The Evolution of Entertainment Marketing:
Personalization and Dynamic Creative Optimization
It’s no secret that working from home, new trends and technologies like AI powered algorithms, smartphones and the rise of streaming services have created a disconnect from traditional media and made audiences more receptive to marketing messages delivered in more relevant, authentic and interactive ways, consistent with the platform trends where they are consuming content. Today, as a result of the pandemic, everyone from Boomers to Millennials to Gen Z are consuming more content than ever before and relying upon their devices around the clock to both inform and escape.
This creates a huge opportunity for studios and brands to engage an audience with targeted analytics, data and dynamic creative content to facilitate conversation with culturally relevant campaigns that push entertainment properties beyond the screen and into audience’s everyday lives and conversations. To do so involves rethinking how creative content campaigns combined with earned, owned paid media strategy will move beyond traditional to digital/social, influencer activations, cross promotional partnerships and virtual/experiential to authentically drive and amplify audience engagement across an ecosystem that will maximize social currency through personalization.
When it comes to personalization and dynamic creative optimization, predictive AI is, and will become more and more integral to campaign production strategies in order to keep pace and scale with this insatiable consumer demand and break through the crowded, fragmented mobile/social marketplace. More studios, streaming and creative production partners are progressively leveraging data/analytics combined with machine learning to personalize content at scale for every possible target audience segment, social platform specs and best practices, a/b testing and localization, while saving time and production costs. While the human creative vision cannot be replaced, this will work to alleviate production time and costs especially now that many studios and entertainment marketing agencies have had to downsize and cut budgets. As predictive AI becomes more common, the effectiveness of those strategies will continue to improve.
One of the best examples of predictive AI is the “For You” feed on TikTok, which is powered by a machine-learning algorithm that analyzes each video and tracks user habits to personalize, streamline and mine intuitive TikToks for its 800 million user profiles that they never thought of watching but now, somehow, can’t resist. ByteDance, TikTok’s parent company is one of the largest investors and pioneers in AI technology with its massive computer vision and “virtuous cycle of A.I. powered algorithms which is aimed at the heart of our everyday existence, interests and shortened attention spans. It all kind of makes one think about the Great OZ, the wizard who uses sleight-of-hand and artful distractions to create illusions for an audience which will pay to be entertained so long as you head his warning “pay no attention to the man behind the curtain!”