The Data-Driven Future Of Media and Entertainment [Sergey Bludov]
It is by now an accepted fact that the future of the music business, media, and entertainment will likely be data driven, but what the exact implications of this may be for creative industries is, as yet, unclear. In this piece we look at how music, film & TV, and small data could be affected.
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Guest post by Sergey Bludov, Senior Vice President of Media and Entertainment Practice at DataArt
The future will be data-driven. But, for the creative industries, what kind of future will data drive towards?
Technology should enhance creativity, not suppress it. Fortunately, much of the ever-increasing amount of information available through integration of technology in the creative industries turns out to be useful information. Intelligent data analysis is a cutting-edge tool that will not only benefit the bottom line of media businesses, but also help businesses that optimize their use of this information to outpace competitors. The data-enabled path leads media and entertainment companies to a new and exciting future.
Publishing and Digital Media
The publishing industry has gone through a number of massive disruptions over recent years, including the rise of online publishing and eBooks. Digitization of the reading experience threatened traditional publishing models. Importantly, however, it opened up a new frontier that publishers are increasingly starting to use to their advantage.
As the digital publishing market has grown over the last few years, so has the amount of data available to publishers. Gathering and intelligently synthesizing the right data helps publishers to understand existing and potential patterns of consumer behavior, allowing authors and publishers to stay relevant, better forecast book sales at a title level, and better market their titles.
What’s Next? Writing “on demand”.
The concept of leveraging predictive analytics (including analysis of signals relevant to consumer interest in various topics) first gained currency with respect to publication and promotion of Internet content. As the data analytics have improved, publishers have now also started to experiment with evaluating Key Performance Indicators (KPIs) to help decide which books to publish from among submitted manuscripts and proposal – and even guiding their authors to which books to write based upon increasingly sophisticated understandings of consumer interests, demand, and propensity to buy particular genres and titles.
This revolution is still in its early days, but the outcome seems inevitable. Book publishers, like their digital media counterparts, are leveraging data in never-before-possible ways to figure out what readers actually want. In short, big data and machine learning are being used not only to make a stronger connection with loyal fans and subscribers, but also to determine what current and potential future readers will want to read tomorrow. Ultimately, data can be the driving force behind increasing publishing revenue and superserving readers in a sophisticated, intelligent way.
Music
After a decade long struggle, the music ecosystem seems to have gotten over the shock of technology disruption and is now actively embracing technological advances. With the rise of mobile, streaming, social media, and connected devices, musicians have never been closer to their audience. Nor has the flow of consumer information ever previously been so extensive. Data analytics makes all of the inflow of user information actionable. Business decisions that used to be based upon personal experience and assumptions about how to better market and sell music are now, instead, being automated through the use of AI and big data.
For instance, Gracenote helps music fans build radio stations and playlists based on their musical tastes, favorite artists and listening preferences. Pandora, Spotify, Apple Music all made recent acquisitions of music analytics firms such as Next Big Sound, The Echo Nest, Semetric. New AI start-ups launch every week. This is a vibrant space with that will continue to transform in interesting ways.
What’s Next? Predictive Music Discovery
There is a reason why Spotify Discover Weekly has become one of the most influential innovations in music. By May 2016, more than 40 million people had used it, streaming just under five billion tracks in under a year. These are big numbers; they reflect active user engagement with personalized music discovery that is likely to increase as AI personalization becomes even more effective.
Relevant, personalized engagement is more important to the music industry than ever. Predictive analytics would be a logical next frontier – intelligent data algorithms that can provide insight into consumer preferences and help players across the music ecosystem discover new potential hits. Warner Music UK’s "streaming-first" sub-label called "Artists To Watch Records", for example, is already using sophisticated algorithms for early detection and discovery of tracks that are starting to heat up.
Machine learning and artificial intelligence, together with other innovative technologies (like audio fingerprinting, which Shazam used to turn sound into data) will enable ever-more-precise recommendation services for both labels discovering artists and fans discovering new music.
Film and TV
Television, meanwhile, is evolving from linear consumptive viewing to web-like interactive experiences. The change has not been easy on a lot of traditional industry players.
Recent reports from TDG and Limelight Networks indicate that consumers are, in increasing numbers, cutting the cord and moving to OTT & video streaming services. About 22 percent of the 100 million households that subscribe to broadband do not have pay-TV service. And the number of consumers who have at least one OTT streamed video jumped by 15 percent. Some consumers are even willing to pay for more than one streaming video service. This suggests that consumers who purchase streamed TV are likely to buy additional OTT services that match their taste preferences as those services become available.
This promises to lead to intense competition. “Content”, as the saying goes, “is king”. Having the right content is key to winning the scattering attention of today’s highly fragmented and multitasking audiences. In this ongoing battle, information about consumers’ preferences, viewing habits and personal interests is power indeed. Smart data science is being employed by video creators of all kinds, from streaming services to Hollywood studios, transforming businesses at every stage along the way, from project greenlighting to development (including budgeting) to marketing of video entertainment, to distribution.
What’s Next? Predictive Analytics and Personalized Programming
Numbered are the days of expensive TV bundles that offer hundreds of channels. The data suggests that viewers of the tomorrow will jettison such bundles and opt instead to subscribe to algorithm-powered user-centric services offering curated, personalized viewing experiences.
Entertainment behemoths such as Netflix and Amazon, who made data an essential part of their corporate strategy and flagship products, are setting trends with highly sophisticated predictive technology solutions that allow them to deliver original premium content. Netflix, for example, has sliced and diced its content into more than 70,000 micro-genres. Similar categorization could soon become available to Netflix competitors through the Video Genome Project, created by a company called Structured Data Intelligence and recently acquired by Hulu.
At the same time, content owners are realizing the value of their own content, along with all ways they can monetize through individual platforms. Content trading is gaining momentum.
There are, however, certain reservations about data-driven programming. While it certainly can influence the decisions about which stories to air, which characters’ airtime to increase or even showing different endings to different subscribers, it is neither clear that such changes will result in better content, nor what the broader impacts of such changes may be – whether artistic/creative, commercial, or even societal. We’ll have to wait and see.
Small Data?
Concurrent with Big Data becoming a household phrase and infiltrating the business side of creative industries, another concept is starting to make an impact – Small Data. The idea here is fairly simple: while Big Data provides top-level trends, Small Data helps companies to connect with consumers on a more intimate level, including marketing to them on a more localized and personal level.
On a more technical note, Big Data is essentially the massive amount of structured and unstructured information, whether from business transactions, social networking, or machine-to-machine interactions. In contrast, Small Data is a set of very specific attributes that can be created by analyzing smaller appropriately-sized chunks of data. It is more informative, timely, and brings meaningful insights in an accessible and understandable way to help companies find solutions to particular problems and achieve actionable results.
In the Media & Entertainment field, Small Data collection methods may include intelligently structured interview questions, detailed analysis of help forum interactions, and other data analysis that is not heavily reliant on massive datasets. This approach can help companies avoid the expense of tackling Big Data. Thus, Small Data can help establish actionable, realistic goals within a company; for instance, to create tailor-made ‘products’ or UX which feel thoughtful and compelling to the end user.
Is the Industry Ready?
Last year MarkLogic and Marketforce commissioned a survey of more than 100 senior executives in the Media & Entertainment space to understand how well the industry had adjusted to the digital era and whether or not it was ready to face the next wave of disruption.
Their findings are both encouraging and worrying.
On the one hand, encouragingly, the survey proves that the industry has coped with initial shock of digitalization and that organizations with the agility to quickly adapt new business models find new and better ways to capitalize on both obvious and unexpected opportunities. On the other hand, and of concern, the survey revealed that many companies in the media & entertainment space are — or feel — unprepared to provide the agile, data-driven services essential to reach the new, distracted consumer.
Whether in publishing, music, or broadcasting, the ability to deliver personalized creative has moved from theory to practice and is likewise moving from unimaginable to expected by digital audiences. To succeed and stay relevant tomorrow, creators and providers alike need to review today how they store, manage, synthesize and utilize data. Doing these things well allows companies to capitalize on new technologies, future-proofing their businesses (including being prepared to adapt to the inevitable next set of unforeseen and disruptive changes), and ultimately to offer services that delight their audiences.
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