Like their pure-play brethren, diversified media companies have worked hard to differentiate and shape content across their properties. Yet as they step into direct-to-consumer (DTC) streaming services, companies like NBCUniversal, WarnerMedia, Disney and Viacom face a new challenge: how best to personalize the one-stop viewing experience that’s at the heart of DTC.
Delivering personalization means walking a fine line. It requires diversified media companies to persuade viewers to watch a broad array of content and to cultivate specialty channels that attract passionate followings. Companies that miss the mark risk increasing customer churn and eroding DTC margins. Finding the right balance takes data, analytics, AI – and a sense of the possible.
By tapping into their data and putting it to work in new ways, companies can differentiate their services in the competitive streaming market and achieve sustainable growth. Based on our work with clients and partners, here are six ways diversified media companies can personalize the DTC experience through data, analytics and AI.
- Make the first impression count. The opening screen provides a great opportunity to engage viewers. However, many media companies don’t personalize the landing page. Instead, they use it for splashy promotions of strategic new content or for recommendations based on viewing history.
Largely overlooked is the opportunity to connect with followers of niche brands. For example, when fans of channels that specialize in dark, moody content click on the app or website of the brand’s parent company, they see generic opening screens, or slates. Changing that picture (literally) requires data – and lots of it.
Media companies have access to troves of data from internal systems and third parties such as Nielsen Gracenote. By enriching their existing data with more data – from social networks and disparate datasets, as well as sociological research from sources like our partner ReD Associates – they can connect the dots in customer experience. With full viewer profiles, they can offer both personalization and more engaging opening screens.
- Create temporal context. Because the challenge for media companies is to understand what viewers want to watch right now, temporal context is critical for delivering personalized content. Smartphones are packed with built-in sensors that play a key role in knowing what a viewer is doing at a given moment. The sensors measure a variety of conditions, including motion, orientation and environment, that can be used for personalization.
Using data from the gyroscope, for example, which indicates rotation or twist, media companies can detect whether the phone is lying flat or on its side – and consequently whether the viewer is sitting up, lying down or playing games. In Android and iOS devices, the gyroscope is turned off by default. By encouraging viewers to turn on the gyroscope and then incorporating gyro data along with social sentiment analysis and external data sources, media companies can suggest more contextual content. For example, when they detect a viewer who is lying down, they could recommend games, short-format content or light comedy.
- Think of devices as Internet of Things (IoT) platforms. Smartphones’ array of sensors can also provide situational awareness, giving media companies a way to become part of the ecosystem of connected homes and buildings. We’re working with a media company to gather data from smartphone barometers. The details on air pressure and elevation help pinpoint viewers’ locations, such as whether they’re in their cars or in high-rise office buildings. These insights can be used to craft personalized options, such as auto-muting a video for someone who’s at work.
- Explore more sophisticated data collection. Rich data requires rich assets. By aggregating data from three essential dimensions – viewers, content libraries and commercial messages – media companies can gain a big-picture view of the customer journey, as well as any touchpoints that could be strengthened or created with delivery of personalized content. Using rich data, for example, media companies can detect where access to premium content may be too generous and lower free-trial conversions. Media companies can also use more sophisticated data collection to run massive A/B tests that use deep machine learning to automate thousands of promotional options using variables such as button size and color.
- Evaluate catalog-wide search – and its strategic ramifications. Many media companies are still unable to search their full catalog of properties, and those that can are often just getting started on personalizing site-wide search results. As companies sort through the options on catalog search presentations, they encounter key choices, such as whether to go wide or narrow. That is, they can either emphasize the depth and breadth of the multi-brand service, or present viewers with a curated selection based on their preferences.
- Balance AI-enhanced content with selections that are hand-curated. Curation is as much art as science. AI holds much potential for media companies, particularly in guiding viewers to relevant content. But the personal touch remains important. In an interview, WarnerMedia’s then-CTO Jeremy Legg envisioned collections of content chosen by people, not computers, as a key offering for the HBO Max streaming service. A central question for diversified media companies is how much to automate curation. That is, how many algorithms are too many? Striking the right balance of hand-curated and AI-generated content is key.
The good news is that data, analytics and AI make personalization infinitely possible. It’s just a matter of putting together the pieces to make it happen.
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