# Recommendations

Step into Recommendations Analytics, your gateway to a wealth of insights into the effectiveness of your recommendation strategies. This module empowers you to dissect the performance of your personalized recommendations, providing a detailed examination of user engagement, conversion rates, and the impact on your overall business objectives. Uncover the nuances of how different recommendation approaches contribute to your success and leverage data-driven decision-making to fine-tune and optimize your recommendation strategies.

<figure><img src="https://2635939301-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F6jDsmHXQ0gdSKhPuXFMw%2Fuploads%2FKzoOZkHtWkQF7BXsSQm4%2FScreenshot%202024-01-03%20at%209.10.20%20PM.png?alt=media&#x26;token=11890aea-c427-4b74-bf4b-f61389e2734b" alt=""><figcaption></figcaption></figure>

### Overview&#x20;

* **Total impressions:** Total number of recommendations impressions for the selected date range.&#x20;
* **Sessions:** Number of sessions where the customer saw at least 1 recommendation-type impression for the selected date range.
* **Click Through Rate:** Rate of sessions where the customer viewed the details of a recommended product, taking into account the attribution window and the selected date range.&#x20;
* **Conversion Rate:** Rate of sessions where the customer purchased a recommended product, considering the attribution window and the selected date range.&#x20;
* **Direct Revenue:** Revenue generated from the purchase of recommended products, considering the attribution window and the selected date range.&#x20;
* **Assisted Revenue:** Revenue generated from the purchase of products after the customer interacts with recommended products, considering the attribution window and the selected date range.

### Trends

For each of the above metrics, you can also visualize how these values have evolved over time. You have the flexibility to view this data on a daily, weekly, or monthly basis. Tailor your analysis to different timeframes, allowing you to gain a granular or high-level perspective on the evolution of metrics.&#x20;

### Date Filter&#x20;

You can narrow down your analysis to specific time ranges, allowing for a more focused examination of the performance of recommendations.&#x20;

<figure><img src="/files/ciG392SmIGaQDq9KACCc" alt="" width="331"><figcaption></figcaption></figure>

### Attribution Window&#x20;

The attribution window is the time allowed for an end user to complete the purchase of a clicked product. It can be same session, 7, 14 or 30 days.&#x20;


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://academy.gopersonal.ai/en/admin-ui/analytics/recommendations.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.