Create and manage a Product Recommendation (PR) model

Coveo Machine Learning (Coveo ML) Product Recommendation (PR) models use usage analytics (UA) events to relevantly target and suggest products to your customers. Therefore, you must log commerce events to ensure that your commerce interfaces correctly track user interactions.

Depending on the recommendation strategy you want to leverage, ensure your commerce interface is tracking the proper events:

Depending on whether models have already been created in your Coveo organization:

Click Next.

(Optional) In the Learning interval section, you can change the default and recommended Data period and Building frequency.

Click Next.

(Optional) In the Apply filters on dataset section, you can add filters to refine the data that the model uses to make its recommendations. By narrowing down the dataset that a model uses, you can better customize relevancy for specific user groups and use cases. You can apply filters on all events, or on every event that belongs to a specific category, such as search, click, view, or custom events.

Click Next.

In the Name your model input, enter a meaningful display name for the model, and then click Start building.

Note On the Models (platform-ca | platform-eu | platform-au) page, under the Status column, in the model row, the value is most probably Inactive. The model value will change to Active when the model creation is complete (typically within 30 minutes, depending on the amount of usage analytics data to process). The model can only return recommendations when its status is Active. For more information on Coveo ML model statuses, see the Status column reference.

(Optional) If you want to specify advanced parameters for your model, you can use the Advanced tab of the model configuration.

You can then associate the model with a pipeline to take advantage of the model in a search interface.

Make sure to follow the model association leading practices before associating your model with your production query pipeline.

On the Models (platform-ca | platform-eu | platform-au) page, click the model you want to edit, and then click Edit in the Action bar.

On the subpage that opens, select the Configuration tab.

Under Name, you can optionally edit the model’s display name.

(Optional) In the Learning interval section, you can change the default and recommended Data period and Building frequency.

(Optional) In the Apply filters on dataset section, you can add filters to refine the data that the model uses to make its recommendations. By narrowing down the dataset that a model uses, you can better customize relevancy for specific user groups and use cases. You can apply filters on all events, or on every event that belongs to a specific category, such as search, click, view, or custom events.

Click Save.

On the Models (platform-ca | platform-eu | platform-au) page, under the Status column, in the model row, the value is most probably Updating.

Note The model value will change to Active when the model edition is complete (typically within 30 minutes, depending on the amount of usage analytics data to process). The model can only return recommendations when its status is Active. For more information on Coveo ML model statuses, see the Status column reference.

You can then associate the model with a pipeline to take advantage of the model in a search interface.

Make sure to follow the model association leading practices before associating your model with your production query pipeline.

Access the Models (platform-ca | platform-eu | platform-au) page.

Click the desired model, and then click More > Edit JSON in the Action bar.

In the Edit a Model JSON Configuration panel that appears, modify the existing model configuration:

{
  "modelDisplayName": "<MODEL_DISPLAY_NAME>",
  "exportPeriod": "<EXPORT_PERIOD>",
  "intervalTime": <INTERVAL_TIME>,
  "intervalUnit": "<INTERVAL_UNIT>",
  "commonFilter": "<COMMON_FILTER>",
  "customEventFilter": "<CUSTOM_EVENT_FILTER>",
  "exportOffset": "<EXPORT_OFF_SET>",
  "searchEventFilter": "<SEARCH_EVENT_FILTER>",
  "viewEventFilter": "<VIEW_EVENT_FILTER>",
  "extraConfig": [<ADVANCED_ML_PARAMETERS>],
}

Click Save to apply your changes.

On the Models (platform-ca | platform-eu | platform-au) page, click the ML model that you want to delete, and then click More > Delete in the Action bar.

In the Delete a Model panel that appears, click Delete model.