It all begins with users linking their data from services like Spotify, Facebook or Zalando to the Hyde platform. This behavioral data allows conclusions to be made about musical tastes, travel or fashion preferences. In accordance with the General Data Protection Regulation, the services are obliged to make the data accessible. "Existing major market players are building data silos with our user behavior," says Kurt Uwe Stoll. "Facebook earns billions here. Users don't get a share of this value creation." So why shouldn’t you profit from your own data? Hyde makes it possible to monetize your own data, i.e. it can be sold specifically to corporate customers. A particular focus here, compared to competitors, is on data protection. Recent developments in privacy tech make it possible to generate insights from data without having to disclose individual specific behavioral details.
The underlying technology can easily be explained: Instead of sharing exact behavioral data with enterprise customers, only statistically aggregated information about user groups is transmitted. This prevents the disclosure of detailed information, e.g. who watched which content on Netflix at what particular time. Hyde is intended to trigger a change of mindset in the area of data sovereignty. Therein lies the greatest difficulty, aside from the technical challenge: explaining the scientific breakthrough in data protection technology to the average consumer. "The average user today simply cannot imagine that selling their data is not linked to the loss of their privacy. There is still a lot of explaining to be done. In addition, many people don't realize that personal behavioral data can be very valuable."
For companies, Hyde offers the opportunity to take customer understanding to an entirely new level. Here, Hyde offers the significant improvement of key business metrics. As an example, Uwe Stoll cites: "An e-commerce store wants to invest in new customer acquisition of its most profitable customers. Unlike existing technologies, Hyde can provide detailed insights into music tastes. For example, once the store has determined that profitable customers like to listen to downtempo techno, it can advertise in this precise segment by sponsoring an event. So Hyde combines benefits of discredited targeting with excellent privacy guarantees."
Another innovative character of Hyde comes from the wide range of data: "While individual providers only ever map small aspects of user behavior, our vision is to create a 360° mapping. We want to link data from a wide variety of areas of life, such as music, shopping or travel, and thus break new ground." In addition to the obvious benefits of improving business performance, Hyde's long-term vision is to use this data to train AI: "The biggest problem with machine learning for many years to come is still the availability of labeled data. Our long-term aspiration is to build the largest privacy-first dataset on human behavior. Next-generation AI agents can then be trained on that."
Hyde's goal: 10 million users in Europe over the next five years. As of July 2022, Hyde stands at 8500 users and 15 services offered from which data can be generated. The platform went live on 01/01/2022.
About the founder
Kurt Uwe Stoll is originally from Saarbrücken. After having received a diploma in business administration in Trier, he earned his doctorate in business informatics in the field of Semantic Web and Machine Learning at the University of the Federal Armed Forces in Munich. Here he was significantly involved in the development of GoodRelations. GoodRelations is a web ontology in the field of e-commerce, which was later integrated into the global Semantic Web standard schema.org of the major search engines. This technology is now used by billions of users daily.
Since 2014, he has worked in various executive positions in large and small companies in the field of Machine Learning / AI. Important stations here were the startup Import.io in London, Pro7Sat1Digital, his own startup in the area of deep reinforcement learning and e-commerce, PwC as Head of Privacy-Preserving Machine Learning Germany as well as RTL in the area of recommendation systems. Since 2016, there has been a further focus on privacy-preserving machine learning at the interface between data protection and artificial intelligence. This research field is the basis for the second startup Hyde, which deals with the privacy-compliant monetization of behavioral data.
