Campaign Optimization Is Enhanced by Algorithmic Attribution

Campaign optimization through attribution is a hot topic for digital marketers, 58 percent of whom say it’ll be the top tactic occupying their time and resources this year, up 22 percent from last year, according to eMarketer.

 But the measurement criteria for attribution is undergoing an evolution from traditional last-touch and first-touch models to more sophisticated computer-generated statistical models that help both buyers and sellers better optimize media spending and consumer targeting.

Algorithmic attribution offers advertisers the ability to react more quickly to competitive changes in the market, eMarketer also noted. But between traditional market-driven forms of attribution and the brave new world of algorithmic attribution, which model allows marketers the flexibility and creativity to better track the path from search to consideration to purchase?

Attention to Incrementality
Whether traditional attribution, like Media Mix Modeling (MMM), or algorithmic, such as Multi-Touch Attribution (MTA), attribution is essentially the practice and measurement of incrementality—the amount of change caused by a small increment of input. In studying the incrementality of attribution, much depends upon the product—cars compared to toothpaste, for example—and the length of consideration time before purchase.

Read my full article on the Videa blog.

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