A

GLP-1 Clinic Booking Optimizer

3.65

Derivation Chain

Step 1 Expansion of oral GLP-1 obesity therapeutics
Step 2 Patient surge at obesity clinics causing appointment/waitlist chaos
Step 3 Clinic appointment & revisit auto-scheduling SaaS

Problem

As oral GLP-1 therapies become mainstream, obesity/diabetes clinics are experiencing a surge in new patients. Small clinics (1-3 doctors) manage appointments and re-prescription schedules manually separate from their EHR, wasting 5-8 hours per week. No-show rates of 15-20% cause monthly revenue losses of 2-4 million won (~$1,500-$3,000).

Solution

Provides automated re-appointment scheduling aligned with GLP-1 prescription cycles (4-week/8-week), no-show prediction-based overbooking optimization, and KakaoTalk automated reminders to improve clinic operational efficiency.

Target: Clinic directors of obesity/endocrinology practices with 5 or fewer staff, physicians aged 30-50 in private practice
Revenue Model: SaaS Monthly Subscription at 59,000 won (~$44)/clinic, 20% discount for annual billing. Additional 50 won (~$0.04) per appointment beyond 500/month.
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
4.0/5
M Market
4.0/5
R Realizability
4.0/5
V Validation
3.0/5
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.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (69%)

Tech Complexity
29.3/40
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.

Market Validation (54/100)

Competition
8.0/20
Market Demand
3.8/20
Timing
14.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
10.5/15
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.

Technical Requirements

Backend [medium] Frontend [medium] Infrastructure [low]
Dashboard