The promise and challenges of advanced TV advertising

The promise and challenges of advanced TV advertising

Tom Weiss, Sun 24 March 2019

There are lots of definitions for and components of advanced TV advertising, but at its simplest, we use the term as a catch-all for improving TV advertising through the application of data, as opposed to relying on more traditional research-based data sets

Traditionally, a company trying to sell ad-space on TV would use Nielsen data, or a local equivalent, to show to potential advertisers that Show A had an estimated audience of X, and that Show B had an estimated audience of Y, and that Shows A and B had specific demographic make-ups defined by the Nielsen data. If X>Y, and if X represented a more attractive demographic to advertisers (e.g., young men) than Y the company would charge more for a commercial in the ad break in Show A than Show B. Or so the logic goes.

With advanced TV advertising, panel data is now only one among many datasets, which as a whole reveal more about who is watching a commercial and to what extent those watching it end up clicking through to a product website, order a sample or buy the product (this is known as TV attribution - more on this later)

These sellers of advertising space are also using addressable television to target particular ads at particular households when the technology allows, such as in an OTT service, a smart TV or via a set-top-box device. So a sports-mad household can be targeted with sportswear where a family with young kids might be targetted with ads for diapers, while both households are watching the same comedy.

Such is the promise of advanced advertising. But when we work with companies trying to carry out advanced TV advertising campaigns, we see often see them come unstuck around a couple of key areas: data quality, and accurate attribution. 

You’re only as good as your data

The key to all advanced advertising is both having accurate data, and knowing how to use it. Without both, your advanced advertising efforts may come unstuck. Here’s a simple example to demonstrate the point. Let’s take our theoretical household from the start of this post. If we know that the household is a family with young kids, but that the mother is also sports-mad, the reality of how to target this household is complicated. Skillful data scientists can attempt to understand individual viewers by reporting and modeling the data to create an individual viewer model (to understand who is watching the show within a household beyond the device level) to try and solve this. So can data from brokers like Experian, although as we have warned before third-party data sets can have issues of their own.

But TV here is inherently at a disadvantage vs. Google et al., where the fact that people are logged in to a computer and/or using a personal mobile makes it much easier to identify the individual exposed to the ad.

Challenges in attribution

Attribution makes it way more complicated; advertisers on digitial only pay for clicks or actions, such as a user buying content after clicking through to an ad. TV is starting to get into this act, too, but typically TV advertisers still pay for impressions. Advanced advertising doesn't merely mean using data to improve targeting. We can also use it to measure, as precisely as possible, the ROI of money spent on advertising - .e.g, has someone who watched an ad clicked through to a website, ordered a sample or even bought a product.

Facebook and Google have used their walled gardens of data to attribute to devastating effect, helping create what is essentially a duopoly in online advertising, and TV companies have started to take notice and act. Much of our work with customers is focused on making the TV experience more similar to digital, helping to use data to make the TV more targetable, more addressable, more accountable, and outcomes better attributed to activity. This can include measuring addressable TV and bringing online segmentation models and techniques to advanced advertising. 

But attribution from a television ad needs data you can match. Counting the number of new users who accessed the site within an hour of the ad appearing isn't very reliable, mainly as not everyone uses other devices while watching TV. Perhaps I saw an ad for a pair of sneakers yesterday, and my subconscious has been wanting them ever since, but I only go to the site today. TVs also works, as an ad medium, by repetition. Perhaps after six weeks of seeing an ad for a brand of washing powder I have never used, I decided to try it instead of my regular brand. One or two ads from this new for me washing powder may not have changed my mind at all, but an accumulation of commercials banging on about this brilliant new washing powder may well work. This branding power, after all, is what TV advertising has been built on over the years, and will continue to do even as it becomes more measurable and attributable.

These are but some of the challenges that advanced TV advertising faces, but we remain very bullish about the future of TV advertising, as it starts to integrate some of these new elements into what has always made it a great medium. 

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Dativa is a global consulting firm providing data consulting and engineering services to companies that want to build and implement strategies to put data to work. We work with primary data generators, businesses harvesting their own internal data, data-centric service providers, data brokers, agencies, media buyers and media sellers.

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