B

Accommodation Price Gouging Monitor

3.30

Derivation Chain

Step 1 BTS Gwanghwamun concert
→
Step 2 Concert-area accommodation price gouging enforcement
→
Step 3 Municipal accommodation price monitoring tool

Problem

During major concerts and events (BTS, World Expo, etc.), nearby accommodations charge 3-10x normal rates, causing consumer harm. Local government tourism department staff (2-3 people) spend 40+ hours per week manually monitoring hundreds of listings, struggling to compile enforcement evidence.

Solution

A SaaS that auto-crawls public pricing from major accommodation OTAs (Yanolja, Yeogi Eottae, etc.) and visualizes price change rates versus baseline on a real-time dashboard. Automatically flags abnormal surges (300%+) and generates one-click enforcement evidence PDFs (screenshots + price history). Core features: (1) Real-time price deviation dashboard vs. baseline, (2) Automated anomaly flagging for surge pricing, (3) One-click enforcement evidence PDF generation.

Target: Provincial/municipal government tourism department officials, Consumer Protection Agency investigators
Revenue Model: B2G SaaS Monthly Subscription at ~$367/municipality (490,000 KRW). Event short-term monitoring package at ~$1,125/event (1,500,000 KRW for 1 month).
Ecosystem Role: Regulation
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
3.0/5
M Market
2.0/5
R Realizability
4.0/5
V Validation
3.0/5
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.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (73%)

Tech Complexity
34.7/40
Data Availability
18.8/25
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.
Total 100 points; below 50% is filtered out.

Market Validation (51/100)

Competition
8.0/20
Market Demand
9.4/20
Timing
14.0/20
Revenue Signals
7.5/15
Pick-Axe Fit
7.5/15
Solo Buildability
5.0/10
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.
Total 100 points; below 50 is filtered out.

Technical Requirements

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