Top AI Use Cases in Media and Entertainment

Media and entertainment companies are facing increasingly competitive and uncertain markets which are driving the need to reduce operating costs and simultaneously generate more revenue from delivering content. Enter: AI.

Content consumption behaviors are becoming increasingly complex and evolving more rapidly than ever.
 Data science, machine learning, and AI represent huge opportunities for companies who are prepared to invest in long-term, viable solutions.

Just look at the way that companies like Google, Amazon, and Netflix affected the media and entertainment space with their data-driven business models. Using advanced data science and AI allows them to understand and create value for customers by presenting content that they might like and that might be relevant to them.  But this change doesn’t happen overnight; full potential comes through gradual evolution into a truly data-powered organization.

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The media and entertainment sectors have always dealt with data – ratings, subscription numbers, etc. But making data-driven decisions is no longer about just analyzing past data; it focuses on high quality predictions based on real-time input from all data sources across the organization.

High-value Use Cases in the Media and Entertainment Industry

Better Recommendation Engines: Recommendation engines have been widely used in the media industry to predict what kind of information or content customers would be interested in. Companies can combine structured and unstructured data and machine learning methods to match people and content, thus improving the relevance of content recommendations and efficiency of content distribution.

With leading tech media players such as TikTok and Netflix venturing more and more into AI-based interactive and smart content, we’re likely to see a shift from simpler content recommendation systems to an entire AI-driven personalized content experience.

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Hyper-targeted advertising: The possibility of combining data from different sources in one place can allow companies to look at their customers as a whole and deliver unique, hyper-targeted offers. In TV and advertising, this is evoked in the concept of addressability: the ability to interact with consumers based on what their specific choices reveal about their interests and preferences. Hence, thanks to AI and ML, media and entertainment companies can predict churn rates more accurately, place advertising at the right time and in the right place, and have more appropriate, personalized offers to increase conversion.

For instance, some streaming platforms and leading film studios are already experimenting with ML-based personalization of movie trailers that emphasizes specific elements that they know a given target audience would like, delivered on the platform that they most frequently use.

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Real-time predictive modeling for anticipating demand and segmentation: In the constantly evolving media and entertainment sector, looking back at consumers’ past activity often isn’t a good indication of what they will do next. Instead, real-time prediction based on current trends and behaviors from all data sources is key. Predictive modeling in particular will aid media and entertainment companies not just by allowing them to react to consumers in real time, but also to anticipate their behavior, influencing long-term investments, for instance, what kinds of movies in which consumer micro-segments will be popular two years from now.  In addition, companies can make predictions about which customers are more likely to view a given type of content, and what device they will be using when viewing it.

Other use cases:

  • Residual payment forecasting to model how talent is compensated based on content distribution across various channels.
  • Automated reporting in newsrooms to free up journalists’ time for more meaningful work.
  • AutoML for casting, HR, and administrative tasks.
  • …and more.

 

AI for Media & Entertainment

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Dataiku for Media and Entertainment

Faced with fierce digital competitors and the ever-growing amounts of data generated by media users everyday, media and entertainment organizations need ever-smarter tools to stay in the game. Enterprise AI platforms open the door to drive media companies in this fast-paced world to new heights.

Dataiku offers a robust predictive modeling solution, capable of accepting data from diverse sources, cleaning the data, and then using powerful algorithms to understand what customers are going to do given specified parameters. Dataiku’s advanced data wrangling features can be used to combine structured (e.g., web analytics) and unstructured (e.g., social media posts) data sources to get a 360° view of clients.

Dataiku lets you use and compare a broad range of algorithms, from simple linear models to complex ensemble methods, to build the best predictive media solutions for the company’s needs. Post-modellng, the software’s automated deployment and automation features enable companies to quickly move their models to production and deliver to their consumers the best possible content in the most effective way.

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