Media: Embrace The Citizen Data Scientist
The media industry is facing a conundrum.
Over-the-top (OTT) services are attracting viewers with nuanced interests and consumption patterns that can be tracked to an extent never before possible. This data, in turn, can be leveraged to create growth opportunities for OTT providers, including subscriptions, advertising and partnerships.
The challenge is understanding the data behind these new consumption patterns.
Top players in the market (e.g., Netflix, Amazon, Hulu) have built teams to analyze the data that they collect. Others, meanwhile, are left with an overabundance of data from which it is very difficult to gain insights. Aggregating and normalizing data to gain a holistic view of a set of services is a challenge in and of itself.
Yet data holds the keys to predicting, preparing for and executing on revenue opportunities (and risks) in real time. Whatever company analyzes data the fastest will thrive in the media market of the imminent future. And those that fail to quickly produce actionable insights from their data will succumb to the competition.
Enter the “citizen data scientist.” Gartner coined the term in 2018 to describe professionals who use technology to learn about their markets and put that intelligence to use for their teams — and they’re going to be pivotal for media businesses looking to remain competitive.
Driven By OTT’s Rise
OTT is expected to keep growing while other sectors of the global economy may face ongoing downturns due to COVID-19.
Comscore recently reported that nearly 70 million homes in the United States are subscribed to OTT services like Netflix, Amazon Prime and others, an increase of 5.2 million homes from April 2019 to April 2020. The global OTT market grew 55% to $161 billion this year, according to Research and Markets. And Allied Market Research forecasts that the OTT market worldwide will hit $332 billion by 2025.
Until recently, only data scientists could harness the technology capable of analyzing the fountain of data that OTT generates. Only in the last few years have sophisticated technologies such as AI been productized in a format accessible to business users. AI is now far more deployable for businesses that have the capacity to collect performance data but have yet to capitalize on the insight it can provide.
This is why the media industry needs citizen data scientists. Though not trained with an identical skillset to a typical data scientist, citizen data scientists use skills they already have in combination with powerful software to analyze and track business activity. They’ve become common in finance, human resources, marketing and sales — all fields where companies need to understand shifting customer and stakeholder behavior, often immediately.
Bringing Citizen Data Scientists To Media
The media world has been slow to jump on board, however. Perhaps using AI is an anathema in a creative industry. Perhaps individual tastemakers still wield substantial power. Maybe assumptions about the investment necessary to benefit from AI are mistaken. Many firms don’t think they’ll achieve sufficient ROI and are hesitant to trust that AI will improve their business.
Whatever the reasons, media companies need to forget them. Today, these companies have ready access to the tech that can leverage their own information to gain competitive advantages.
But once committing to using AI, or even taking steps toward it, media companies will discover that humans are critical to capturing its transformative potential. And it’s individuals, likely already within their companies, who have a basic working knowledge of analytics that will need to take on the role of citizen data scientists to make this happen.
Technology can crunch data, isolate trends and apply formulas. It can do so most effectively with human input: defining the goals to be met and questions to be answered and translating the results to action. If there is an urgent business need to identify churn risk signals within a new subscriber segment, for example, then that’s what the tech will investigate — with human prompting.
And while AI is certainly capable of prescribing and even automating preemptive actions, such as personalized retention offers, citizen data scientists can add value by contextualizing these insights for others in the organization.
Of course, the most advanced AI will also employ unsupervised machine learning to investigate and surface business issues undetected by — or undetectable to — humans. These “unknown unknowns,” combined with the valuable work of citizen data scientists, yield more powerful insights than either humans or machines could produce alone.
The New Normal
Consider how fast, precise, multivariate data analysis would help media companies predict market-level trends as well as navigate the race to monetize content. The latter is crucial if media companies plan not only to survive but also to thrive amid consolidations and other tectonic realignments in the industry, like the rise of new content creators and distributors and the shift away from linear viewing. Data-driven moves within and between media companies based on those market changes are fast-becoming the new normal.
Other pressures are mounting, too. While the media market might not be in for a contraction, it’s bound to experience plenty of disruption and churn. Though OTT is popular, for example, Deloitte recently reported that U.S. customers are limiting their OTT subscriptions to about three per month, on average.
That means that companies have to experiment with different levels of services, ad- and non-ad-based offerings and so on in order to keep revenue on an upward path. And I’d wager, only companies with citizen data scientists will be able to monitor and leverage all of their data closely enough not only to know if their companies are keeping pace with the competition or losing ground, but also how they can reach and remain at the top.
Joe Mancini is vice president of product at SymphonyMediaAI.