> For the complete documentation index, see [llms.txt](https://help.citrusad.com/retail-media-interface/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.citrusad.com/retail-media-interface/advertiser-reporting/understanding-on-site-standard-and-enhanced-metrics.md).
# Understanding on-site standard and enhanced metrics
On the onsite performance dashboard you can see campaign performance as well as enhanced metrics. In addition to the standard campaign performance, you can also understand brand HALO and instore purchasing performance.
{% hint style="info" %}
The enhanced metrics table will appear once it’s enabled for your retailer. In some cases, your retailer may need to make integration updates before it’s available.
{% endhint %}
### Understanding enhanced metrics
There are three attribution methodologies operating in the platform and available. Together, these three methods allow you to understand how advertising contributes to both online and offline sales:
* **Direct platform attribution (standard):** underpins all onsite attribution and links ads to exact product purchases.
* **Halo attribution:** captures influence across related products or view-through behaviours for the same brand.
* **In-store attribution:** extends measurement to link onsite browsing to offline retail purchases.
This layered attribution approach delivers a more complete picture of how ads are performing and helps making it easier to understand campaign performance across the full retail journey.
### Understanding attribution
Attribution connects advertising interactions (like ad views and clicks) with purchases, so retailers and brands can understand how their ads contribute to sales.
#### 1. Direct platform attribution: linking ads to purchases
Direct platform attribution measures conversions that occur directly because a shopper interacted with an ad on the retailer’s site. This model tracks both:
* **Clicks:** when a shopper clicks an ad and then makes a purchase.
* **Impressions:** when a shopper sees an ad and later purchases within a set period.
**How it works**
When a purchase happens online, sales data is sent to the platform.\
The system then matches each purchase to prior ad interactions based on:
* exact matching product codes between the ad and the purchased item.
* a lookback window (e.g., 14 days) that defines how far back the system will look for an ad interaction before a purchase. Lookback windows vary per retailer.
If the conditions are met, the purchase is attributed to the ad. This provides precise, product-level attribution for online sales.
#### 2. Halo attribution: capturing broader ad influence
Halo attribution extends beyond direct matches and captures related influence that ads can have on purchases. The system uses the retailer's product catalog with each product having a brand synchronized, so the platform knows which products should be considered related.
**How it works**
When a purchase happens online, sales data is sent to the platform.\
The system then matches each purchase that has not already been attributed to prior ad interactions based on:
* **Click attribution:** if a shopper clicks an ad and then buys a related product in the same session, the sale is still associated with the ad even if the product codes differ.
* **Impression view-through attribution:** if a shopper sees an ad (without clicking) and later purchases the same product within the same session, that purchase can be counted as influenced by the ad.
This model gives a wider view of impact, recognizing ad influence that isn’t captured by direct (exact match) attribution alone.
#### 3. In-store attribution: connecting digital ads to brick-and-mortar sales
While direct and halo attribution focus mainly on online purchases, in-store attribution links online ad interactions with offline, in-store purchases. This shows whether digital ads influenced shoppers who eventually bought items in physical stores.
**How it works**
Retailers synchronize instore sales data with the platform.\
The system then matches each purchase to ad interactions based on:
* Tracking IDs match between online ad data and in-store sales records.
* SKU codes align between online and store sales files.
This provides an even broader understanding of how ads drive real-world sales.
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