How data and AI can help media companies better personalize; and what to watch out for

Media companies now have access to an ever-expanding pool of data from the digitally connected consumer. And over the past two years, as content consumption and audience behaviors have shifted in response to the world around us, direct-to-consumer has only accelerated. 

As media organizations pivot from third-party to first-party data, this presents challenges with the volume, velocity and fragmentation of data. It’s also an opportunity to better understand how to acquire, engage and retain audiences ⁠— and inject agility into their business amidst a competitive landscape. 

How should media companies be thinking about their data, and its value, to capitalize on this opportunity?  

To help answer these questions, we sat down with Gloria Lee, Executive Account Director in Media & Entertainment and John Abel, Technical Director for the Office of the CTO at Google Cloud.

Data and the growing importance of personalization 

There's no doubt customer needs and expectations are in a constant state of flux. Across the media industry, audiences are increasingly expecting personalized content. In fact, a  PWC study conducted in 2020 found that nearly one-third (31%) of survey respondents said easy, personalized content recommendations would be a reason for staying with a streaming service.

Audience engagement is the currency, and in a crowded space where attention is finite, media companies need a granular understanding of their audience. To do this, there’s an opportunity to capture and capitalize on first party data, so they can better serve their audience. Not just what audiences are consuming, but also when, where, and on which platform (and increasingly, those platforms are digital). These data points are key in understanding audiences deeply to deliver hyper-personalized experiences that audiences are expecting.    

“If you look across the world today, we know that through digitalization, [that] hyper-personalization is required,” says John. “So that hyper-personalization, the volume of data and the value of the data is super critical across all industries. Media and entertainment is no different,” he adds.

Enriching storytelling through AI & ML   

Extracting insights on how, where and when the consumer wants to receive content will accelerate the need for data research; AI and ML will be critical to unlocking data’s full potential. “The most valuable data is generated data, typically from machine learning or AI, where you're seeing new insights in data that give you new opportunities.” explains Gloria.  

New technologies are providing insights — often in real time — about audiences, making personalization an easier task. An example use case would be recommending a new song based on a user’s listening history. This kind of personalization is just the start, as AI/ML unlocks more novel opportunities. For example, AL/ML can also be used to enrich the watching experience by finding opportune moments to integrate brands. As Gloria puts it, “Artificial intelligence, and machine learning is what enables people to quickly look through their content to find relevant moments for marketing purposes”. 

Getting personalization right, while making sure to keep consumer information safe and private is a challenge for all consumer companies; not just M&E. John explains “there’s a blend of how they move technology to the edge and they don’t break privacy.” Media and Entertainment companies will need to keep their data secure and private, using sophisticated practices like data federation. In this model, individual data is not exchanged.  Rather, data is first aggregated into cohorts to anonymize the individual. The goal of methods like this is to obtain useful insights while retaining privacy and security.

How data is driving audience experiences 

Spotify is a prime example of a media company using data-led insights to provide personalized content for their customers — making it easier for users to discover new audio content and connect with their favorite artists or podcasts. 

“[With] Google Cloud...we can iterate quicker on key needs, like data insights and machine learning…[streamlining] our ability to concentrate on what’s important to our users and give them the experiences they know and love about Spotify.”—Tyson Singer, VP of technology and platform at Spotify

Sky, one of Europe’s  leading broadcasters is also transforming its data strategy to better serve their customers. By creating a scalable cloud-based architecture, Sky can keep up with increasing amounts of TV box diagnostic data on service uptime and delivery ⁠— meaning less data lost and more time to focus on improving user experience through personalization. “The data will sit right at the heart of Sky’s future strategy. It will help ensure that our products are intuitive and easy to use and that we can keep seamlessly connecting customers with the content and services they know and love,” says Oliver Tweedie, Director of Data Engineering at Sky.

Transforming to a data-oriented Media company

Keeping up with new technology trends, inside and outside of the industry, will play a critical role in how media and entertainment companies can survive and thrive into the future. And without a way to centralize and draw insights from their data quickly, media organizations will struggle to stay in the race. 

With any type of change comes resistance. But at the end of the day, it all comes down to people. When navigating digital transformations, Gloria touches on the three categories of people: ⁠supporters, those excited about the change, those who couldn’t care less and detractors, those who are opposed to it. “It's really tapping into the leaders for those three different groups within the company and trying to get them on board and seeing what their drivers are,” Gloria explains.

So what advice do John and Gloria have for Media players looking into the data-led future?