A

Actor Fandom Power Index

3.50

Derivation Chain

Step 1 K-drama actor buzz
→
Step 2 Advertisers' model selection decision-making
→
Step 3 Quantified per-actor fandom size and loyalty index

Problem

Marketing teams at brands spending $375K–$3.75M annually on advertising rely on ad agencies' subjective recommendations when selecting celebrity endorsers because there is no objective data to compare actors' actual fandom size, loyalty, or purchase conversion power. Brands commit $75K–$750K on talent contracts without data-driven verification of whether a given actor matches their target audience.

Solution

A SaaS platform that automatically collects each actor's SNS followers, real-time search volume, fan community activity, online mentions, and ad response rates to calculate a 'Fandom Power Index,' then provides a matching score against the brand's target segments. Core features: (1) Per-actor Fandom Power Index across reach, engagement, and conversion axes, (2) Brand target–fan base overlap analysis, (3) Competitor brand endorsement benchmarking.

Target: Marketing directors at consumer goods, Beauty, and Fashion brands with annual ad budgets over $375K; advertising agency account executives
Revenue Model: Monthly subscription at $220/month (monitoring 50 actors); single report at $150; Enterprise (500+ actors) custom pricing
Ecosystem Role: Supplier
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
3.0/5
M Market
5.0/5
R Realizability
3.0/5
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 (71%)

Tech Complexity
29.3/40
Data Availability
21.2/25
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 (58/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
16.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
12.0/15
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

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