B

Local Small Business Group Buying Board

3.40

Derivation Chain

Step 1 Small business digital operations
→
Step 2 High costs from individual small-quantity orders
→
Step 3 Group purchasing among local small business owners to reduce costs

Problem

Small business owners aged 45-58 running neighborhood restaurants, cafes, and snack shops pay 20-40% more for ingredients, packaging, and supplies compared to large franchises when ordering individually. Shops in the same building or street order similar items (cooking oil, disposable containers, napkins, detergent) separately from different suppliers in small quantities. Group purchasing could significantly reduce unit costs, but there is no channel to coordinate items, quantities, and order timing with neighboring shops.

Solution

When local small business owners register items for group purchasing, the platform automatically groups them to secure wholesale pricing. First, when a demand like 'need 18L cooking oil this week' is registered, it auto-matches buyers of the same item in the same area. Second, it obtains wholesale quotes based on combined quantities and shows savings compared to individual orders. Third, it handles ordering, payment, and delivery in one place and distributes to each shop.

Target: Small business owners aged 45-58 running 1-2 person neighborhood restaurants, cafes, and snack shops; 3+ shops clustered in the same commercial district; monthly supply orders of 500,000-2,000,000 KRW (~$375-$1,500)
Revenue Model: Free to join group purchases; 10% commission on savings upon successful purchase; wholesale supplier partnership ads
Ecosystem Role: Consumer
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
4.0/5
M Market
4.0/5
R Realizability
2.0/5
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.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (63%)

Tech Complexity
24.0/40
Data Availability
19.4/25
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 (59/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
15.0/15
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

Frontend [medium] Backend [medium]
Dashboard