In the ever-evolving landscape of marketing and ad tech, the concept of „digital twins“ is gaining traction. According to a recent Ad Age column, companies are exploring the use of digital twins to better understand and target their audiences. But what exactly are digital twins, and how are they being utilized in the industry?
Essentially, a digital twin is a virtual representation of a real-world entity or system. In the context of marketing, a brand might use its own first-party data about high-value customers to create a digital twin. This digital twin is generated using sophisticated language models like OpenAI, Google, or Amazon, which analyze the data to create an archetype version of the customer cohort. This persona can then be used to identify new preferences, test campaign tactics, and optimize ad creative.
One key aspect of digital twins is the use of „synthetic data,“ which allows marketers to test and iterate on campaigns without using personal information. This approach not only protects consumer privacy but also enables sandbox testing and product development. Companies like AWS are proponents of synthetic data, as it provides a safe and efficient way to experiment with different strategies before launching a campaign.
However, there is a level of skepticism surrounding digital twins and synthetic data. Some critics liken the process to simulating an NFL season using a video game and expecting the results to mirror reality. While digital twins can provide valuable insights and predictive capabilities, they are not a perfect replica of real-world behavior.
In a separate development, streaming giant Netflix is making a strategic move to increase its ad-supported membership base. By defaulting some ad-free subscribers to the ad-supported plan, Netflix is following in the footsteps of Prime Video, which has seen success with a similar approach. This shift is aimed at driving more subscribers towards the ad-supported model, as Netflix looks to compete with the growing number of ad-supported streaming services in the market.
Meanwhile, in California, lawmakers and Big Tech companies have reached a compromise on compensating news publishers. The proposed legislation would allocate $242.5 million for newsroom funds and AI programs over the next five years, with Google committing a significant portion of the funding. However, some publishers are critical of the compromise, viewing it as a validation of Google’s monopoly power over the news industry.
Overall, the convergence of digital twins, ad-supported streaming, and news publisher compensation highlights the ongoing evolution of the marketing and tech landscape. As companies continue to innovate and adapt to changing consumer behaviors, the use of advanced technologies like digital twins will play a crucial role in shaping the future of advertising and media.