Mapping the Use of Artificial Intelligence for the Optimization of Paywalls in the News Media Industry: How Firms Are Taking Advantage of Machine Learning and Related Technologies to Increase Reader Revenue

The journalism industry has experienced a gradual increase in reader revenue strategies for news media, including memberships and paywalls. On the upside, these strategies allow journalism to generate income in other ways than through advertising revenues, and user demands can be directly met with high-quality content, as readers only pay for content they really want or need. To achieve this product-market fit, many companies have started using artificial intelligence (AI), a technology that allows paywalls to adjust to individual consumption habits and patterns. While big data techniques allow media outlets to analyze large amounts of data from each user very quickly, AI―including deep learning and natural language processing―builds upon this capacity to improve subscriber conversion and retention by personalizing their offerings and asking them to pay at just the right moment or using the best pricing strategy. Moreover, AI is useful in predicting cancellations, improving user experiences with editorial products, and other features. Its potentials have caused extant research to recommend further analysis about this phenomenon through more theoretical and practical studies. To do so, this chapter provides an overview of AI-optimized paywall initiatives, both built in-house by news outlets and from technological platforms that provide AI services to media companies (163 initiatives between 2015 and 2022).