One innocuous job advert caught my eye recently as a highlight of a big trend in broadcasting and pay TV.
CableLabs was advertising for an intern to work over the summer supporting its Video Services and Technology department on Big Data Analysis development. The ad stated that “Big Data analytics, especially low-latency processing, enables opportunities for near real-time decision making, with 360-degree visibility in the measured business space.”
This was business speak stating that pay TV operators have a great chance to harness customer and service related data to make immediate decisions that boost quality of experience for customers in various ways. This includes the QoS in terms of picture and audio quality, along with zapping speed, and also aspects relating to the content itself. The latter might involve recommendation, but, intriguingly, could also mean actually changing a live program as it is going out, in response to audience feedback.
This is all in the realm of big data analytics for broadcast and video, which has become a battleground not just for vendors of products in the field but also among service providers themselves. It is fast becoming a source of competitive advantage and improving customer satisfaction. No wonder vendors are piling in from all directions. We have big IT companies that play in the data center and amassed data analytics portfolios there, such as IBM and Hewlett Packard, meeting up with traditional pay TV quality assurance (QA) vendors, like Mariner, Ineoquest and Agama Technologies. Then, we have big network and broadcasting infrastructure companies like Cisco and Ericsson weighing in, often through acquisition, bumping up against specialists in data offload and analytics on the mobile and Wi-Fi front, such as Birdstep, Aptilo and Smith Micro. Pay TV operators themselves are getting involved, as are their representative bodies, and that is where CableLabs comes in as the cable TV operators club, along with its European equivalent EuroCable Labs.
Social media companies are naturally also edging into the field from their base as custodians of data about TV preferences and opinions about shows, again through acquisition. Twitter confirmed in February 2013 it had bought Bluefin Labs with a product that measures the effectiveness of commercials and programs on TV on the basis of social network buzz. Facebook’s key move, most relevant for TV, was its recent acquisition of the Atlas Advertising Suite, which will enable Facebook data indicative of user preferences or ad success to enhance ad targeting through video channels.
Then, perched in the middle like a spider in its web, is Nielsen, the world’s leading audience measurement company, for which Big Data is a natural extension of its business. Nielsen is already well into the game with its Online Campaign Ratings, which delivers overnight audience ratings on a demographic basis, consistent with TV gross rating point (GRP) measures, combining massive amounts of social media data with a traditional multi-platform panel.
Nielsen also has its Twitter TV Rating based on tweet analysis, and has already proven that this works through a study of over 140 broadcast and cable TV programs. Twitter proved to be one of three variables, along with prior year rating and advertising spend, to have a statistically significant relationship to TV ratings.
Broadcasting, or at least its representative unions, has often been slower to embrace big data, which has not appeared to be that high on the EBU’s agenda for example. But, the BBC has been actively pursuing big data development with plans to apply real-time, audience-based analytics across all aspects of its operation, including finance and marketing as well as program making.
The corporation is currently investigating use of data culled from social media to make real-time program decisions during some live shows such as panel games as well as interviews, in response to audience sentiment. If lots of people are enjoying a particular part of the show, such as an interview or discussion of a given topic, that could be prolonged, or conversely curtailed if it was unpopular.
The various parties involved in big data analytics are coming at the problem from their own perspectives in promotion of their interests, with QA vendors for example seeking to harness it for improved QoS, particularly for OTT and mobile video delivery. For Nielsen, it is about capitalizing on its near monopoly of cross-platform audience data spanning all operators and broadcasters. For pay TV operators, it is about accumulating and then harnessing massive data sets about their own customers, using this for their own marketing strategies, as well as real-time recommendations and targeted advertising.
They will need this analytics capability to compete for ads in a world where brands will increasingly expect immediate feedback on ad success and ROI. So, Big Data analytics will become a necessity for staying in business and this is where Cable Labs sees its role in developing the relevant technologies on behalf of its members. It also wants to reduce its members’ dependency on services from audience measurement companies, such as Nielsen, and become masters of their own destiny.