The most important AI use cases from newspaper publishers – which ones are you already using?

When thinking of AI for newspaper publishers, the first thing that comes to mind is editorial use cases such as robotic journalism. However, many exciting AI use cases exist in processes that are not directly related to the creation of the actual product. In the reader market in particular, there is a wealth of user data that can be profitably analyzed and used to optimize customer relationships. The two most important use cases in the reader market are predicting conversions and cancellations. 85% of the publishers surveyed consider these to be very relevant or even critical to success.

By 2024, more than 90% of publishers plan to implement these approaches at their sites. The fact that not only the technical accuracy of the algorithm but also the correct use of the results plays a major role in churn prediction was discussed in an earlier article The use of chatbots in customer service is rated as least relevant. The individualization of paywall control and the individualization of prices (market-based pricing) are targeted by 75% and 64%, respectively, by 2024. All use cases in the reader market area are only actively in use at a few publishers so far. The most widespread use case is Market-Based-Pricing with 27% of publishers.

Content writing is the core area of newspaper publishers and it is here that the use of AI is viewed with great skepticism. Content creation comes with a lot of journalistic responsibility and automated content creation is already being abused by rogue companies (keyword fakenews). This is one reason why automated content creation (robot journalism) was rated with the lowest relevance in the content production section.

Nevertheless, more than half of the publishers consider this use case to be at least very relevant and 69% of the publishers plan to implement it by 2024. In particular, the creation of highly data-driven and standardized content such as soccer reports, stock market news, and event announcements has established itself here. However, we are still a long way from AI-assisted creation of all content. Currently, the most widespread is the automation of content planning, e.g. via news/social media monitoring or the automated analysis of historical content for topics with post-movie potential. Here, 38% of publishers already use corresponding tools. The third area is the automated adaptation of finished content, such as the generation of article summaries. You can try out for yourself interactively how the automated shortening of article texts works with our web tool.

The third area covered in our study is content playout. Here, AI offers an incredible array of opportunities in digital to show individual readers the right content, at the right time, and in the right format. Companies like Netflix have proven that they can use personalization to deliver a unique selling proposition for a product and tremendous value to the customer.

The study results show that personalization of newsletters and websites are also among the most relevant AI use cases at newspaper publishers. Highberg (formerly known as Schickler) is also currently focusing on the topic of personalization. As part of the DRIVE project, we are developing personalization algorithms together with 20 regional German and Austrian regional publishers. We believe that personalization is the biggest lever for increasing reader engagement and thus conversion/retention with digital subscriptions. Even apart from personalization, all other use cases in content playout are highly relevant for publishers and their implementation is firmly planned by 2024. This includes the improved presentation of supplementary content via the automated placement of links in articles, the automated creation of topic pages or the highlighting of interesting archive content. AI can also take a lot of the work out of moderating reader comments for publishers. In addition, AI also helps make content more accessible, for example, by allowing it to be automatically extended into audio pieces via text-to-speech.

Newspaper publishers are aware of the relevance of AI and have identified the most important use cases. They have also set ambitious goals to implement a large number of new use cases in the next few years. This poses major challenges, since in addition to the obvious great technical complexity of AI, major strategic, organizational and cultural changes often have to be mastered for successful deployment of the use cases. 

Highberg (formerly known as Schickler) has already supported a large number of newspaper publishers and other media companies in the development and implementation of various AI use cases. If you would like to know more and benefit from our experience, please feel free to contact us.