C2C Trust Score Analyzer

3.70

Derivation Chain

Step 1 Karrot Pay and trust system expansion

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Step 2 C2C Platform trust Infrastructure demand

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Step 3 Trust score-based transaction decision tool

Problem

When trading on C2C platforms like Karrot (Danggeun Market), there's no comprehensive standard for evaluating a counterparty's reputation score, payment trustworthiness, and transaction history, leading to fraud losses or abandoned safe transactions with an average opportunity cost of $37.50-$112.50 (~50,000-150,000 KRW) per transaction. For high-value items (electronics, luxury goods), using escrow adds 3-5% in fees, and researching a seller's profile takes 10-20 minutes per transaction.

Solution

The tool crawls public profiles across multiple C2C platforms (Karrot, Bunjang, Jungonara) — reputation scores, review keywords, repeat transaction rates — to calculate a unified trust score. Users enter a counterparty's profile URL before a transaction to receive fraud risk assessment and recommended transaction method (in-person/shipping/escrow). Suspicious patterns (new account with high-value listings, duplicate photos, etc.) are auto-detected with alerts.

Target: Ages 20-40, individual sellers/buyers making 3+ secondhand transactions per month, especially in electronics and luxury goods categories

Revenue Model: Premium SaaS Monthly Subscription $3 (~3,900 KRW)/account; Free tier: 5 lookups/month; Premium: unlimited lookups + real-time alerts; 20% discount for Annual Subscription

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

2.0/5

U Urgency

4.0/5

M Market

4.0/5

R Realizability

4.0/5

V Validation

4.0/5

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.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (72%)

Tech Complexity

29.3/40

Data Availability

23.1/25

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 (57/100)

Competition

10.0/20

Market Demand

20.0/20

Timing

10.0/20

Revenue Signals

4.5/15

Pick-Axe Fit

7.5/15

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

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

Dashboard