dashboard