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Compare two listings
Your listing against another version of it (or any you like): each one's Wintraits Match Index with the winners, where each comes closest and what you would change in each.
This is the comparison you get
Which version is closer to the winners and by how much, how they differ, where each one wins, the price of each and what you would change in each.
Made-up listing; the calculation is the model's real one. Your first 2 reports are complete and free.
Listing B is closer to the ones that succeed: 16 more Wintraits Match Index points.
Wintraits Match Index: similarity with the launches that end up in the top-selling 20% of their quarter (0-100). 80% margin: among the 160 check products with a similar index, the real share of winners could be within this band. Correlation, not causation: these are patterns of winning products, not guarantees.
Both listings against the winners
What does each axis measure?
- Formula and actives
- What the product contains and how much: the active ingredients the listing highlights, the concentration of the main one, how many different actives it has and the sun protection factor (SPF), if any. Example: “Serum with 15% vitamin C and ferulic acid” scores on this axis; a “moisturising face serum” with no named actives does not.
- Format and use
- What the product is like and how it is used: packaging, texture, time of use, application, skin or hair type it targets, volume and units per pack. Example: “30 ml dropper, gel texture, day and night, for oily and combination skin”.
- Claims
- What the listing claims about what the product is or how it was tested: labels and guarantees, not results on the skin. Example: “Dermatologically tested”, “vegan”, “cruelty free”, “fragrance free”, “paraben free”, “hypoallergenic”, “made in Spain”. By contrast, “reduces wrinkles” is a promise (Promise axis).
- Listing (text and images)
- How the listing is told on Amazon: length of the title and description, number of bullet points and images, clarity and tone of the text, and how much product information it gives. Example: A title that says what it is, the active and the size, five complete bullet points and seven images, versus a short title with two photos.
- Value for money
- What it costs versus what it offers: price, price per ml, price versus products of a similar size, and how much content and how many promises it gives for that price. Example: Two 30 ml serums at €19.90: the one with 10% niacinamide and two more actives scores better on value for money than the one that names none.
- Promise
- What result it promises the customer: the benefits (hydration, anti-ageing, radiance, anti-dark spots, pores…), how many it promises and whether it gives figures. Example: “Hydrates and adds radiance” are two benefits; “reduces dark spots by 30% in 4 weeks” is also a promise with figures.
Listing B, in: Formula and actives, Format and use, Listing (text and images), Value for money.
Each axis groups the attributes that repeat in the winning combinations of that area, weighted by how many times more frequent they were in the check. 100 = as complete as the most complete 10% of winners on that axis.
How they differ
| What we read | Listing A | Listing B |
|---|---|---|
| Promised benefit | luminosidad | luminosidad, antimanchas |
| Listing quality | 2 | 4 |
| Ingredient | vitamina_c | vitamina_c, acido_hialuronico |
| Number of actives | 1 | 2 |
| Number of promised benefits | 1 | 2 |
| Skin type | no_indicado | todas |
| Time of use | — | dia |
What winners have, and what each listing has
| Attribute | Win · flop | A | B | Checked |
|---|---|---|---|---|
| quantified claim: yes | 23% · 9% | no | no | ×1.8 |
| claim: clinically proven | 26% · 10% | no | no | ×1.7 |
| listing quality: high | 22% · 10% | no | yes | ×1.7 |
| claim: dermatologically tested | 23% · 11% | no | no | ×1.7 |
| ingredient: niacinamide | 30% · 16% | no | no | ×1.3 |
| promised benefit: pores | 26% · 16% | no | no | ×1.1 |
| content index (actives, concentration and listing quality): high | 43% · 28% | no | yes | ×1.3 |
| description length: low | 42% · 29% | yes | no | ×1.2 |
| number of images: medium | 49% · 37% | no | yes | ×1.1 |
Share of winners and of flops that have each attribute (30 products or more). ×N = times more frequent among winners, with new products.
The price of each listing
Share of winners in each price-per-ml band; in blue, the band with the most winners, also with new products.
What you are missing, and how much it weighs
Recommended plan: from 6 to 22
Wintraits Match Index: similarity with the winners (0-100). Each change adds to the previous one. Only apply those that are true of your product.What you are missing, and how much it weighs
Recommended plan: from 22 to 25
Wintraits Match Index: similarity with the winners (0-100). Each change adds to the previous one. Only apply those that are true of your product.How it was calculated
| Sample | 1410 launches with a result (197 winners) |
| Period | launched between 2023-11-01 and 2026-04-30 |
| What succeeding means | Winner = product in the top 20% of the sales rank for its launch quarter (median of days 60 to 180). |
| Accuracy with new products | The model learned from listings as they are today, not as they were on launch day: it describes what the listings of successful products look like. The accuracy figure at launch is pending a new test. |
| Data as of | 2026-11-06 |
| Limits | Correlation, not causation. Every figure comes from 30 or more products. Only make changes that are true of your product. |
More detail in Methodology.