Marketers, driven by demands to demonstrate true incremental impact, will increasingly look to more statistically rigorous techniques. These include media mix modeling and randomized controlled trials, which can help determine the channels truly delivering value and the channels simply coming into incidental contact with customers as they move along their customer journey.
This post is part of our 2023 Data Transformation Outlook series
Hot Take on Marketers’ Hot Seat
The Complete View of Customer’s Interactions: A Siren Song
When digital advertising emerged in the early 2000s, companies rushed to embrace it. That was the right call: marketers need to put their messages in front of their prospects’ eyeballs, and their prospects’ eyeballs were (and still are) spending more and more time looking at screens. The bonus of that shift—or, so it was thought—was user-level visibility into their customers’ journeys and what that might mean: A complete, rich dataset would finally deliver “the truth” about the value of each channel and each hyper-detailed tactic within each channel!
Unfortunately, this misunderstanding became Accepted Wisdom: Maybe a last click model wasn’t “accurate,” but then, surely, a linear attribution model…or a time decay model…or a data-driven model would yield “the truth.” Of course, the dataset was never particularly complete—tracking a user across different interactions, across different devices, over time, and from online to offline (and vice versa) has always resulted in broad, deep, unknowable holes in the data.
And, those holes have gotten exponentially larger. Bots are on the rise (nefariously arbitraging brands’ media dollars into their bank accounts), privacy regulations are drastically curtailing when and how brands can track user behavior, and privacy changes in browsers and operating systems are further cutting off that visibility.
Today’s Attribution Problem
But, that’s not the main challenge! Consider the branded paid search conundrum: “How many of the users who are coming to our site from clicks on our search ads when someone searches for our brand would have come anyway by clicking on an organic search result if our paid search ad wasn’t there?”
This problem exists across all channels. Media targets “users who would be most likely to buy their product or service.” Unfortunately, that media will invariably target some users who would have bought anyway. This is simply a reality, but the more marketers (and their finance counterparts) realize this, the more they will realize that those “would have bought anyway” interactions are not delivering incremental value to the brand, and, therefore, should not get credit for delivering value.
The Antidote to the 360-Degree Fallacy
Media mix modeling and randomized controlled trials are two techniques grounded in decades of research and refinement in fields extending well beyond marketing. They both estimate the incremental impact of individual channels in very different ways.
The Importance of Showing Incremental Impact
The Importance of Online and Offline Tracking
As a bonus, both media mix models and randomized controlled trials have no reliance on user-level tracking and can easily factor in both online and offline media and results!
