Reading a result
A search returns up to 10 products in a ranked list. Each row packs a lot of signal into a small amount of space. This page is the field guide.
In this guide:
- The anatomy of one result row
- What the SellerScore is (in 30 seconds)
- Which sub-scores to glance at first
- How to spot a “false high”
Anatomy of a row
Reading left to right:
| Part | What it tells you |
|---|---|
| Image | The product. Tap to open detail. |
| Title + brand | Who you’d be competing with. |
| Price | The sell price the SellerScore was computed against. |
| SellerScore (0–100) | The headline. Higher is better. |
| Sub-score chips | The six independent sub-scores (D / M / C / T / S / X for Demand, Margin, Competition, Trend, Seasonality, Cross-platform). Each is 0–100 too. |
| Data quality badge | Yellow if any sub-score fell back; red if multiple did. Trust the score less when this is colored. |
| Net profit per unit | Quick read on whether the margin is dollar-meaningful. |
| BSR / category | Best Sellers Rank for context. |
| Actions | Open detail, add to watchlist. |
What the SellerScore is, in 30 seconds
A weighted average of the six sub-scores. Default weights:
- Demand 25% • Margin 20% • Competition 20% • Trend 15% • Seasonality 10% • Cross-platform 10%.
A 75 means “this scored well across most sub-scores.” A 75 with a data-quality red badge means “scored well across the available sub-scores; some fell back to estimates.” That’s not the same thing.
Which sub-scores to glance at first
Different research goals weight differently in your head:
| Goal | Sub-scores to glance at |
|---|---|
| “Is anyone buying this?” | Demand, Trend |
| “Will I make money?” | Margin, Competition |
| “Is this the right time of year?” | Seasonality |
| “Can I source it cheaper than competitors?” | Cross-platform (when live) |
| “Is the niche too crowded?” | Competition |
The chip row lets you read a row in 2 seconds: any chip in the 70+ green is a positive contributor; any in the 30 or below red is dragging the composite down.
How to spot a “false high”
A high SellerScore can mislead in three ways. Watch for these:
1. High score, low data quality
If the data-quality badge is red or yellow, the score is partly extrapolated. A SellerScore of 80 with red data quality may be actually a 60 on real data. Open the product detail to see exactly which sub-score fell back.
2. High score, narrow margin
A 80 SellerScore with a $1.50 net-profit-per-unit is a low-margin product that needs volume to be worth selling. Glance at the absolute profit number, not just the margin %.
3. High score, declining trend
A high score on a product with a falling trend chart is yesterday’s winner, not tomorrow’s. Open the detail and look at the 12-month trend chart before committing.
How to read the data-quality badge
| Badge | Meaning |
|---|---|
| 🟢 Green / no badge | All six sub-scores from preferred data sources. Trust the score. |
| 🟡 Yellow | One sub-score fell back to a secondary source (e.g., demand used BSR+Trends instead of SFR). |
| 🔴 Red | Two or more sub-scores fell back, or a critical one (margin) is missing. The composite is informational; verify before acting. |
Hover or tap the badge to see exactly which sub-scores are affected.
What’s next
Manage your credits — the most common follow-up question after a first search.