B

Dubai Exhibition Lead Harvester

3.20

Derivation Chain

Step 1 Expansion of Korean companies' participation in Dubai exhibitions
→
Step 2 Lead management for exhibition participants
→
Step 3 Automated follow-up CRM for exhibition leads

Competitor references

No usable source links are available for this idea. Its signal notes and scores need independent verification.

Problem

Korean medical device and IT SMEs with annual revenue of 1-5 billion KRW (approx. $750K-$3.75M) participating in Middle East exhibitions like WHX Dubai spend 1-2 weeks manually organizing 200-500 business cards and QR leads collected over 3 days into Excel and individually writing English follow-up emails. Research shows that failing to follow up within 72 hours after the exhibition reduces lead conversion rates by over 60%.

Solution

A mobile app that instantly OCR-processes business card photos and QR codes captured at the exhibition, inputs them into CRM, automatically classifies lead grades, and generates and sends personalized English and Arabic follow-up emails via LLM. It automatically calculates exhibition ROI reports (cost per lead, conversion rate).

Target: Overseas sales managers at Korean medical device and IT SMEs with annual revenue of 1-5 billion KRW (approx. $750K-$3.75M) that participate in 1-3 overseas exhibitions per year.
Revenue Model: Per exhibition license: 199,000 KRW per event (approx. $149.25) (includes 500 leads), additional leads 200 KRW per lead (approx. $0.15), annual subscription (5 exhibitions) 799,000 KRW (approx. $599.25).
Ecosystem Role: Supplier
MVP Estimate: 2_weeks

NUMR-V Scores

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

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.

Market Validation (56/100)

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
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

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