RetailMeNot has introduced new Mobile Attribution for retailers and restaurant marketers to determine their return on advertising expenditure through RetailMeNot mobile campaigns.
This new Mobile Attribution powered by RetailMeNot analyses user actions within the app and uses location data to quantify in-store footfall, attributable sales and sales increment.
RetailMeNot’s vice-president of products Jody Goehring said: “RetailMeNot is leveraging location to understand consumer shopping behavior and the impact of digital content on physical retailing.
“Location is to mobile what the cookie is to desktop. With the majority of our users opted-in, we now have a more complete picture of the consumer shopping journey and are able to offer more relevant content to consumers within that journey."
To determine attribution and incrementality accurately, RetailMeNot refined its ability to measure digital and mobile campaign effectiveness so it combines anonymised consumer information that includes first-party data, geo-fencing and latitude-longitude data with algorithm-based smart proximity detection for better results.
This new combination of data will help retailers to evaluate their in-store footfall and sales resulting from their campaigns run with RetailMeNot.
Store visits are based on average, anonymised data collected from a sample set of users with location services turned active on their smartphones. This data is then extended to represent a cross-section of representative consumers throughout the country.
Charlotte Russe marketing vice-president Kate O'Hare said: “This new method of calculating attribution is a powerful tool for me.
“With the study, I can clearly see that my mobile marketing spend yielded a strong return, which is on the conservative side of the actual ROI. The combination of data, location and consumer insights helps me clearly articulate the value of mobile marketing via RetailMeNot channels on my in-store sales.”
Image: RetailMeNot Mobile Attribution Performance Funnel. Photo: courtesy of RetailMeNot.