Modern TV attribution methodologies bring three worlds together. The first one, called top down, specializes in strategic measurement across all marketing channels. The second one specializes in measuring tactical allocations in addressable channels, such as digital. And the third one specializes in measuring tactical allocations in offline TV advertising. Getting access to the right type of data is key, but applying the right methodology to leverage its power is what makes the information actionable.
Impressions and rating points are good indicators of how many people saw your TV ad, but how does it influence individual consumer behavior? Consumers take action online in response to seeing your ad offline. But which types of TV ads trigger the greatest response?
To ensure you’re getting the most accurate answers to your questions, make sure your TV attribution methodology does the following:
Applies an algorithmic approach: The methodology should be able to ingest very granular TV and digital response data to build a highly accurate model that predicts the impact of TV on digital responses. Understanding TV’s impact by network, daypart, pod position, designated market area (DMA), timestamp, among others is critical to the TV buyer. Similarly, the same methodology should be able to ingest granular digital stimulation data. This will allow marketers not only to see the impact of TV on digital responses, but also see TV’s impact side-by-side with individual digital channels to gain a holistic view of performance.
Doesn’t make assumptions: Even though traditional TV is not addressable, some methodologies attempt to guess which of your digital users have also seen your TV ads. By artificially adding TV touchpoints to the sequence of digital touchpoints for some of your users, it negatively impacts the accuracy of your attributed metrics across all users. As a result, not only will the credit attributed to your TV advertising be inaccurate, but it will also skew the credit attributed to your digital channels.
Predicts the tail effect: The “tail effect” is the window of time between when a TV ad is viewed and when the viewer takes an action online in response to seeing that ad. It would be inaccurate to apply the same tail effect to all of your TV ads in order to make the assumption that all digital responses within the tail effect window should be attributed to the corresponding TV ad. There are too many variables that have an impact on tail effect. For example, daypart can play a big role. Early-morning TV ads may have a longer tail effect than prime time because viewers have more time to take action online in the evening. The algorithm should be able to figure out this changing tail effect at the spot level.
Accurate TV attribution takes the guesswork out of determining which combination of tactics drives the greatest digital response in order to more effectively allocate TV budget moving forward.
This post was previously published in an earlier edition of Metrics Insider.