> For the complete documentation index, see [llms.txt](https://docs.search.io/documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.search.io/documentation/fundamentals/search-settings/understanding-relevance-and-ranking.md).

# Understanding relevance and ranking

### Search score

When performing a search, Search.io assigns a search score to each document in the index. The score ranges from 0 (no match) to 1 (perfect match) and search results are ordered starting with the highest score. The relevance score consists of three score components: the *keyword score,* the *neural score*, and the *boost score*.

![The components of the search score.](/files/z05pPwh6WNCeChs0s9NE)

### Relevance <a href="#index-score" id="index-score"></a>

The **keyword score** represents the \[[Textual relevance](/documentation/fundamentals/search-settings/textual-relevance.md)]\(/pages/F654qUlittxw1Y3cYpxT) of the result. In other words, how well does the search text match the content. This considers spelling, synonyms, stemming, and other language specific features.

The **neural score** represents the neural hash similarity of the result and the search text.

The larger of these two scores is used when calculating the overall **search score**, and their contribution generally comprises the majority of the total score, since most users are looking for results which match their query.

### Ranking <a href="#feature-score" id="feature-score"></a>

The **boost score** represents the business-specific ranking of the **search score**. Generally comprising a smaller portion of the total score, it can be used to make [Ranking adjustments](/documentation/fundamentals/search-settings/ranking-adjustments.md) to better tailor results to business requirements or to personalize search results.