Look, Big Data's on TV!
Over the past decade, the Media & Entertainment sector has been completely disrupted by digital technologies. First there was the transition of content, from creation to delivery, to digital formats. Then the arrival of the new-age-device-loving digital consumer significantly altered established norms of content consumption. This was followed by the emergence of innovation-led, technology-fueled, consumer-focused new economy companies, which proceeded to completely rewrite all established rules of the M&E business.
Content consumption is still on the rise; it's just that the rules of engagement have changed irrevocably. Consumers now demand innovative content, at the time, place, device and platform of their own choosing, and, generally, free of cost. Consequently, the industry faces the massive challenge of reinventing every aspect of content, from development through distribution, and from pricing to marketing to service, around consumer preferences and expectations.
Luckily, the industry has access to a critical enabler in the form of Big Data. Historically, a data-intensive business, the M&E sector is now awash with information, structured and unstructured, transactional and real-time. Parsing all of this into actionable insights that deliver engagement and value is its next big (data) opportunity.
Most of the world's leading media marques are already leveraging the power of big data analytics. The Weather Channel's big data initiative meshes historical data with current information to improve forecasts, in real-time - to not only pronounce whether an umbrella would be needed or not, but to actually issue advisories to aircraft, or predict the output of a wind energy farm. At the Financial Times, big data analytics drives the optimization of ad inventory pricing by day-part, target audience and location. It enables service providers like Time Warner Cable to understand and respond to competitive challenges like on-demand streaming and cord cutting or to deliver individually targeted ads across multiple platforms.
Such big data-led transformative possibilities also exist in the content value chain. The keystone in most operating models is the consumer - understanding who brings the revenue in advertising-supported businesses or simply the direct revenue from customer in subscription-based models. A deep understanding of consumers and the ways in which they engage with content across channels can inform strategies and enable decision making throughout the supply chain spanning content creation, distribution, communication, sales & marketing and customer service.
And this is where big data analytics rules by enabling media businesses to derive unprecedented consumer insights from varied sources of structured and unstructured data, lying within or outside the organization. Which in turn, can inform a range of activities to enhance engagement and maximize mutual value.
For instance, clear customer understanding allows for the personalization of content to context; even marketing campaigns may be personalized to target only those consumers who have shown a propensity for a particular product, service or message. Recently, Time Warner Cable Media ran a pilot program, putting the same ad campaign on cable TV, mobile, Internet and social media. It analyzed a customer's interaction with the campaign on each channel and subsequently, modified offers to increase appeal. The company says it got great results.
Similarly, analysis, of consumer sentiment and intent expressed in social and other online networks, can provide valuable feedback that media businesses can use to fine tune existing offerings, or create custom content packages based on individual habits. They can also identify the key influencers in specific categories or topics, and cultivate them to generate buzz or word of mouth for future campaigns. They could forecast demand based on the response to current offerings. Last but not least, they can sense which customers are likely to leave by analyzing transactional and behavioral data.
It's pretty clear that in a sector where information is the business, companies that leverage big data to add value to customers or make better decisions will get ahead. Unfortunately, they can't turn to conventional analytics solutions, because they're simply too niche, far too slow, don't handle unstructured data and are just too painful to integrate. To extract maximum value from this opportunity media companies need to find an analytics solution that has the capability to operationalize insights quickly and efficiently. It should integrate tightly with their business processes, operations and support functions. Finally, it must enable real-time collaboration between the people who decide, and operationalize their decisions at the right time. Like whether to hit the runway now, or head back to the hangar.