Nico Wilfer, Deputy Chief Digital Officer- Frankfurter Allgemeine Zeitung
Most large news portals have long since stopped focusing on the goal of maximum reach for advertising purposes. The focus for news companies lies more and more on building a functioning funnel for their sustainable digital subscription business.
With those still increasingly important business models in mind, they need not only reach but qualified reach. The goal remains to monetise users, but it’s especially focused on making them paying customers in the end. On the long road from converting a user during the first visit to paying customer, it is important to concentrate on user engagement.
But first, what does “qualified reach” mean? Qualified reach is reach within target groups that can become loyal and engaged, identify with the brand, and, ultimately, are more likely to become paying customers.
It is easy for us to prove the more committed readers are to our platform and its apps, the greater their willingness to pay. A user with 10 or more visits per month is three times as likely to become a paying customer as a user with only four to nine visits. We see that especially converting mobile users to app installs pays off because once people use the app, they are much more engaged.
Users’ loyalty can be measured and achieved in many different ways. An exciting model of the Financial Times is presented in this INMA article.
So, what does it mean to focus on qualified reach for the product strategy? First of all, qualified reach is reach that cannot be achieved with click-baiting. The focus on acquiring loyal users instead of just generating traffic is in itself a goal that pays off with the brand core and strong journalism.
In terms of product development, it means we need to focus throughout the user journey on making readers stick to our brand — from reducing bounce rates on article pages to increasing subscription lifetimes.
Following a strategy to acquire more loyal users — and keep them! — the Frankfurter Allgemeine Zeitung has been experimenting with Artificial Intelligence-based, personalised recommendations for a year now. We see personalisation features as a great opportunity, especially for general interest publications with a broad range of topics and a three-digit number of articles per day.
On many news sites, content recommendations are still purely context-based because we have learned this makes a lot of sense from an editorial point of view. At the same time, it reduces bounce rates and increases traffic overall. The benefits for the reader, however, are limited. For example, the lists do not even learn what the individual user has already read.
More intelligent personalisation features enable us to show readers products tailored to them in times of fragmented and partly brand-independent media usage. These personalised features are intended to increase the engagement of non-customers and turn them into loyal customers, but they are also a great opportunity to orient those already-paying subscribers who could consume much more content with a freemium model, for example.
Readers with little time can quickly find what interests them instead of digging through hundreds of articles. At the same time, it remains open to users to become inspired and fully informed by browsing through full streams or editions.
So far, our new personalisation features pay off when it comes to increasing user loyalty. We see that readers convert to registered users to access personalised recommendations. They also have a higher overall commitment (both more visits per month and more page impressions per visit) if they use the recommendations, and, in the end, they are more likely to subscribe.
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