B

AI Subscription Service Actual Usage Checklist

4.00

Derivation Chain

Step 1 Expansion of conversational AI advertising and commercialization
Step 2 Increase in paid AI subscriptions
Step 3 Identification and cancellation guidance for unused AI/digital subscriptions among 50-somethings

Problem

A worker in their 50s subscribes to AI services like ChatGPT Plus, Copilot, Midjourney, and Naver Clova out of curiosity, but on average 1.5 services are used 2-3 times or less per month. Combined with existing digital subscriptions (Netflix, YouTube Premium, cloud storage, etc.), 50,000-150,000 KRW (approximately $37-$112) is auto-charged monthly, but it's hard to track which card is charged how much. AI services are especially difficult to manage because they are billed in dollars and amounts fluctuate with exchange rates.

Solution

Enter card payment details (via text or screenshot) to automatically categorize subscription services, calculate each service's 'cost vs. actual usage frequency,' and recommend cancellation priority. Provide free alternatives for each AI service (free tiers, open-source options) and step-by-step cancellation guides.

Target: Workers aged 48-58, currently paying for at least one AI service, with 3+ digital subscriptions, and unable to track total monthly subscription costs
Revenue Model: Basic analysis free; monthly subscription management report (auto-payment fluctuation tracking) 2,900 KRW (approximately $2.20) per month; cancellation assistance 1,000 KRW (approximately $0.75) per transaction.
Ecosystem Role: Consumer
MVP Estimate: 2_weeks

NUMR-V Scores

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

Feasibility (74%)

Tech Complexity
32.0/40
Data Availability
21.7/25
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 (59/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
10.5/15
Solo Buildability
10.0/10
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 [medium]
Dashboard