AI-monetization-BeataMosór

AI Monetization | AdTech & Entertainment Industries

AI monetization isn’t a new concept 🤔

Beata Mosór (CLO @CIRCmodel.com) had the opportunity to discuss monetizing AI technology with Bartosz Ziółko during the Krakow Tech Summit 2024. They met in person after a couple of years apart, and their conversation was quite interesting that Bartek decided to record it!

They explored exciting topics, including:
💡 The use of AI in AdTech & Entertainment industries
💡 How AI can stimulate growth using the laws of behavioral economics
💡 How to increase user engagement and ROI using AI

It was great chatting and discussing such an important topic – where the money is in this AI game! 🤑

Here you can watch the video:

I discussed AI monetization in the AdTech & Entertainment industries at the Krakow Tech Summit 2024.

Here is a transcript:

Beata Mosór:

“When we talk about AI monetization, we primarily think of SoTA models like Facebook/Llama, Google/Gemini, Anthropic/Claude. But AI monetization has been happening for years, whether in AdTech companies (which I mentioned earlier – we’re talking about Meta and Google, but also companies like OpenX) that use Machine Learning and AI for targeted advertising, matching ads to user preferences, and behavioral economics. It used to be called Machine Learning, but now we know that these are often AI models tailored to user shopping preferences, as well as user behavior and behavioral models. Of course, the same models can be applied in the entertainment industry. Netflix, YouTube, and other media outlets (like Ringier Axel Springer, which operates in Krakow) also use technology to tailor ad displays and content to user preferences based on AI models. This has been happening for years, but now, thanks to the popularity of ChatGPT, which came out two years ago, people are talking more about AI than Machine Learning. However, the main difference between Machine Learning and AI lies in the statistical models used, which means the mechanics of operation and a certain level of ‘freedom for the model to think or act independently’ – Machine Learning models or, as they were often called, RPA (Robotic Process Automation) were more specifically programmed for specific automation, specific actions.”

Bartosz Ziółko: “But why do Facebook or Netflix earn more thanks to AI? Where does that money come from?”

Beata Mosór:

“It’s primarily linked to the ease of creating ads and adapting them to user preferences. This results in higher ROI, higher conversion rates for ads, greater advertiser satisfaction, and thus higher spending – advertisers spend more on ads on these platforms to reach their users. This spending increases when users spend more screen time, for example, on Netflix, YouTube, Facebook, or Instagram, creating and consuming content. Therefore, when we talk about content adaptation, we’re thinking about how to keep users engaged with our platform for as long as possible. A key KPI when we consider traditional media, traditional television, was screen time. Traditional TV wanted users to spend as much time as possible in front of the screen, and they succeeded: In the 50+ demographic in small towns, we’re talking about 14 to 16 hours of content consumption, or user presence with traditional television screens. When large streaming and media platforms entered the digital market, wanting to replace traditional media, their main KPI was also screen time – user presence, their interaction with the platform. The first thing these platforms focused on was user engagement, striving for maximum engagement and screen time within the platform. Now, AI is used to monetize this by adapting content and ad models to user preferences, behavioral economics, and engagement.”

AI monetization isn’t a new concept. It’s been happening for a while, but it’s becoming more and more important as AI technology matures. I see several key areas where AI monetization is happening:

  • Firstly, we have the use of AI in AdTech and the Entertainment industry. AI is being used to personalize ads and to create more engaging content, and that’s driving a lot of revenue in those areas.
  • Second, we’re seeing the use of AI to stimulate growth by leveraging behavioral economics. Understanding user behavior and applying AI to personalize experiences can lead to increased engagement and conversions.
  • And finally, we have the use of AI to boost user engagement and increase ROI. AI can help companies optimize their marketing efforts, create more personalized experiences, and ultimately, improve their bottom line.