Methodology
How Shimm Score Works
Every product gets a 0–100 score based on 7 weighted dimensions. No black box. Here’s exactly what goes into the number.
The Composite Score
Each dimension produces a score (0–100) and a confidence level (0–1). The final Shimm Score is a confidence-weighted average across all 7 dimensions, capped at 100.
Final Score = Σ(dimension_score × weight × confidence) ÷ Σ(weight × confidence)
The 7 Dimensions
Price Quality
25% weightWhether a product's current price represents genuine value relative to its history.
Signals
- •Position in 90-day price range (near low vs. near high)
- •Price drop magnitude (10%, 20%, 30%+ discounts)
- •Price momentum (is the price still falling?)
- •Discount authenticity (real sale vs. inflated markdown)
- •Cross-retailer comparison (Amazon vs. Google Shopping, eBay)
Data Sources
- •Keepa price history
- •Google Shopping
- •eBay sold prices
Demand Velocity
20% weightHow fast the product is selling and whether demand is accelerating.
Signals
- •Best Seller Rank strength (category-adjusted)
- •BSR velocity (improving, stable, or declining)
- •Estimated monthly unit sales
- •Stock-out frequency (high demand indicator)
- •Review velocity (reviews per month)
Data Sources
- •Keepa BSR history
- •Category sales tables
- •Reddit deal communities
Conversion Confidence
15% weightThe likelihood that buyers will convert based on social proof and brand trust.
Signals
- •Star rating (4.5+ is excellent)
- •Review count depth (category-aware thresholds)
- •Review recency (are recent buyers happy?)
- •Brand trust (recognized brand vs. generic)
Data Sources
- •Keepa review data
- •Brand trust index
Earning Potential
15% weightEstimated monthly commission earnings from promoting this product.
Signals
- •Commission per sale ($)
- •Price sweet spot ($15–$75 converts best for affiliates)
- •Volume × price × commission = monthly earning estimate
- •Arbitrage opportunity (Amazon vs. eBay price gap)
Data Sources
- •Category commission rates
- •BSR-to-sales conversion
- •eBay sold prices
Market Position
10% weightThe competitive landscape — how many sellers and whether the market is opening or closing.
Signals
- •Number of active sellers (few = less competition)
- •Seller count trend (falling = opportunity)
- •Amazon first-party presence
- •Category opportunity (high demand + low coverage)
Data Sources
- •Keepa offer data
- •Category benchmarks
Risk Profile
10% weightThe downside risk — price stability, product quality, and category safety.
Signals
- •Price volatility (stable prices = lower risk)
- •Review quality and count (well-reviewed = fewer returns)
- •Category risk level (supplements = risky, home & kitchen = safe)
- •Demand sustainability (is BSR stable or a flash?)
Data Sources
- •Keepa price variance
- •Category risk map (29 categories)
Timing Signal
5% weightIs now the right moment to promote this product?
Signals
- •Price position in all-time range (near historical low?)
- •Flash sale detection (sudden drop + active downtrend)
- •Momentum alignment (BSR improving AND price dropping)
- •Seasonal peak approaching
Data Sources
- •Keepa all-time history
- •Reddit deal threads
- •Google Trends seasonal data
Personalized Scoring
As you use Shimm, the scoring engine learns from your decisions. When you triage products as Good or Skip, patterns emerge — preferred categories, price ranges, BSR thresholds. After 10+ decisions, your scores get personalized:
- •Products in your preferred categories get a confidence boost
- •Products in categories you consistently skip get a warning signal
- •If you upload sales data, categories where you perform well get weighted higher
- •Price range alignment with your historical wins
Data Sources & Freshness
Shimm never scrapes Amazon product pages. All marketplace data comes through licensed APIs and official data providers.
Primary: Keepa
90-day price history, BSR trends, review velocity, stock-out data, seller counts. Refreshed on each lookup.
Amazon PA-API
Official product data, current pricing, availability. Used for enrichment and verification.
Google Shopping
Cross-retailer price comparison. Detects whether Amazon is the cheapest option.
Community Signals
Reddit deal thread mentions, Google Trends seasonal data. Adds context on timing and buzz.
Every research result shows which data sources contributed and when the data was last refreshed, so you always know how current the score is.
What the Score Is Not
- !Not a guarantee of earnings. A high score means the signals are strong — rising demand, good price, low competition. Your actual earnings depend on content quality, audience size, and timing.
- !Not financial advice. Shimm is a research tool. Product selection decisions are yours.
- !Not static. The scoring model improves continuously based on user feedback and outcome data. Weights and thresholds evolve.
See It In Action
Research any Amazon product and get a full 7-dimension breakdown. Free.
Start Scoring Products