When a potential customer engages with your digital property, every second counts in making a relevant and memorable experience. Rich search and discovery experiences win customer loyalty and provide information or products that they are likely to engage with. Algolia’s platform can easily leverage insights from multiple data sources to superpower personalization of the search experience. With our partner Adobe, we have focused on bringing in event data from Adobe Launch into Algolia to understand what behaviors and actions customers have taken both online and offline. These events come anonymized into Algolia, and are used to understand what items will be most relevant to each customer. For example, we may get event data that indicates a person has clicked on multiple Instagram ads for brownie mix. Later, when they go to the search bar and start searching “b-r-o-w”, we would know to rank brownie mix higher than a brow pencil or brown pants. Every second matters in keeping a user on your site, and having as much context as possible helps businesses understand affinities and interpret intent.
Our previous article walked you through various data ingestion methods, to get you up and running in Adobe Experience Manager (AEM). This article shows you how to personalize your users’ search results by capturing their click-through and conversion events.
Adobe Launch is a tag manager and distribution container, allowing digital teams to collect user behaviors on their web properties and to leverage those events in their workflows. Launch adds a Javascript onto a page as the customer browses the site. The script executes and binds launch rules on actionable elements on the page, such as a search or click.
Launch allows marketers to manage tracking scripts in one place that they want to add to the page with a form-based experience. For example, a marketer can create a Launch rule to send a user, page, and browser properties when an event occurs on a button, for example,, click or mouse over.
We built an Algolia Insights extension for Adobe Launch, which provides two pre-packaged Algolia Insights events (‘click after search’ and ‘convert after search’) wrapped in an Adobe Launch extension. This code is inspirational (not supported), but can give you an idea on how to get started and add more events.
The Extension dashboard provides a way to browse available Launch extensions for installation. It also allows for extension configuration based on your needs.
The Algolia Insights extension requires configuration before use.
These two events – ‘click after search’ and ‘convert after search’ – are created as an “Adobe Action”. These actions require inputs such as query ID, product ID, position, and user ID, which we can get from the search results. We can add these properties directly into the DOM, on the HTML element that the action can fetch. User ID comes from the API call.
Launch rules are needed to use the Algolia Insights actions.
The Algolia Insights API is wrapped in a Launch action. This action must be configured with the following:
The documentation provides more details on this action.
The Algolia Insights API is wrapped on a Launch action. This action requires the following configuration:
Additional properties are required but pulled from the url. The Algolia Hit widget will need to add the query strings on the actionable links. The documentation provides more details on this action.
When one of these user events takes place on the page, Launch will send the events and appropriate metadata back to Algolia, and our search engine will use the information to re-rank products in a way that reflects trends and personal affinities. Above, you can see an example of how we might use specific events to define the search personalization strategy within Algolia.
We welcome you to build off of our helper and share with us how you are leveraging Adobe Launch events to drive dynamic re-ranking and search personalization in Algolia! Reach out to us at adobe-algolia-solutions@algolia.com.
Check out the other blogs in the ‘Algolia x Adobe Integrations’ series, on how to ingest your AEM content into Algolia, and how to leverage Adobe Analytics metrics for your search ranking.
Sajid Momin
Senior Director, Integrations @ AlgoliaDebanshi Bheda
Global Alliances Director - AlgoliaPowered by Algolia AI Recommendations
Micah Garside-White
Solutions Engineer @ AlgoliaDebanshi Bheda
Global Alliances Director - AlgoliaDebanshi Bheda
Global Alliances Director - AlgoliaJon Silvers
Director, Digital Marketing