How is Keyword Relevance Calculated?

2025-05-27| Help Center|views(320)|Comments(0)

Keyword Relevance measures how closely a keyword matches your product, based on the overlap between the keyword’s search results and your selected competitor ASINs.

Core Logic

Relevance is calculated by checking how many of the competitor ASINs appear in the top 96 organic search results for a given keyword (based on desktop layout: 48 results per page → top 2 pages, or 16 per page → top 6 pages). The more often your selected ASINs appear in these top positions, the more relevant the keyword is considered to be.
Occupancy Rate = y / x 
Where:
  • x = number of positions analyzed (e.g., top 4, 16, 48, or 96)
  • y = number of your selected competitor ASINs found within these positions
In simple terms: the higher the share of your competitor products in the top organic positions under a certain keyword, the more relevant that keyword is to your product.

Example

Suppose you sell insulated cups and enter 50 competitor ASINs. When analyzing the keyword “insulated cup”:
  • In the top 4 results, 4 are competitor ASINs → Occupancy Rate = 4/4 = 100%
  • In the top 16 results, 10 are competitor ASINs → Occupancy Rate = 10/16 = 62.5%
  • In the top 48 results, 35 are competitor ASINs → Occupancy Rate = 35/48 = 72.9%

Final Relevance Score: Weighted Average

Since each keyword may show different occupancy rates across position ranges, the final score is a weighted average of multiple ranges (e.g., top 4, 16, 48, 96), with higher weights assigned to top positions.

Relevance Levels

Final Score (Weighted Occupancy Rate)

Relevance Level
≥ 60%

High Relevance

20%–59%

Medium Relevance

5%–19%

Low Relevance

< 5%

Irrelevant

 

 


How to Prepare a Competitor ASIN List for Better Accuracy

To get the most out of this feature:
  1. Avoid too few ASINs – Too small a sample can skew results based on weaker competitors’ rankings.
  2. Avoid too many ASINs – A large sample increases crawl time and may dilute relevance due to lack of focus.
  3. Ideal input: ~48 ASINs – Matches the number of products on one Amazon desktop search results page.
  4. Diversify your ASINs – Include both high-sales and high-similarity competitors to balance precision and market representativeness.

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