Big Data’s Big Impact on TV Advertising
The Big Data-Television Gap
Big data is earning its keep in a number of industries today. In retail, Amazon has surpassed all others, analysing data from millions of customers to recommend apt products at every step of the purchasing process. In finance, American Express has been studying customers’ transaction history collectively to spot loyal customers and prevent churn. In sports, match and player data is so ample that football team owners are analysing player attributes from leagues across the globe to identify upcoming talent.
Bar a few exceptions, the TV industry is still not capitalizing on the opportunity to combine big data and advertising efforts. Over the last decade, TV advertising has taken a hit every year with more people watching TV online than ever before. For companies, digital ad spending has started exceeding TV ad spending. The reason is quite clear, digital advertising provides fine-grained targeting of audiences while traditional TV does not.
Why Big Data and Advertising Aren’t as Opposed as You Think
During the analog era, TV networks commissioned content for a wide bulk of people who watched only a small number of shows on a few channels. TV networks and advertisers concentrated their energies on a single factor – prime time slots. While the 9:00 p.m. slot guaranteed large viewership, for advertisers it meant pouring down a lot of money for a shot in the dark. The majority of advertisers would rather reach out to a group of well-defined target prospects.
In today’s age, TV can certainly do a lot better. Digital audience data is the game-changer for TV profitability. Both networks and advertisers have access to more viewing information than before from smart TVs and set-top boxes, in addition to traditional audience measurement panels such as the Nielsen panel.
All these new sources provide insights that give TV marketers deep and instant understanding of ad and show performance. Leveraging big data for television advertising results not just in more relevant campaigns, but also delivers insight into how a campaign performed.
How Netflix Bridged the Gap
One of the most popular examples of using data to drive TV content is Netflix’s House of Cards, a show that was designed to be a success based on data like viewing preferences, user ratings, and viewing habits.
Netflix knew the show would be a hit even before anyone called out “roll camera, action”. Typically, TV networks ask show directors to shoot a pilot episode – a standalone episode that acts as a testing ground to assess if a show will be popular – before they approve an entire season. Netflix, on the other hand, commissioned House of Cards without the overhead and delays of a pilot episode.
Their decision to air the show was based on data – data which revealed that there existed a huge audience who would gladly watch a political drama. Netflix received this data from millions of online accounts and set-top boxes, and then used Hadoop, AWS computing power, and Spark to analyse the data. For Netflix, it was a risk rooted in factual data– and the risk paid off handsomely.
While the demise of TV advertising has been predicted every year, the fact is that TV advertising is still where the big money is. Marketers need to look at this as a point of inflection. Advances in technology are making it possible for companies to process enormous quantities of data and carry out intricate analysis without breaking the bank. TV marketers now have the power of machine learning algorithms at hand to predict audience preferences accurately based on historical viewing patterns.
Need proof? Read one for an inspiring tale of love between big data and advertising.
A Bit Data/Television Case Study
We recently helped a cable TV company identify prime ad spots for advertisers and channels using data collected from panels, set-top boxes, and smart TVs. The results were phenomenal and caused a 30% increase in promo conversion rate and a 25% increase in ad viewership. Here’s the complete case study which describes how they achieved this using the data they already had and without hiring analytics experts.
TV advertising is evolving to match its digital counterparts. Marketers need to embrace new big data-based approaches that drive reach, increase custom audience engagement, and measure attribution before they get left behind.