Manage Listing Page Optimizer (LPO) models

This is for:

System Administrator

This article explains how to create and manage Coveo Machine Learning (Coveo ML) Listing Page Optimizer (LPO) models in the Coveo Administration Console.

Prerequisites

Before enabling LPO in your Coveo organization, make sure that you:

Create an LPO model

  1. On the Models (platform-ca | platform-eu | platform-au) page of the Coveo Administration Console, click Add model, and then click the Listing Page Optimizer card.

  2. Click Next.

  3. Under Catalog, select the catalog entity that makes available the products that the LPO model must rank.

  4. Under Tracking IDs, select the tracking IDs that correspond to the catalog entity chosen in the previous step. Catalog entities and tracking IDs have a one-to-one relationship, which you can view on the Storefront Associations (platform-ca | platform-eu | platform-au) page of the Coveo Administration Console.

  5. Under Search hubs, select the search hubs associated with the PLPs where you want LPO to optimize product ranking. The model uses only usage analytics events (clicks, add-to-carts, purchases) that originate from the selected search hubs to train its ranking algorithm.

    Tip

    If you’re unsure which search hubs correspond to your listing pages, check the originLevel1 value sent with your listing page queries. This value is the search hub identifier that appears in this dropdown.

  6. Under Train recommendations by, select whether you want the model to use Coveo Analytics data gathered from individual products or from product groups:

    • Products: Leverage usage analytics data from individual products. The model identifies content using each item’s unique content ID (for example, permanentid).

    • Product groups: Leverage usage analytics data aggregated from all products within the same group. The model uses grouping fields to identify the content to recommend (for example, ec_item_group_id), ignoring the items' unique content ID.

      Important

      You must configure product grouping before selecting this option. Products without a group ID will be excluded from the training dataset.

  7. Click Next.

  8. In the Name your model input, enter a meaningful display name for the model.

  9. (Optional) Use the Project selector to associate your model with one or more projects.

  10. Click Start building.

    Note

    On the Models (platform-ca | platform-eu | platform-au) page, under the Status column, check the status value in the model row. If the status is Inactive, model creation is still in progress. The status changes to Active when 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.

Edit an LPO model

  1. On the Models (platform-ca | platform-eu | platform-au) page, click the model you want to edit.

  2. On the subpage that opens, select the Configuration tab.

    The Configuration tab opens in view mode and is organized into three sections: Basic information, Training dataset, and Building parameters.

  3. To make changes, click Edit in the upper-right corner of the page. The sections become editable.

  4. In the Basic information section:

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

    • (Optional) Use the Project selector to associate your model with one or more projects.

  5. In the Training dataset section:

    • Under Catalog, review the catalog entity that the model was configured with.

    • Under Tracking IDs, you can change the tracking IDs that you want to use to train the model, but this must still correspond to the catalog entity chosen when configuring the model. A catalog entity and a tracking ID have a one-to-one relationship, which you can view on the Storefront Associations (platform-ca | platform-eu | platform-au) page of the Coveo Administration Console.

    • Under Search hubs, select the search hubs associated with the PLPs where you want LPO to optimize product ranking. The model uses only usage analytics events (clicks, add-to-carts, purchases) that originate from the selected search hubs to train its ranking algorithm.

      Tip

      If you’re unsure which search hubs correspond to your listing pages, check the originLevel1 value sent with your listing page queries. This value is the search hub identifier to select on that dropdown.

    • Under Train recommendations by, select whether you want the model to use Coveo Analytics data gathered from individual products or from product groups:

      • Products: Leverage usage analytics data from individual products. The model identifies content using each item’s unique content ID (for example, permanentid).

      • Product groups: Leverage usage analytics data aggregated from all products within the same group. The model uses grouping fields to identify the content to recommend (for example, ec_item_group_id), ignoring the items' unique content ID.

        Important

        You must configure product grouping before selecting this option. Products without a group ID will be excluded from the training dataset.

  6. In the Building parameters section, under Building frequency, you can change how often the model is rebuilt. The default and recommended value is Daily, but you can select a different frequency based on your needs and constraints.

  7. Click Save.

    Note

    Some configuration changes initiate an automatic model rebuild when you save the model. The Models (platform-ca | platform-eu | platform-au) page shows your model’s current Status. Model settings take effect only when its status is Active.

    For more information on Coveo ML model statuses, see the Status column reference.

Delete an LPO model

Note

If the model is associated with a query pipeline, make sure to dissociate the model from the query pipeline after deleting it.

  1. 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.

  2. In the panel that appears, click Delete.

Project association prompts

A machine learning model is a resource you can associate with a project. Resources associated with a project can require confirmation when you modify them. These confirmation prompts help prevent accidental changes that could affect a Coveo implementation.

Deleting a resource always requires confirmation, whether it’s associated with a project or not. When the resource is associated with projects, the confirmation prompt lists those projects.

Review model information

On the Models (platform-ca | platform-eu | platform-au) page, click the desired model, and then click View in the Action bar. For more information, see Reviewing model information.

"Status" column

On the Models (platform-ca | platform-eu | platform-au) page of the Administration Console, the Status column indicates the current state of your Coveo ML models.

The following table lists the possible model statuses and their definitions:

Status Definition Status icon

Active

The model is active and available.

Active

Build in progress

The model is currently building.

Building

Inactive

The model isn’t ready to be queried, such as when a model was recently created or the organization is offline.
Click See more details for additional information (see Review model information).

Inactive

Limited

Build issues exist that may affect model performance.
Click See more details for additional information (see Review model information).

Limited

Soon to be archived

The model will soon be archived because it hasn’t been queried for an extended period of time.
Click Delete to remove the model.
Learn more about archived models.

Archive pending

Error

An error prevented the model from being built successfully.
If it’s a temporary system error, check back soon. Otherwise, click See more details for additional information (see Review model information).

Note

If the model previously built successfully but is now in error, the last successful build version will continue to be used until the issue is resolved and a new successful build is completed. Any subsequent rebuild attempts will continue to fail until the underlying issue is resolved.

Error

Archived

The model was archived because it hasn’t been queried for an extended period of time.
Click Delete to remove the model.
Learn more about archived models.

Archived

Required privileges

The following table indicates the privileges required to use elements of the Models page and associated panels (see Manage privileges and Privilege reference).

Action Service Domain Required access level

View models

Machine Learning

Models

View

Organization

Organization

View

Search

Query pipelines

View

Edit models

Machine Learning

Models

Edit

Organization

Organization

View

Search

Query pipelines

View