Modern consumers only value content they find relevant–and they expect more and more control over the delivery of this content. Companies within the Entertainment and Media industry must champion their brands by providing smarter content with on-demand access. For music, art, film, etc., delighting and connecting with users more deeply than ever before, is what spells long term sustainability.
With more purchasing decisions being based on mobility and integration, how can this vibrant and dynamic industry turn up the volume on personalization to better secure a head-and-heart position?
Customers want choices. But they don’t want to work through them. Sorting through multiple subscription services in order to find the entertainment they want only leads to frustration. Adobe comments, “We’re bombarded with so many devices, mediums, shows, books, movies, and albums to choose from, it’s almost overwhelming. People are seeking better ways to curate the types of media and entertainment they should consume.”
To cut through the massive media flow, users want clear choices and customized content. A recent Adobe survey found 67% of respondents believe it’s important for brands to automatically adjust content based on their current context. If content is not personalized, 42% of the respondents say they are dissatisfied. Oh, and by the way, this has to be pulled off without consumers feeling like they’re being “stalked” by big brother, or that their identity and privacy are at risk.
Digital algorithms solve for content to distribute to individual users. But that wow factor is fading–desensitization to targeted ads on Facebook is in full effect. And it’s because everyone who receives a certain piece of content (Facebook post, news story, or Netflix episode) triggers the same result.
For example, Netflix shows episodes of Love, Death & Robots in different order to different users based on their patterns. Consider that getting your feet wet. ABC News in NY offers a personalized feed, via its mobile app, enabling users to choose topics, locations and dictate the level of detail within their content preferences. More eyes and ears on more variables makes for a more targeted effort.
Techcrunch notes, “Content itself will become a software-like fluid and personalized experience, where your digital footprint and preferences affect not just how the content is recommended and served to you, but what the content actually contains.” Imagine a news delivery channel that edits and delivers an article based on how much you know about, or how much you’ve previously engaged with the topic.
When you think of something creative, whether it’s musical, visual, literary, etc., you probably consider the entire work. A film, a song, a novel. Smart content disrupts this inclusive perception, using AI to separate larger work into smaller modules. The metadata assigned to each modules can be integrated into the work from the beginning, to aid with delivering satisfying content to end users. In short, smarter content actually uses the sum of its parts to its full advantage.
Additionally, these modules can be delivered individually–activated or arranged based on user preferences, or on behavioral information the platform gathers. Zorroa Visual Intelligence shows how AI handles content modules. It searches visual media, like video, locating and assigning significance to specific themes, effects, and more.
Platforms that search and categorize video empowers content producers to deliver what users want, faster. NBCUniversal uses metadata around people and themes in videos to create customized clip generators and advanced search functions. This approach applies to audio files as well. TikTok continues to experience tremendous growth and adoption with its modularization capabilities. The popular songs that make up much of its value are only available in 15-second clips.
Video personalization platforms like IRIS.TV capture metadata from a client’s video feed, using AI and machine learning. Once this metadata is available, the platform integrates its personalization engine directly into the video player. Each user receives their very own playlist, based on analytics about their individual history and preferences. This platform is used both by media companies as well as by any marketer using branded videos.
Most entertainers/artists don’t have access to the sophisticated AI that allows audience members to assemble their own customized experience. Instead, artists turn to personalization platforms to provide this service. Using machine learning, platforms like Evergage and Taplytics market themselves to media and entertainment companies.
Evergage promises artists it will “transform their one-size-fits-all content sites into responsive digital properties that uniquely cater to each and every individual based on his or her behavior, attributes, interests and preferences.” To understand visitor behavior, Evergage tracks clicks, mouse movement, and all associated user behavior on the site. This information integrates with geolocation, historical data, and third-party information. It then gets sold to content producers in the industry.
TIVO’s “Personalized Content Discovery Platform” groups user recommendations and predictive search results into individual “carousels,” making it easy for users to find the content they want. A conversational interface adds to the streamlining, while an assortment of metadata categories and natural language capabilities yield layers of user information.
TIDAL is a “global music streaming and entertainment platform” owned by a small group of top-tier artists (including Beyonce, Rihanna, and others). In addition to both personalized and artist-curated playlists, TIDAL gives its subscribers back-stage access to special content, to better connect them with their favorite artists.
This platform also offers a first look at new work by participating artists, so the user has early and easy access. Venturing further afield, the TIDAL Rising program offers an array of promotion services to emerging artists with strong online followings. This is a mutually beneficial platform that offers users the opportunity to directly contribute to the success of up-and-coming artists.
One of the goals of personalization is to focus user efforts. No one wants to be saddled with slogging through a labor and time-intensive “choose your own content” maze. Instead, the AI engine effortlessly delivers entertainment that appeals to each user. However, while this process needs to be streamlined, it should also be honest and transparent. One small example of opt-in transparency is seen in Dish Network’s Evolve, which allows hotel guests to log in to their own Netflix account on the hotel room TV.
Techcrunch points out that it’s vital for users to be able to choose whether or not they want their content to be personalized. In fact, it would be remiss not to mention the scrutiny around the increasing trend of personalizing everyone’s online experience. California’s upcoming data privacy law, the CCPA, which goes into effect in January 2020 is a prime example.
“Sheldon County” an experimental podcast by a visionary AI researcher, is read by a voice synthesizer, creating a whole new episode plotted for each individual user’s preference. The current version is still raw and won’t compel a lot of audience attention, but its implications for generative media captivate AI innovators worldwide.
Subscriber numbers at premium cable channels are falling, while direct streaming to digital devices is increasing. Entertainment and Media companies must fight harder to maintain audience share in an increasingly crowded online environment. Those industry adopters leveraging smarter content are the ones whose work will prove sustainable in the decades to come.