View analytics

This page describes metrics that can help you determine how Vertex AI Search for commerce is affecting your business.

Prerequisites

The analytics dashboards use ingested user events as data sources for metrics. You must complete user events integration to be able to see user event analytics. Metrics are refreshed about every six hours, so it can take hours after you create your app to see metrics on the Analyticspages.

User events

The following user events are required to view some metrics:

• Search events.Required for any type of metrics.
• Detail page view events.Required for page view metrics.
• Add-to-cart events.Required for add-to-cart rate, conversion rate.
• Purchase-complete events.Required for total revenue, recommender-engaged revenue, average order value, purchase rate, revenue rate, average unit value, purchase order rate, conversion rate.

The following information is also used for analytics:

• Product details. To ensure accurate computation of search-related metrics, include UserInfo.productDetails within your user events. This information allows Vertex AI Search for commerce to attribute searches with specific product interactions. If the UserInfo.ProductDetail.quantity field is omitted within user events, a default value of 1 will be assumed for calculations.
• Revenue. The UserInfo.PurchaseTransaction.revenue field is crucial for generating accurate revenue metrics. Ensure this field is populated within your user events to enable meaningful revenue-related analysis.
• Attribution tokens. Attribution tokens are unique IDs generated by Vertex AI Search for commerce and returned with each search request. Make sure to include that attribution token as UserEvent.attributionToken with any user events resulting from a search. This is needed to identify if a search is served by Vertex AI Search for commerce.
• User agent. Include UserInfo.userAgent with user events resulting from a search so that you can filter on user event metrics by device type.

View recommendations analytics

To view recommendation analytics:

1. In the Google Cloud console, go to the Search for commercepage.

   Go to the Search for commerce console

2. In the navigation menu, click Analytics.

3. Click the Recommendationtab.

4. Use filters to view your metrics:

   • If available, enter a custom date range or select a preset range.
   • You can select a device type on which the recommendation occurred.
   • To show metrics for a recommendation setting, use all of the following filters. Set none to display aggregated metrics over all recommendation settings.
     • Serving config ID
     • Recommendation ID
     • Context event type with a displayed recommendation

View search analytics

If there are no user events, default values are shown for all metrics.

To view search analytics:

1. In the Google Cloud console, go to the Search for commercepage.

   Go to the Search for commerce console

2. In the navigation menu, click Analytics.

3. Click the Searchtab.

4. Click a tab to view that metric group:

   • Per Search. Metrics are grouped by searches.
   • Per Visit. Metrics are grouped by search visits.

5. To filter your metrics, use the following filters:

   • Date range. Select a preset date range or, if available, enter a custom date range.
   • Device type. Select a device type that queries occurred on.

View browse analytics

If there are not yet any user events, default values are shown for all metrics.

To view browse analytics:

1. In the Google Cloud console, go to the Search for commercepage.

   Go to the Search for commerce console

2. In the navigation menu, click Analytics.

3. Click the Browsetab.

4. Click a tab to view that metric group:

   • Per Browse. Metrics are grouped by browses.
   • Per Visit. Metrics are grouped by browse visits.

5. To filter your metrics, use the following filters:

   • Date range. Select a preset date range or, if available, enter a custom date range.
   • Device type. Select a device type that browsing occurred on.

View serving config analytics

1. In the Google Cloud console, go to the Search for commercepage.

   Go to the Search for commerce console

2. In the navigation menu, click Serving Configs.

3. Click the name of the serving config that you want to view analytics for.

4. Click the Analyticstab.

5. Select a metric type from the Metricdrop-down list to see its graph for the last month.

Metrics definitions

These sections provide definitions of the site-wide metrics displayed on the Analyticspage :

• Recommendations summary metrics : Metrics representing user engagement with recommendation results.
• search summary metrics:
  • Text query search summary metrics : Metrics representing engagement with text-based query search results.
  • Browse search summary metrics : Metrics representing engagement with category browse search results.

Recommendations summary metrics

The following metrics are displayed for recommendations on the Recommendationstab.

Text search summary metrics

The following metrics for text searches are displayed on the Searchtab.

Browse search summary metrics

The following metrics for browse searches are displayed on the Browsetab.

Configuration-specific metrics

You can see metrics for a specific serving config on the Serving Configs page . For metric graphs, click a serving config name to go to its details page, then select the Analyticstab.

This table provides definitions for configuration-specific metrics.

To track clicks from a serving config, Vertex AI Search for commerce aligns the results in predict and search responses with ingested user events. If a clicked item appears in the responses for the same visitor ID within a one hour time window, the click or purchase is treated as a result of the Vertex AI Search for commerce.

This process is fully automatic; you don't need to set anything up. However, when you configure your prediction and 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 match the timestamp for that event.

When 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 this method is to use attribution tokens . This requires significant instrumentation and is only recommended as an advanced tracking use case.