Attribution has become a much more of a challenge for marketers as the path to purchase for consumers has become so fractured across multiple digital devices. Attribution is simply the method of calculating how to give credit to one or more actions taken that results in a desired outcome. For example, on Tuesday, Mary receives an email about a sale on her favorite jeans at a local department store. On Wednesday, as she is walking to work, she sees an ad on the side of a bus for the department store. That evening, she goes to that store and buys a pair of shoes. So, from an attribution standpoint, does the email for jeans get credit? Does the bus ad get credit (although there is no data that she saw it!)?

With the growing number of digital advertising outlets, determining how to resolve attribution for a display ad that was viewed on mobile but then led to a web search later that day with a click on a paid search ad makes multi-channel attribution quite difficult. Assumptions are often made using a variety of attribution tools that can aid in the challenge of valuing a variety of media impressions that can aid the marketer in future media mix or marketing mix decisions.

Most often, attribution models are built with a number of assumptions that are usually based on previous experience across particular media. Using the earlier bus ad example, there are estimates of how many impressions, or "sightings", of the ad that week occur in a pedicure time period in a particular geographic area. An increase in sales at the store in that location as compared to comparable stores, with ALL other variables being equal, will likely be attributed to the existence of the bus ad.

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