Home On TV & Video Why Today’s CTV Attribution Models Fall Short

Why Today’s CTV Attribution Models Fall Short

Richard Girges, VP of Engineering, MNTN 

It needs to be said: Television is under-monetized.

I can practically hear the sound of a record scratch. Yes, TV ad spending still commands nearly $90 billion a year from US marketers, according to Insider Intelligence. But it’s a distant second to the $263 billion in annual online ad expenditures online media attracts.

Brand advertisers dominate traditional television, driving about $60 to $70 billion in revenue. The performance advertising sector, with its emphasis on attribution and targeting, is three times larger, totaling approximately $180 billion. It’s a crucial distinction. And it’s often overlooked.

Enter connected TV. Its unique ability to measure audiences’ engagement and actions in response to TV advertising has allowed marketers to align the soft goals of brand-building with the hard goals of driving direct sales outcomes. In doing so, CTV bridges the gap between branding and performance.

CTV is poised to become the third “big scale” performance advertising channel, but is effective CTV attribution actually possible? It’s up to marketers and their agencies to demand CTV solutions that promise deduplicated performance results by not assigning CTV credit for site traffic from other media sources.

When spike analysis loses its sharpness

In branding, one buys ads. In performance, one buys traffic. Marketers don’t negotiate with Google to buy ads; they go to the search giant to buy traffic to their brand’s sales channels.

This is where media buyers and their ad clients struggle with managing attribution and targeting on CTV. Specifically, the trouble manifests when traditional TV methods are applied in a CTV context. 

Case in point: Geico’s success as both a brand and performance marketer would seem to hold the key to unlocking CTV attribution. As an example of linear performance advertising, it’s hard to beat Geico’s iconic tagline, “15 minutes could save you 15% or more on car insurance.” The company historically relied on spike analysis to gauge the impact of those ads, which involves measuring response rates immediately after an ad is served at a specific broadcast time.

This technique falls flat in the on-demand, time-shifted realm of CTV. In a streaming environment, individuals watching the same show on different devices may receive different ads at different times. Attempting spike analysis in such a scenario is futile, resulting in wasted advertising dollars.

Transparency: Credit CTV where it’s due


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Performance marketers using CTV – or digital video in general – have typically been relegated to a form of view-through attribution to determine cross-device site traffic, conversions and return-on-ad-spend (RoAS).

View-through attribution looks at the point when someone sees an ad and later visits the marketer’s website. In this method, the credit for that visit goes solely to the ad.

That seems reasonable. But here’s the thing: View-through attribution can sometimes give too much credit to that ad. It doesn’t consider that the person might have visited the website for other reasons, like clicking on a different paid advertisement, email call-to-action or organic social post. 

Advertisers need to measure the impact of their ads in a way that considers different factors and only gives credit to the ad when it truly has a clear impact.

To accurately attribute conversions by CTV, brands need to adopt attribution that takes into account the other paid and organic ad channels they’re actively supporting in-market, such as paid search and social.

Among the clearest solutions is attribution that automatically analyzes Urchin Tracking Module (UTM) codes, which are pieces of code attached to the end of a web address. UTM codes are also used to locate specific sources that deliver traffic to a site. In this case, the model can see that another channel actually delivered a site visit and won’t take credit for that site visit. 

Crossing over

Cross-device attribution is a necessary first step to create a form of “last touch” attribution for CTV campaigns.

The television serves as the first device, followed by smartphones, tablets or computers. Connecting these devices can be accomplished through various methods, such as unified IDs or household IP addresses. Additionally, connections can be filtered to exclude public spaces like coffee shops or airports, ensuring accurate attribution.

Once the devices are connected, a “visit” can be established after an individual views a CTV ad and then visits an advertiser’s website on a secondary device, replacing the traditional concept of a click for a non-clickable channel. Conversion attribution then becomes straightforward, allowing direct response marketers to focus on metrics such as return on ad spend (RoAS) and cost per acquisition (CPA).

But cross-device attribution doesn’t provide an accurate picture of the impact an ad had unless you have source-validation to ensure credit is only given to CTV when it’s actually earned. Accurate incrementality measurement can provide another layer of validation.

Applying the scale of attribution that has been achieved through online performance marketing, we are on the cusp of a new “golden age of television” advertising that represents the best of both worlds.

On TV & Video” is a column exploring opportunities and challenges in advanced TV and video. 

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