The Search for Retail console provides metrics to help you determine how incorporating Vertex AI Search for retail is affecting your business.
View metrics
You can view summary metrics for your project on the Analytics page. This page displays site-wide metrics about revenue and orders. See Summary metrics for metrics definitions.
For metrics specific to your serving configs, go to the Serving Configs page. Click a serving config name and select the Analytics tab to see its metrics. See Configuration-specific metrics for metrics definitions.
Metrics definitions
Summary metrics
The table below provides definitions of the summary metrics that Vertex AI Search for retail displays on the Analytics page.
| Metric | Description | Details |
| Total revenue | The total revenue from all recorded purchase events. | This value includes shipping and tax. |
| Results-engaged revenue | The revenue for purchase events that include at least one product that was selected from a recommendation or search result. | This value includes shipping and tax and any discount applied. |
| Average order value (AOV) | The average value of orders from all purchase events. | Total revenue divided by the number of orders. |
| Results-engaged AOV | The average value of orders that include at least one item selected from a recommendation or search result. | Results-engaged revenue divided by the number of orders with at least one item that was selected from a recommendation or search result. |
Configuration-specific metrics
You can see metrics for a specific serving config on the Serving Configs page. For metric graphs, click the configuration name and select the Analytics tab.
The table below provides definitions for configuration-specific metrics.
| Metric | Description | Details |
| Click-through rate (CTR) |
The number of product detail views from a serving config divided by
the total number of predict or search queries for this configuration.
|
For example, if a recommendations serving config
points to a "Frequently Bought Together" model, then the CTR would be the number of product
detail pages viewed from the shopping cart recommendation panel divided by
the number of predict queries on the shopping cart page.
|
| Add-to-cart events | The number of add-to-cart events from a serving config divided by the total number of predict or search queries for that configuration. | |
| Purchase events | The total purchase events from the recommendations or search results from this serving config. |
To track clicks from a serving config, Vertex AI Search for retail
aligns the recommendations in predict responses and search results in search
responses with ingested user events. If a clicked item appears in the predict
or search responses for the same visitor ID within a one hour time window, the
click/purchase is treated as a result of the recommendation or search result.
This process is fully automatic; you do not need to set anything up. However, when you configure your prediction or search requests for the first time, you should confirm that:
- Visitor IDs in the request are the same as the visitor IDs you used in event ingestions.
- The timestamp in the response roughly matches the timestamp for that event.
When Vertex AI Search for retail metrics are compared to the ideal expected result, or ground truth, the values might be lower, but the trends align.
A more direct alternative to the method above is to use attribution tokens. This requires significant instrumentation and is only recommended as an advanced tracking use case.