More Reach by Building Loyalty

More Traffic Through Stronger User Retention

Two pieces of news from the Google universe have stood out in recent weeks: First, the new AI Overviews nachweislich zu Lasten der Besuche bei Nachrichtenmedien.. Then, last week, it was announced that Google is also testing AI-generated content inDiscover KI-Inhalte
So the question is: What should publishers do?
In many of our recent conversations, it has become clear that publishers are turning their attention more and more toward their organic, or direct, user base. The goal: to foster stronger user relationships and boost engagement. One very effective method is the use of content recommendations. These not only generate more pageviews but also extend session duration and user journeys. If implemented well, recommendations can help fill the conversion funnel — and if the content offered is truly relevant, even build loyalty and increase return visits.

There are many ways to use content recommendations: under articles as reading suggestions, embedded as boxes within article bodies, on automated overview pages, or as parts of the homepage. An added benefit: automation. Done right, it relieves the editorial team of the time-consuming task of manual curation.

When introducing content recommendation tools or systems, it pays to proceed thoughtfully. My advice is to consider the following eight key points:

1. Define your product strategy
Content recommendations must fit your overall product vision and meet high standards of quality. The technology should be easy to implement. Standard adtech tools are often a poor choice — due to outdated links, unclear editorial quality, or irrelevant recommendations.

2. Real-time control
To maximize impact, algorithms must react in real time — to newly published articles, user behavior, and demand trends. What’s recommended should always reflect the most up-to-date and relevant content.

3. Define your recommendation scenarios
You will likely want to use several types of recommendations — depending on the placement. For example, contextual suggestions below articles, trending topics on automated overview pages, or personalized content on the homepage. Make sure your system allows you to control these separately and flexibly.

4. Audience targeting
User segmentation is one of the most important performance levers. In practice, subscription status often makes the biggest difference. For subscribers, show the premium content with the highest engagement. For non-subscribers, highlight articles that convert well and help move users through the funnel.

5. Content segmentation
Be strategic about the pool of content from which recommendations are drawn. Which sections should be prioritized? Which ones should be excluded? And how relevant should the content be in terms of timeliness? Define how fresh (e.g., in hours) articles need to be per placement. Daily relevance is often a must.

6. A seamless user experience
Don’t compromise on UX. Fast-loading widgets and real-time deduplication are crucial — to avoid showing the same article multiple times on the same page. Content modules should load quickly and blend in visually.

7. Layout considerations
Design should match the style of your site. Decide how many recommendations to show in each placement (more is not always better), and optimize for mobile users who shouldn't have to scroll endlessly. Ask yourself: Is a header really needed? Does the author profile link add value? How long should the snippet text be?

8. Work with performance data
Track impressions, visibility, and click-through rates for each recommendation placement. Once you’ve gathered baseline data, you can start optimizing: adjust targeting, tweak the algorithm, test new placements — and repeat.

By putting these eight points into practice, you not only create a smart, automated content delivery system, but also significantly improve the user experience and perceived content value. If users know that a specific part of the page always offers the most relevant or interesting stories, you’re encouraging a habit — and building true loyalty over time.

Good luck — and keep testing!