The evolution of AI in entertainment marketing

With all of this content comes a massive amount of data. The unstructured audio and video that is contained in film, TV or influencer videos can range from the expressions of the people on screen to objects in a scene. The availability of this data is transforming entertainment marketing today, allowing marketers to predict the outcomes of brand integration campaigns before they even begin.

Merging entertainment with data is not a new concept. Both content creators and marketers have always aspired to understand what will resonate with audiences and keep them engaged. Focus groups and screen tests have been happening in Hollywood for decades. The field of entertainment marketing is no different. As more marketers look to get inside content, there’s a strong desire to understand how to create authentic integrations that will move a story or influencer video forward – and products off the shelves.

Over the last two years, networks, platforms, brands, content creators and influencers have all utilized AI to refine their marketing strategies. For example, AI has been tasked to help combat influencer fraud, which remains a growing concern for the industry as fake followers abound. AI’s uses don’t stop there. Netflix boldly removed people-based recommendations from its platform late last year and shifted solely towards AI-based ones. Those are significant milestones for marketers actively leveraging AI but are just the tip of the iceberg in terms of how it can be leveraged in the future.

The promise of deep learning

The real promise of AI lies within deep learning algorithms that have the ability to think like a human but scale like a machine. Deep learning can digest, asses and contextualize unstructured data quickly to derive actionable insights. Through deep learning, AI can analyze millions of pieces of content in the time it would take humans to analyze a dozen, and at the same time be able to find patterns and insights that most humans would miss. This brings benefits to both content creators and marketers. Creators will be able to use insights from neural networks – the algorithms that make deep learning possible – to understand which settings, storylines, characters, or topics engage audiences most. Marketers will be able to use deep learning predictive capabilities to gain greater insight into the creators or shows that will deliver the greatest ROI. Brands are already benefitting from the application of deep learning to influencer marketing campaigns, realizing tangible benefits such as increases in click-through-rates of over 170%, higher engagement rates within their campaigns, or even 10x increases in subscription conversion efficiency.

Even more, customized deep learning algorithms are being trained to predict the specific outcomes a brand is most interested in achieving. Gone are the days of blindly hoping for good results or being satisfied with a vanity placement. Marketers are now using AI to predict what will work best for their specific products, and to more accurately measure the value of influencer marketing and brand integration relative to other forms of marketing.

Ultimately, the objective of brands and creators for entertainment marketing is the same as it always has been – predicting which programming will keep viewers glued to the screen and identifying the right integration opportunities that will drive sales of their products. To make better sense of the content at their fingertips, marketers are increasingly turning to deep learning algorithms. It is the only way they’ll be able to accomplish every marketer’s dream: predicting whether a campaign will be successful before it starts, instead of understanding its impact after the campaign has ended.

Ricky Ray Butler, CEO, Branded Entertainment Network

Telephone: 310.342.1500

Contact: info@bengroup.com

@BrandEntNet