Heise Online Increases Reader Loyalty with Data-Driven Customer Audience Management

Like many other businesses, publishers and media companies have also faced challenges posed by COVID-19. While they may have benefitted from an increased interest in news over the past year, it remains critical for publishers to target their online offerings more efficiently. More than ever, it is important to identify people who are potentially willing to pay for the editorial content and then to specifically target them with relevant information.

Heise Medien is one of the leading publishers in IT and tech news in the German language. The media company has been relying on paid digital content offers for some time. The publisher has now designed and implemented a customer audience management system for heise online, the leading online portal for tech news in Germany, together with Mapp and Dymatrix Consulting Group. In a matter of months, they were able to develop an innovative infrastructure based on the technical framework provided by Mapp that can be used to segment users and personalize marketing activities with the aim of strengthening reader loyalty.

INITIAL RESULTS: SUBSTANTIALLY HIGHER CLICK RATES

• Article recommendations in the right pane of the webpage have average click-through rates of 8x higher than conventional banner ads in the same position
• Improved click rate by 26% on average for paid content recommendations below freely accessible articles
• Editorial and marketing teams at heise online have a reliable overview of what content is performing better and what is performing less than adequately – and they can adjust their activities accordingly

We were able to seamlessly connect to our existing analytics and data setup with the new system thanks to the immediate availability of raw data. And within a few months, we established an innovative infrastructure that links user- and content-based recommendations that allows us to personalize activities on our website with just a few clicks. I am confident that we will continue to improve the user experience of our digital offering with the help of our partners and, in so doing, the customer engagement of our readers in the long term.

Knut Pape

Web Analyst - Heise Medien

THE STARTING SITUATION

At the beginning of 2019, heise online launched heise+, a flat rate online magazine subscription providing coverage of IT and technology news, including exclusive content. Since then, their content has been expanding regularly. Explaining Heise Medien’s goal, Michael Diestelberg of Mapp says: “For real-time user centricity, we needed to develop a data-based system that could predict the affinity of readers and potential user clusters for paid content calculated, as well as recommend targeted editorial content to them in the next stage.”

An interdisciplinary team from Heise Medien set up the customer audience management system in just six months. Internal web development, marketing, product management, and other departments were involved in the implementation, in addition to the project’s core team from Heise Medien’s data center. Three employees each from the technology service providers Mapp and the Dymatrix Consulting Group contributed their expertise as well. The system was launched in February 2020 as a minimum viable product, or MVP, which divides users into groups and identifies their preferences. The content recommendation system, which was based on this, went live at the beginning of May 2020.

HOW IT WORKS

Michael Diestelberg explains: “The customer audience management system calculates the affinity of each heise online user for the paid content product heise+ based on their individual behavior.”

Users are also divided into specific groups based on the conversion probability for each individual page impression. The calculation is performed or updated each time the page is viewed. Based on raw data provided by Mapp, several data models work in the background.

Mapp’s customer intelligence is used for data acquisition and processing. All the processed information is first-party data that has been pseudonymized, as data protection is a top priority at Heise Medien. User groups are defined based on real-time data and a model for calculating product affinity is developed and continuously optimized. This involves a separation between users who are and are not interested in the heise+ paid content. Articles based on their level of recommendability are also determined for each user individually.

The next stage involves the targeting of clusters and affinity groups. The information gathered through the customer audience management system is transferred to Mapp Intelligence, which then takes over the control of campaigns in real-time. Website visitors who have a high affinity for heise+ are shown subscription ads on the homepage, as well as with individual articles. In addition, paid articles that match individual user behavior are displayed as editorial recommendations in the right pane of the webpage and in other areas.

In turn, the campaign response is added to the conversion calculations. In this regard, an important source of information is the type and performance of the recommended articles. “ The system enables heise online to determine and play out personalized next-best content in this manner,” says Michael Diestelberg. “The goal is to improve usage depth and create relevance for readers through personalized, targeted content.”