AI, Deep Learning Enhances Analytics For TV

The convergence of broadcast television and internet-delivered content services has become a reality — one that soon will be cemented by the media industry’s embrace of ATSC 3.0. In this cross-media environment, broadcast stations face many challenges, a mix of old and new.

While ratings are a long-familiar concern for broadcasters, fierce competition for audience share today comes from a variety of providers on platforms ranging from linear channels to over-the-top (OTT) services to social and digital media.

The new complexity of content distribution and consumption makes it hard for executives at a station to understand that station’s place — and the value of its media inventory — within the larger marketplace. Even more difficult is to be proactive in ensuring that the station leverages that inventory to its best advantage.

Without reliable insights into the business and the market, as a whole, station leaders simply cannot be responsive to the fast-changing world around them.



Analytics is the only tool capable of providing a clear picture of a broadcast station’s history, current performance and future revenue opportunities. By automatically aggregating data from the station’s transactional systems, consolidating that data into a unified repository, and normalizing and analyzing the resulting information, a robust analytics system can deliver intelligence that is fundamental in driving the survival and success of the station.

The evolution of artificial intelligence and deep learning platforms now presents new and more powerful tools to the arsenal of analytics.

Leveraging machine-learning technologies, a new generation of analytics systems can continually monitor and assess sales performance, market trends and business cycles across lines of business (local, national, digital, etc.), products, sales offices and even individual advertisers essentially in real time.

Even more importantly, these new technologies can bring the right insights, to the right people, at the right time, to facilitate new revenue opportunities.

Gleaning insights from millions, even billions, of data points, a robust analytics system exposes the trends (internal and external) and opportunities (missed and available) that determine how a broadcast station separates itself from the competition and exploits its marketplace differentiation.

Whether moving to capitalize on an opportunity or to avoid a potential problem, station executives and sales people often have only a narrow window in which to identify the ideal course of action and follow through on it. With a new approach, guided by “intelligent agents,” the station can be confident that timely intelligence is being injected at key points in the sales workflow and customer relationship lifecycle.

Timely intelligence in providing alerts to mobile personal platforms (tablets or smart phones) keeps executives and sales people continually on focus, pointing the team toward areas of potential revenue growth which helps surface the best path to execution and accomplishing corporate objectives.

These alerts can range from recommended change of rates based on demand, new target audience opportunities, new client opportunities, to pacing performance to achieve revenue targets, all conveyed in a priority of importance reflecting their potential financial impact on the business.

Broadcast stations in large part collect the data they need to understand their current business workflow and future opportunities on their legacy workflow platforms, but few aggregate and put that data to work with analytics that is directed at the new world.

The new world has complexity across multiple platforms and a range of new competitors and only those stations that harness the power of the new generation of robust analytics will be able tie this data to their performance and revenue potential across all platforms and properties.

When they do, stations will be well equipped to charge ahead into the converged media marketplace — and succeed. 

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