---
title: Relevance Index metric
slug: '3318'
canonical_url: https://docs.coveo.com/en/3318/
collection: coveo-analytics
source_format: adoc
---
# Relevance Index metric

The **Relevance Index** [metric](https://docs.coveo.com/en/263.md) evaluates how well search results satisfy user [queries](https://docs.coveo.com/en/231.md).
It combines several behavioral signals, including the clickthrough rate, the [Average Click Rank](https://docs.coveo.com/en/2836.md), and how frequently a query is performed.

These signals are combined to produce a score between `0` and `1`, where higher values indicate stronger search performance.
In general, higher clickthrough rates and lower average click ranks contribute to better scores.

Lower [Relevance Index](https://docs.coveo.com/en/2838.md) values mean users aren't finding what they're looking for.
Sorting queries or items by ascending **Relevance Index** is our recommended approach to focus on high-impact queries or items with [relevance issues](https://docs.coveo.com/en/2017.md).

> **Note**
>
> The **Relevance Index** is intended as a relative metric used to compare queries and identify potential relevance issues, rather than an absolute measure of search performance.
> The formula and parameters may evolve over time as the metric continues to be refined.
## How the Relevance Index is calculated

The **Relevance Index** calculation relies on three behavioral signals:

* Clickthrough rate
* Average click rank
* Number of queries

These signals are combined into two components:

* **Relevance**, which reflects user engagement signals.
* **Confidence**, which reflects how frequently a query is performed.

The calculation can be summarized as follows:

```
Score = Relevance x Confidence
Relevance Index = (Score + 1) / 2
```

The normalization step converts the score from a range of `-1` to `1` into a `0` to `1` scale used in reports.

Relevance is computed using a weighted combination of the clickthrough rate and click rank.
Confidence increases with the number of queries, meaning that queries with higher frequency produce more reliable scores.

> **Note**
>
> In Coveo Analytics [reports](https://docs.coveo.com/en/266.md), the **Relevance Index** and **Relevance Index (Legacy)** values are color-coded to show whether they're good, bad, or neutral.
> 
> The predefined thresholds for each [metric](https://docs.coveo.com/en/263.md) are the following:
> 
> * **Relevance Index**: < 0.3 = bad (red), >= 0.3 and \<= 0.7 = neutral (black), and > 0.7 = good (green)
> * **Relevance Index (Legacy)**: < 0.5 = bad (red), from 0.5 to 0.7 = neutral (black), and > 0.7 = good (green)
### Concept of confidence

The **Relevance Index** uses the concept of confidence.
For the same proportion of **Search Event Clickthrough** and the same **Average Click Rank**, the current **Relevance Index** value will increase proportionally to the number of times a user query is performed.
In the same scenario, the **Relevance Index (Legacy)** value would have decreased.

Confidence amplifies the result.
Queries performing well receive scores increasingly above `0.5` as their frequency grows, while poorly performing queries receive scores increasingly below `0.5`.

**Example**

For the same **Search Event Clickthrough** (that is, 40 %) and an **Average Click Rank** of 3, the table below shows how a positive change in the **Search Event Count** metric impacts the **Relevance Index** and **Relevance Index (Legacy)** values.

| Search Event Count | Clickthrough (%) | Average Click Rank | Relevance Index | Relevance Index (Legacy) |
|---|---|---|---|---|
| 5 | 40 | 3 | 0.63 | 0.70 |
| 10 | 40 | 3 | 0.68 | 0.65 |
| 50 | 40 | 3 | 0.80 | 0.56 |
| 100 | 40 | 3 | 0.84 | 0.52 |
| 500 | 40 | 3 | 0.87 | 0.46 |

### Average Click Rank value impact

An **Average Click Rank** value change has less impact for the same number of queries and clickthrough rate in the **Relevance Index** formula.
The value changes gradually.

**Example**

For the same **Search Event Count** (that is, 500) and a clickthrough of 40%, the table below shows how a change in the **Average Click Rank** metric impacts the **Relevance Index** and **Relevance Index (Legacy)** values.

| Search Event Count | Clickthrough (%) | Average Click Rank | Relevance Index | Relevance Index (Legacy) |
|---|---|---|---|---|
| 500 | 40 | 1 | 0.87 | 0.82 |
| 500 | 40 | 4 | 0.85 | 0.42 |
| 500 | 40 | 8 | 0.78 | 0.35 |
| 500 | 40 | 12 | 0.64 | 0.32 |
| 500 | 40 | 16 | 0.56 | 0.30 |

### Score of queries with a Clickthrough of 0%

The **Relevance Index** attributes a low score to queries with a clickthrough of 0 %.

**Example**

For the same **Search Event Count** (that is, 500) and an **Average Click Rank** of 3, the table below shows how a change in the **Search Event Clickthrough** metric impacts the **Relevance Index** and **Relevance Index (Legacy)** values.

| Search Event Count | Clickthrough (%) | Average Click Rank | Relevance Index | Relevance Index (Legacy) |
|---|---|---|---|---|
| 500 | 0 | 0 | 0 | 0.72 |
| 500 | 1 | 3 | 0.08 | 0.53 |
| 500 | 10 | 3 | 0.41 | 0.43 |
| 500 | 25 | 3 | 0.7 | 0.44 |
| 500 | 50 | 3 | 0.91 | 0.48 |