B

Evidence Organizer for Small Business Owners Affected by Coupang

3.95

Derivation Chain

Step 1 Sanctions against Coupang for violating the Large-Scale Distribution Industry Act
→
Step 2 Difficulty for small business suppliers in responding to unfair practices by large distribution companies
→
Step 3 Building capacity to file complaints with the Fair Trade Commission by systematically collecting and organizing evidence of damage

Competitor references

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

Problem

Small business suppliers in their 40s-50s, even when they suffer unfair practices from large distribution platforms (such as Coupang) like forced returns, shifting promotional costs, and delayed payment for goods, give up filing complaints with the Fair Trade Commission because they don't know how to systematically collect and organize evidence. Although the damage per case is 1 to 5 million KRW (approx. $750 to $3,750), many fail to receive relief due to insufficient evidence.

Solution

On the web, users select the transaction type (returns/promotional costs/payment delays, etc.) and upload emails, KakaoTalk screenshots, and contract photos. The service automatically classifies and organizes evidence by type of violation under the Large-Scale Distribution Industry Act. It generates an evidence summary document in the format of the Fair Trade Commission complaint form and provides step-by-step guidance for the filing process.

Target: Representatives of small business suppliers aged 40-55, with at least 1 year of experience supplying to online distribution platforms, and who have experienced unfair practices.
Revenue Model: Evidence classification and organization: 3 cases per month free. Automatic complaint form generation: 15,000 KRW per case (approx. $11.25). Referral fee for connecting with distribution-specialized lawyers.
Ecosystem Role: Supplier
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
5.0/5
M Market
4.0/5
R Realizability
3.0/5
V Validation
4.0/5
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.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (67%)

Tech Complexity
24.0/40
Data Availability
23.1/25
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 (62/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
18.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
12.0/15
Solo Buildability
7.0/10
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

Frontend [medium] Backend [medium] AI/ML [medium]
Dashboard