If you've ever been at the point where you're very close to deciding to buy something but not quite there yet, you know how effective advertising can be.
Imagine for instance that you're fed up with your telecom service and you've decided to switch. Ideally, during this time a telecom would run an ad during your favorite program. To entice you, the service might mention that anyone who comes to a store in the next three days will get a special deal.
Until recently, targeting to that one individual user wasn't an option. Instead, a marketer would have to run local ads of a suitable demographic, such as people between the ages of 18-49. For 99% or so of viewers, that ad might not communicate a relevant message. Thanks to addressable ads, that dynamic has changed: Marketers can use data to target people relevant to their product or service at the household level.
Behavioral data makes addressable advertising a great fit for nudging consumers who are in the purchase stage. For instance, it's possible to isolate people who, based on their web searches, are in the later stages of buying a car. This allows marketers to have conversations with consumers who are one step away from purchasing. In a recent real-life example, a compact SUV maker targeted in-market auto intenders (households likely to buy or lease a compact SUV in the next six months) with an addressable ad campaign. The brand enjoyed a 5:1 ROAS (Return on Ad Spend) and a 12% lift in buy rate compared to the control.
The one caveat about addressable is that the math has to make sense; CPMs are higher when targeting in a more granular fashion. A higher CPM may not make sense if you're selling fast food. If that's the case, a continuum or blend of media will bring down CPMs. Marketers should work out the math to understand the cost per acquisition against media spend.
Television indexing also makes sense in the buy stage -- data science can help advertisers find correlations in content and consumer interests so that marketers can deliver specific messages to segments most likely to buy. If a telecom has a few service options, for instance, it could place a buy for people in the 18-49 demo for shows that tend to attract people who use a lot of cell phone data. If the data indicates that a particular TV show draws more viewers fitting that description, then the telecom might want to spend a bit more to advertise on that program. The advertiser can go beyond standard demo-based buying by layering data and reach customers relevant to its brand.
The purchase stage isn't as linear as it once was. Some customer journeys take a minute or two -- an ad for pizza at 5 p.m. on a weeknight might prompt a call for pizza delivery -- while something like priming a cell phone service buyer could take years.
While addressable TV advertising gives marketers a new tool in their arsenal, for most it's the mix of broadcast, local and content indexing which they can constantly refresh with addressable that works best for them. Determining the exact mix, of course, will vary tremendously, but a close look at the data should lead marketers to a strategy that maximizes purchases, boosts return on ad spend and gets ads in front of the right consumers at the right time.
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