Enable personalization¶
The personalization service is based on a client-server architecture. To enable it, you must set up authentication parameters that you receive from Ibexa.
Get authentication parameters¶
First, either you or another Ibexa user responsible for managing the Ibexa DXP
instance must request access to the service.
Set up customer credentials¶
When you receive the confirmation email, add the credentials to your configuration.
In the root folder of your project, edit either the .env or .env.local file
by adding the following lines with your customer ID and license key:
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Configuring user credentials for different customers
If your installation hosts multiple sites with different customer IDs, for example, to provide separate recommendations for different language versions of the store, you can store all credentials in the same file:
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Configure Personalization¶
The Personalization package adds a personalization solution to Ibexa DXP and communicates with the Personalization server.
Its job is to track the way visitors use the website and recommend content based on their behavior.
For more information about integrating the Personalization service, see Developer guide and Best practices.
Set up item type tracking¶
For the recommendations to be calculated, apart from visitor events (CLICK, BUY, etc.), the Personalization server must receive a list of item types that are tracked.
You define item types to be tracked in the config/packages/ibexa.yaml file.
The content is then initially exported by a script.
After this, it is synchronized with the Personalization service every time a change
occurs (using any method that triggers the event).
The Personalization configuration is SiteAccess-aware. If your installation hosts multiple sites with different customer IDs, for example, to provide separate recommendations for different language versions of the site, provide the credentials that correspond to each of the sites.
The configuration can resemble the following example:
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Authentication
For data exchange purposes, basic authentication is enabled by default. To change this, contact support@ibexa.co. For security reasons, store the authentication credentials in the ENV file, and do not commit them to the Version Control System. Then, use environment variables to pull them into the YAML file.
| Parameter | Description |
|---|---|
host_uri |
A location where the site's REST API can be accessed. This is where the Personalization server imports items from. |
authentication.customer_id |
A customer ID related to the supported SiteAccess. |
authentication.license_key |
The Personalization service's license key. |
export.authentication.method |
Authentication method used to get access when importing items. |
export.authentication.login |
The credential used when importing items. |
export.authentication.password |
The password used when importing items. |
included_item_types |
A list of alphanumerical identifiers of item types on which the tracking script is shown. |
random_item_types |
A list of alphanumerical identifiers of item types that are returned when the response from the server contains no content. |
Enable tracking¶
The Personalization client bundle delivers a Twig extension
which helps integrate the user tracking functionality into your site.
Place the following code snippet in the <head> section of your header template:
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How tracking works
For more information about tracking in general, see Tracking API and Tracking with yct.js.
Check whether the bundle provides REST data¶
You can verify the import controller of the bundle by calling the local API.
Use the Accept header; you may need to add an Authorization header if authentication is required.
To check whether the content endpoint is working as expected, perform the following request:
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Additionally, check whether the contenttypes endpoint is working with the following request:
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The content endpoint returns one item and the contenttypes endpoint returns many.
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Export item information¶
To get recommendations you must first export the item information to the Personalization server.
After you define item types to be tracked and recommended, start the full export.
You do it with the ibexa:personalization:run-export command.
If your installation hosts only one SiteAccess, run the following command to export your data:
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If your installation hosts multiple SiteAccesses with different customer IDs,
you must run the export separately for each of the <site_access_name>/<customer_id> pairs.
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The bundle exporter collects all content related to the <site_access_name>/<customer_id>
pair and stores it in files.
After finishing, the system sends a POST request to the endpoint and informs the
Personalization server to fetch new content.
An internal workflow is then triggered, so that the generated files are downloaded
and imported in the Personalization server's content store.
The export process can take several minutes.
Re-exporting modified item types
If the item types to be recommended change, you must perform a new full export
by running the php bin/console ibexa:personalization:run-export command again.
Check export results¶
There are three ways to check whether content was transferred and stored successfully in the Personalization server:
REST request to client's content store¶
To get the data of an imported item you can request the following REST resource:
GET https://https://admin.perso.ibexa.co/api/<your_customer_id>/item/<your_item_type_id>/<your_item_id>
This way uses basic authentication. The username is the customer ID and the password is the license key.
Example response
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Personalization backend¶
In the Back Office, go to Personalization > Import and review the list of historical import operations to see whether a full import was successful.
Subsequent content exports¶
The Personalization server is automatically kept in sync with the content in Ibexa DXP.
Every time an editor creates, updates or deletes content in the Back Office, a notification is sent to https://admin.perso.ibexa.co. The personalization service also notifies other components of the Personalization server and it eventually fetches the affected content and updates it internally.
Display recommendations¶
Client-based recommendations
Recommendations are fetched and rendered asynchronously, so there is no additional load on the server. Therefore, it is crucial that you check whether the content export was successful, because certain references, for example, deeplinks and image references, are included. If the export fails, the Personalization server does not have full content information. As a result, even if the recommendations are displayed, they might miss images, titles or deeplinks.
To display recommendations on your site, you must include the asset in the template using the following code:
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This file is responsible for sending notifications to the Recommendation API after the user clicks a tracking element.
To render recommended content, use a dedicated showRecommendationsAction() from the RecommendationController.php:
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Tip
To check whether tracking is enabled on the front end, use the
ibexa_personalization_enabled() Twig function.
You can wrap the call to the RecommendationController with:
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Parameters¶
| Parameter | Type | Description |
|---|---|---|
contextItems |
int | ID of the content you want to get recommendations for. |
scenario |
string | Scenario used to display recommendations. You can create custom scenarios in the Back Office. |
outputTypeId |
string | Item type that you expect in response, for example, blog_post. |
limit |
int | Number of recommendations to fetch. |
template |
string | Template name. |
attributes |
array | Fields that are required and are requested from the Personalization server. These Field names are also used inside Handlebars templates. |
You can also bypass named arguments with standard value passing as arguments.
Custom templates
To use a custom template for displaying recommendations,
ensure that it includes event_tracking.html.twig:
{% include '@IbexaPersonalization/event_tracking.html.twig' %}.
Recommendation responses contain all content data that is requested as attribute in the recommendation call. This response data can be used in templates to render and style recommendations.
For example, the following GET request should deliver the response below if the content Fields were previously exported by the export script.
GET https://https://reco.perso.ibexa.co/api/v2/<your_customer_id>/someuser/popular.json?contextitems=71&numrecs=5&categorypath=/&outputtypeid=<your_item_type>&attribute=name,author,uri,image
Example response
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Modify recommendation data¶
You can retrieve data returned from the Personalization server and modify it before it is shown to the user.
To modify recommendation data, subscribe to RecommendationResponseEvent.
See Event/Subscriber/RecommendationEventSubscriber.php for an example:
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The -10 refers to priority, which must be negative so this action is performed
before the main subscriber is run.
Image variations¶
Displaying image variations is not supported out of the box.
You can work around this limitation by creating a template (based on recommendations.html.twig).
To access a specific image variation through API, add the image parameter to the
request URL with the name of the variation as its value.
For example, to retrieve the rss variation of the image, use:
/api/ezp/v2/ibexa_recommendation/v1/contenttypes/16?lang=eng-GB&fields=title,description,image,intro,name&page=1&page_size=20&image=rss
Troubleshooting¶
Logging¶
Most operations are logged by using the ibexa-personalization Monolog channel.
To log everything about Personalization to dev.recommendation.log, add the following to the ibexa.yaml:
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You can replace info with debug to increase verbosity.
Set up user roles and permissions¶
Depending on your requirements, you may need to set up edit and view permissions
to grant users access to recommendation settings that relate to different SiteAccesses
and results that come from these websites.
Configure recommendation logic¶
When you enable the Personalization, you can go back to the Back Office, refresh the Personalization dashboard and proceed with configuring the logic used to calculate the recommendation results.