London/Berlin, 15 June 2021 – Heise Medien is one of the leading publisher for IT and Tech news in German language. The media company has been relying 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.
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 and technology have been expanded regularly. 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 with three members. 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.
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. The goal is to improve usage depth and create relevance for readers through personalized, targeted content.
Heise Medien plans to regularly expand the comprehensive setup, in particular the recommendation management based on similar user data, to strengthen reader loyalty. The information captured by the system can also be used for further analysis.
The implemented technology responds to several million queries every day. It can achieve very fast response times, despite the level of complexity of the data processing. The system can provide enough information after just a few page views, even for new visitors, which is necessary for basic recommendation management, cluster predictions, or the suggestion of next-best content. It provides the editorial and marketing teams at heise online with a reliable overview of what content is performing better and what is performing less than adequately – and they can adjust their activities accordingly.
The success of the system is illustrated by the initial metrics. “We can observe significantly increased click-through rates (CTR) and conversion rates (CVR) for users with medium and high affinity for the paid content offering,” confirms Knut Pape, Web Analyst at Heise Medien. “The CTR doubles on average compared to a non-personalized user approach and compared to the previously non-segmented campaigns. We have also measured significant increases in CVR since the system was introduced (+94%).”
Recommendation management is also working successfully. 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. The rate can be even higher depending on the article and specific topic. As a result of personalization, the click rate for paid content recommendations below freely accessible articles improved by 26% on average.
“Mapp’s technology was extremely helpful in developing our customer audience management,” comments Niklas Grocholl, Project Leader Customer Audience Management at Heise Medien.
Knut Pape comments further: “We were able to seamlessly connect to our existing analytics and data setup with the new system thanks to the immediate availability 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.”
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