With new challenges for streamers and longstanding headwinds for many other media creators, fighting churn is more important than ever.
Think of your favorite movie as a kid, say in the first 10 years of your life. Now think about your favorite movie from the last decade. Do you have one? do you have 100
In a world of essentially infinite content, choice is one of our greatest joys – and frustrations. With each passing year, consumers seem to become more fickle and demanding, regularly switching to the platforms and publications that offer not only the best catalogue, but also the best customer service, content experience, user interface and value for money.
And even those features may not be enough, as the recent upheaval among major streamers has shown.
Bonding with viewers, readers and listeners has become more important than ever. However, most consumers can only maintain a limited number of subscription services at one time. The goal for media companies must be to maintain their interest with as much of the consumer’s wallet as possible.
As such, churn is the most prominent enemy of the media and entertainment industry business model today. Consumers can be fickle, sensitive to pricing and changes in content catalogues. Just as adding a service has seldom been easier, it is seldom easier to delete a service, which consumers have been more than willing to demonstrate when a channel no longer meets their needs.
Faced with these challenges, leading media and entertainment companies are increasingly turning to data analytics and personalized content recommendations to improve customer experience and retention. In the digital canine world, it’s no longer the loudest bark that gets the most attention. It’s about mating the right breed with a specific person’s sensibilities and having the best information and offerings to make that match and keep it going.
As subscriptions have increased, so has churn
A good example of the churn challenge is streaming video. Deloitte conducted a series of surveys in 2020 to measure how consumers are changing their media consumption habits amid the pandemic.
As of January 2020, the average consumer in the United States subscribed to three paid streaming services; by October 2020, the number of subscriptions had increased to five. Overall a positive development for media, but as subscriptions increased, so did churn.
In January 2020, Deloitte found that only 20% of people who subscribed to a paid streaming service had canceled at least one of those services in the past 12 months. By October, that number had more than doubled, with 46% of consumers having canceled a streaming service in the previous six months. And back then, 34% of consumers said they’d both added and canceled a streaming service since the pandemic began.
Why have viewers left? Deloitte found that 62% of people who signed up for a service in 2020 and then canceled it did so because they signed up for a specific show and then canceled the service after finishing watching it had. As always, the price also played a major role. In October 2020, 31% of people who canceled a service did so because it was too expensive. Another 28% have canceled because a free trial or discount period has expired. About 21% stopped using the service due to a lack of interesting content.
No matter how focused a company is on churn, what can it do when consumer whims are so sensitive and highly volatile?
Companies need to find ways to anticipate what their target audience wants at least as well as the target audience—and certainly better than their competition. Two of the best defenses against churn are an organized data platform and using that data to personalize content recommendations and customer experiences.
Data maturity is the first step to mitigating churn
Data maturity is the ability to have accurate and reliable data ready to be consumed across cloud platforms, with advanced analytics driving every decision. It’s one of the most important steps for media and entertainment companies to curb churn
Based on our experience working with companies as diverse as Spotify, The New York Times, Major League Baseball, and Hearst, the first step to achieving data maturity is to build an organizational culture where data is prioritized and resources allocated within the strategic business framework Technology and human resources to build a mature data ecosystem.
Data maturity should not be an add-on to existing practices, but must be at the core of the organization’s strategic business goals. Organizations that have reached data maturity typically have dedicated teams or centers of excellence that manage the goals, strategies, and tactics of the organization’s data framework.
In a 2020 EY Global Media & Entertainment survey, 62% of media and entertainment executives said they see increasing availability of data as an opportunity. About 56% prioritized first-party data, versus just 13% who prioritized third-party data. When asked about their top three data priorities, 44% said consolidating customer data is a top concern. About 40% said developing proprietary data sources was a priority, while 39% prioritized improving the relevance of data.
Consolidating data from data silos onto a unified data platform is the number one challenge most organizations face when creating a data maturity roadmap.
A report by Deloitte in partnership with the Google News Initiative on how news and media companies can achieve digital transformation through data outlined some of the technologies companies can employ to achieve data maturity. Two items are required. First, media and entertainment companies need to be able to collect and store data they collect from their global audiences and users using the tools listed below.
- Data Management Platform (DMP) helps manage first-party data segments and integrate third-party data and transfer data to other systems.
- Data lake or warehousea central repository of data from multiple sources.
- Cloud storage for reliability, security and scalability.
- Customer Relationship Management (CRM) the backbone of customer data that records and tracks user interactions with registered subscribers.
- Customer Data Platform (CDP) to record and track customer data across platforms and devices.
Second, organizations need to understand all this data and derive actionable insights from it.
- Data analysis and reporting tools that can collect, organize, and analyze data from multiple sources.
- Artificial intelligence and machine learning tools. Gain even more insights with AI/ML-enabled capabilities like computer vision, speech and object recognition, and text translation.
- Propensity modeling helps build a better understanding of customer preferences and fulfills the key elements of personalization to prevent churn.
Below we describe some of the unique data sources available to media and entertainment companies and how they can be applied to artificial intelligence and machine learning.
Media and entertainment have unique data sources
Media and entertainment companies can improve personalization by leveraging two industry-specific datasets: media content and audience behavior.
Media content includes easily identifiable metadata such as title, headline, genre, subject or format of a content. However, media data can also contain the context of the actual content itself.
For example, AI tools such as object recognition and computer vision can recognize elements in a movie and then add the object’s description to the content’s searchable metadata. If a TV show features a Border Collie, the AI can recognize the well-behaved dog and display the show when searching for “shows with dogs”. Or with speech recognition and translation, the AI can create a dataset of dialogue within a movie and include specific keywords in searches for that show.
Audience behavior data can be used in a variety of ways. Data can come from many different sources, including an individual’s location, device, browsing and scrolling, user profile, engagement, billing preferences, purchase and support history. Organizations can help personalize experiences with this data by understanding how people interact with content and how best to engage with it, e.g. For example, what times of the week are best for push notifications or when a person is best for a content recommendation.
Using artificial intelligence to personalize user experience
If you’ve ever wondered how your favorite streaming service seems to know so uncannily what you want to watch – even better than you might – the answer is probably some clever AI. Personalization is the practice of combining the new, massive data sets described above with machine learning and artificial intelligence to create experiences tailored to an individual’s specific needs and behaviors.
Personalization is often associated with content recommendations. For example, about 70% of what is watched on YouTube comes from a personalized recommendation. Certain streaming services are known for having some of the best content recommendation systems in the industry. The goal in personalizing content is to show the person a new show, video, movie, podcast, song, band, album, article, or blog at exactly the right moment.
Personalization is also an important element when searching. Consider that with the right data inputs, two users searching for the same keywords could get vastly different results aligned to their consumption preferences. In both cases, content that better suits an individual’s interests will discourage them from browsing other platforms or publications, thereby helping to reduce churn.
The same goes for more traditional outlets too. Take a recent example from the (digital) pages of Newsweek. The publication’s Chief Technology Officer, Michael Lukac, recently noted that “Google Cloud Recommendations AI not only improved our click-through rate by 50% to 75% and subscription conversion rate by 10%, but also enabled us to Increase total revenue per visit 10%.”
If you’re looking for more information on why personalization is so important and how to incorporate it into your own services and experiences, check out our new e-book, Personalizing Media for Global Audiences.
Download eBook: Personalization of media for a global audience