> For the complete documentation index, see [llms.txt](https://docs.abtasty.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.abtasty.com/recommendations-and-merchandising/getting-started/recommendations/reporting-recommendation.md).

# Reporting Recommendation

### Goal

* Provide both a **global view** of all recommendations and a **per-strategy view** when data is available.
* Help identify optimisation opportunities based on user engagement and revenue impact.

### **Access**

* **Global view** – Available from the *Reporting* section in the sidebar.
* **Per-strategy view** – Accessible from the recommendations strategies table, via the “Reporting” icon, **only when performance data is available** for that strategy’s UUID.

### **Available options**

* **Filter by**:
  * Specific recommendation strategy
  * All recommendations combined
  * **Date range selector** – Choose a reporting period and compare it with the same previous period.
  * Device type (*mobile* / *desktop*)

### **Available metrics**

| **KPI**                        | **Definition**                                                                                            | **Example**                                                        |
| ------------------------------ | --------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------ |
| **Click-through rate (CTR)**   | % of exposed visitors who clicked on a recommended product.                                               | *10% CTR means 1 in 10 exposed visitors clicked a recommendation.* |
| **Revenue share**              | Revenue per visitor for those who clicked a recommendation vs. revenue per visitor for those who did not. | *€5 per clicking visitor vs €2 per non-clicking visitor.*          |
| **Revenue per visitor uplift** | Difference in revenue per visitor between interacting visitors and exposed non-interacting visitors.      | *Clickers generate €3 more revenue per visit on average.*          |

### **Performance over time**

* Displays performance for the selected period.
* View **one metric at a time**:
  * Impressions
  * Product clicks
  * Number of closes
  * Click rate
  * Close rate *(only available if the recommendation format can be closed)*

### **Key indicators** *(exportable CSV)*

The **Key Indicators** table provides a detailed breakdown of performance across three segments: *All visitors*, *Exposed visitors*, and *Converted users*.

{% hint style="info" %}
**Internal value**: 

This table is a powerful communication tool for stakeholders, as it links recommendation performance directly to core business KPIs (revenue, conversion, order value). It can help justify investment in new recommendation formats or highlight successes to management by showing measurable uplift between segments.
{% endhint %}

**Segments:**

* **All visitors** – Total visitors to the site.
* **Exposed visitors** – Visitors who saw a recommendation block.
* **Converted users** – Visitors who purchased after interacting with a recommendation.

**Metrics tracked for each segment:**

* **Visitors** – Total number of unique visitors in the selected segment during the period.
* **Revenue** – Total revenue generated by visitors in the selected segment during the period.
* **Revenue per user** – Average revenue generated per visitor in the selected segment.
* **Transactions** – Total number of orders completed by visitors in the selected segment.
* **Transaction rate** – Percentage of visitors in the segment who completed at least one purchase.
* **Average order value (AOV)** – Average revenue per transaction.
* **Sales index** – Average number of products purchased per transaction.
* **Unique SKU sales index** – Average number of distinct products (SKUs) purchased per transaction.

{% hint style="info" %}
Reading it allows you to:

* **Compare** **how each audience behaves** (e.g., Are exposed visitors spending more than average? Do converted users have a higher basket size?).
* **Identify opportunities to improve** — for instance, if the transaction rate for exposed visitors is low, this could mean the recommendation placement or relevance needs optimization.
* **Track the commercial impact of recommendations** using concrete business metrics like revenue per user, average order value, and sales index.
  {% endhint %}

***

### **Engagement indicators**

* **Direct contribution share** – Revenue from products purchased immediately after a click (visit or add-to-cart) on a recommendation.

{% hint style="info" %}
Measures the immediate, trackable impact of recommendations on sales.
{% endhint %}

* **Assisted contribution share** – Revenue from transactions where recommendations influenced the purchase but were not the final click before buying.

{% hint style="info" %}
Captures the broader impact of recommendations in the customer journey, even when the purchase happens later or via another path.
{% endhint %}


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