Create unique navigation experiences in your site by guiding users to the articles they are most prone to read.
Scenario Description
Printed newspapers offered a clear and structured presentation of their daily content. Readers could easily gauge the full extent of an edition, deciding how much to read with the certainty of a finite number of pages.
In contrast, digital editions often rely on static homepages and recirculation modules, which rarely capture the full scope of what’s published. As a result, frequent readers may feel they’ve seen everything within minutes, while much of the content remains hidden beneath the surface.
To bridge this gap, personalized recommendations have proven highly effective, increasing click-through rates by up to 100%. While ranking systems weigh multiple factors to determine relevance, a personalized engine prioritizes a reader’s historical interests—leveraging past site navigation to surface the most engaging content.
On top of that, previously read articles are excluded from recommendations, ensuring a dynamic and ever-evolving feed.
How to Set it Up
As a replacement of an existing module
- Navigate to Experience Manager and click on New experience, filter by Recommender family and Inline format and select any. Experience edition screen will open up.
- Use the dropdown for the preview url to navigate to the page where the module to be replaced is shown.
- Click on the target icon to activate highlighting mode and select the module to be replaced. Use the breadcrumbs above to refine the selection if needed.
- Once the proper element is selected, use the dropdown options and the bottom and click on “Generate both” (CSS selector and layout).
- Once both have been generated, confirm they look good or tweak what’s needed, and click on Confirm. Check the preview to make sure that everything looks as it should.
- On Content tab, click on the configured Recommender feed’s three-dot options → Edit, and select “Personalized” as Engine
- Configure the rest of parameters (Time Window, number of articles, …) as needed.
- On targeting tab, add the filter of “Visitor loyalty” as equal to “Loyal” or “Lover”. Less engaged users do not hold enough data to generate meaningful personalized experiences for them.
- Add any other targeting required, and publish. Before publishing, you can just create it and test it in multiple devices by sharing the url generated when clickin on “Open in browser” option on preview’s three-dot options. Different devices should show different content.