Auditable research model

Methodology

A transparent framework for ranking persistent franchise-level merchandise opportunities—not a subjective best-games list and not a prediction of revenue.

Why franchise level?

Ecommerce merchandise is usually built around persistent brands, characters, symbols, worlds, factions, and recurring title families. Individual releases are treated as momentum catalysts inside the broader IP.

Why actionability first?

The primary rank includes licensing friction, market saturation, operating complexity, and minimum-order exposure. This explains why enormous demand—such as Marvel’s Spider-Man—does not automatically rank first.

Observed versus modeled

Sales, concurrency, assortment, and pricing evidence are shown with dates and source tiers. Scoring and forecasts are visibly labeled as model outputs.

Initial weighted model

Eight criteria, one auditable score

Each criterion is rated from 0–10; the weighted result is normalized to 0–100.

Brand recognition
22%
Momentum & cadence
18%
Fandom engagement
15%
Visual suitability
15%
Licensing feasibility
12%
Demographic fit
8%
Price elasticity
5%
Market whitespace
5%
overallScore = (brandRecognition × 0.22 + momentum × 0.18 + fandomEngagement × 0.15 + visualSuitability × 0.15 + licensingFeasibility × 0.12 + demographicFit × 0.08 + priceElasticity × 0.05 + whitespace × 0.05) × 10

Decision labels

Recommendation bands

85–100Priority

Actively investigate rights and build a test thesis.

80–84.9Strong pursuit

Advance category and licensing discovery.

75–79.9Selective pursuit

Pursue only with a differentiated format.

68–74.9Test or monitor

Validate a narrow hypothesis or wait for a catalyst.

60–67.9Niche only

Small limited test for a known audience.

Below 60Deprioritize

Do not allocate near-term development time.

Two separate outputs

Raw demand ≠ actionability

Raw demand score

Consumer recognition, momentum, fandom engagement, visual potential, demographic reach, and price willingness—with minimal penalty for rights difficulty.

Small-company actionability

Adds licensing complexity, category saturation, minimum-order exposure, product operations, and practical differentiation.

Evidence quality

Confidence methodology

Confidence is not opportunity. It indicates how much trust to place in the supporting evidence.

confidenceScore =
  official sales evidence × 0.25
+ source recency × 0.20
+ source diversity × 0.15
+ engagement evidence × 0.15
+ merchandise evidence × 0.15
+ licensing evidence × 0.10
High · 80–100Medium · 60–79Low · below 60

Directional scenarios

Forecast methodology

The forecast does not pretend to predict actual sales or revenue.

projectedOpportunity = currentOpportunity
+ release catalyst adjustment
+ media catalyst adjustment
+ engagement trend adjustment
+ merchandise whitespace adjustment
− licensing delay adjustment
− saturation adjustment
− staleness adjustment

Ranges widen for low-confidence franchises, unconfirmed releases, complex multi-party rights, volatile live-service engagement, and older franchises without recent disclosures.

Research provenance

Source hierarchy

Tier 1

Official

Publisher, developer, investor relations, and official platform data.

Tier 2

Industry

Established databases and recognized analytics providers.

Tier 3

Public proxies

Community, streaming, retail, platform, and search indicators.

Modeled

Internal scenario

Transparent calculation, judgment, or explicit planning assumption.

Forecast scores are directional scenarios based on available market indicators, model weights, catalyst assumptions, licensing friction, and merchandise-market evidence. They are not predictions of actual sales or profit.