TV Attribution is Only as Good as the Data Behind It
This is a guest post from Robert Bareuther, SVP of Business Development, iSpot.tv.
Data is everywhere today. Streams of location data are pouring in from people's phones and cars. Cash registers and credit card companies, search companies, and social media platforms are, at every step, logging the consumer journey from point of interest to point of purchase. Watches are gathering heart rates. And TV sets have joined the fray as well: According to Nielsen, two-thirds of US households have a connected TV or Smart TV now, and those devices are capable of capturing viewing behavior on a second-by-second basis.
These new data streams are a bonanza for unscrupulous martech companies. They can get their hands on consumer data from millions of homes inexpensively, layer in a “probabilistic” math equation, and call themselves bona fide analytics companies. The scale might sound impressive—and in some respects, it is. But the problem is that while the size of the data is important, it’s actually not what’s most important.
Big data without measurement grade accuracy is dangerous. Especially, when it’s being used to measure the performance and efficacy of TV advertising, with million-dollar budgets at stake. For one thing, there is no such thing as a perfect raw data set. All data needs to be refined, sometimes quite radically, before it becomes usable for actionable measurement. Set-top box data for TV advertising measurement, for instance, may count viewing while a TV is off, or when the box is on and the TV is playing something else. ACR data may provide game-changing, glass-level impression verification, but it needs a reference ad to match against (something iSpot does at scale for all ads).
It’s great that a data model can inhale a trillion transactions, but what’s most important is that the data is clean, accurate, and actionable. Throwing “big” raw data into a model to make decisions with advertising dollars is like throwing crude oil into your car. Yes, it’s technically fuel, but because it’s not refined, not only will that not get you where you need to go, you’ll also end up wrecking your vehicle.
It's also crucial for the data to be fast. Many martech companies offer little more than handcrafted “insights” reports on a pretty dashboard. Those insights typically don’t come the next day, as promised, but the next week or month. Slow, stale data isn’t actionable or helpful for brands under pressure to defend and optimize their media buys, especially in today's fast-changing advertising landscape.
Once you have the right data, at the right level of granularity, and it's been properly cleaned and calibrated, you can start building attribution solutions with much more confidence. At iSpot.tv, our strength is television, and we've worked hard to help marketers make the most of our TV data to understand their consumers' viewing behavior. But TV, as strong as it is, is only one side of the coin. The best omnichannel MTA solutions are able to account for digital and offline advertising too. It's the interplay between all of those touchpoints that creates the best models. And the only way to connect all the dots is through a strong and trusted identity platform. That's why we're so thrilled to be partnering with Neustar.
Think of yourself as an aeronautics engineer. The data is your rocket fuel, and the equation behind your attribution model determines your rocket's trajectory. Get any of it wrong, and your brand will launch onto the wrong orbit—or crash back to earth.
To learn more about how iSpot, in partnership with Neustar, can help you measure and optimize the impact of your TV advertising on your overall business, click here.