Those of you who work in video advertising already know the technological shift taking place where the lines between TV and video blur. Even if you’ve already worked with analytics in this arena, it’s obviously a challenge to keep up with the latest technological changes.
The biggest area to explore now is advanced TV and all the options viewers use to watch content. Due to everything from connected TV to OTT apps, the way people watch content is more fragmented than ever. While some lament us not watching TV collectively in one place, it’s still imperative to gather granular data.
What kind of metrics should you scope out in each of these new TV sectors?
Trying to figure out viewer behavior is always a major hurdle, especially when people change their minds so often on what they want to see. For more advanced media advertising, though, you’ll have to dig even deeper into viewer behavior.
Using third-party data providers, you’ll be able to gain a wider picture of viewer behavior when taking from multiple sources like satellite TV, OTT (Over-the-Top) apps, or smart TV’s.
Reports are that 79% of advertisers and agencies plan to use advanced linear TV throughout the year for the above purposes. As a result, traditional TV advertising is on a major decline.
While you might think of Google and Facebook as the only ones into behavioral targeting, all other media companies are jumping onto the same boat. Out of all those, 56% of them are using behavioral targeting now for more significant ROI.
Areas to focus on here include purchase history and intent, general interest, web navigation history, and customer relationship management information. All of these behaviors can have varying data, depending on the type of media device being used. Using AI and machine learning for this aids in more accuracy.
One thing you’ve likely tried to do is expand your audience on a geographic basis. With the world becoming smaller and other countries watching TV shows we only thought would stay in America or Europe, geographic targeting should become top of mind.
With addressable TV being another medium you’ll want to explore in extracting metrics, different geographic regions are perhaps watching the same live show. Using the addressable TV tactic, it’s possible to send different ads to targeted people collectively watching the same content.
You may want to target or limit ads to specific countries, states, postal codes, or DMAs (Designated Market Areas). Segmenting your analytics into regions like this helps you better understand the diversity of your audience and what their entertainment needs are.
By limiting your ad targeting to specific parts of the day, you’re able to better target the people you know watch certain shows when at their most receptive. The targeting on this is always tricky, though, because advanced TV is so diverse.
Those watching at particular hours could end up bringing varied results considering some might watch at odd times, especially on mobile devices.
As Google points out, AI and machine learning are at the forefront of scoping out this type of ad targeting to better customize personalized marketing experiences. You’re now able to send ads to those watching in the evenings, overnight, or just on weekends.
Contextual and Technology Targeting
In these realms of targeting, you’ll work with relational metrics and broadcast ads based on how people watch shows. For contextual targeting, you’d base your ads on surrounding content from a webpage or a specific streaming device a viewer uses.
Technology targeting goes squarely on what device the person uses to watch content. Keep in mind this isn’t limited to device or service. It can also mean what browser they use or operating system.