B

Small Business Season Calendar

3.45

Derivation Chain

Step 1 Small business digital operations
→
Step 2 Revenue patterns exist but no systematic advance preparation
→
Step 3 Linking industry-specific seasonal events to revenue preparation

Problem

Small restaurant, cafe, and academy owners aged 45-55 know from experience the recurring revenue fluctuation patterns (school breaks, holidays, local festivals, post-college entrance exam season), but cannot systematically prepare in advance (adjusting ingredient orders, staffing part-timers, timing promotions). Especially, hyper-local events like municipal festivals, community events, and road construction significantly impact revenue, but this information is hard to obtain proactively.

Solution

Enter your business type and location to generate an annual season calendar. First, it displays industry-specific revenue patterns (restaurants: -20% before holidays, +30% on Fridays, etc.) based on statistical data. Second, it auto-collects municipal public event, festival, and road construction schedules to notify 'this week there's an event in your area, expect +/-% revenue.' Third, it generates action checklists aligned with revenue fluctuations (ingredient ordering, part-timer scheduling, SNS promotion timing).

Target: Aged 45-55, 1-3 person neighborhood restaurant/cafe/academy owners, operating at same location 3+ years, running both dine-in and delivery
Revenue Model: Basic season calendar (nationwide) free, local event integration + custom checklists at $2.95/month, B2B Subscription for franchise headquarters
Ecosystem Role: Regulation
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
3.0/5
M Market
3.0/5
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.
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 (70%)

Tech Complexity
29.3/40
Data Availability
20.8/25
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 (56/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
7.5/15
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.
Total 100 points; below 50 is filtered out.

Technical Requirements

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