Being able to track offline purchases and offline attribution is imperative to any traditional retailer. In 2014, U.S. retail sales amounted to $4.6 trillion. Of that, only 6.5%, or roughly $300 billion, came from e-commerce. This gap suggests that offline retailers are still struggling to find solutions that can efficiently and accurately link online media spend to in-store conversions. Advancements in cross-device identity, marketing automation, and consumer profiling have generated a lot of excitement over the last couple years (and rightfully so). But notably absent from this fanfare has been offline attribution. Traditional retailers need to find ways to efficiently measure their advertising spend, and given that the majority of their customers are available digitally, this becomes a very important problem to solve. Currently, marketers can track online conversions with deep customer and performance insights. These insights, however, become lost once the conversion moves offline. While cross-device identity solutions have enabled marketers to target users more efficiently, they still are unable to reliably tie a mobile ad to an in-store purchase.
Today, there are currently two solutions that attempt to solve this offline attribution problem. The first marries purchase and CRM data to cookies (via cross-device mapping if served on mobile device). This method can be costly and mapping breakages occur when customers are exposed to ads on multiple devices. The second (newer) approach marries store visits (via mobile location data) to location data passed in ad requests, allowing a match to occur between when a consumer sees an ad and when they are in a store. In addition to these two methods, there several key metrics that are used to measure offline conversions. These include store visits (exposed to ad prior to store visit), conversion window (determines look-back window in which an ad can receive credit for store visit), conversion rate (store visits/impressions), cost per store visit (media spend/store visits), and lift (difference between exposed vs unexposed). Given the current solutions and metrics, here are 4 tips to more efficiently measure offline conversions and help in solving the offline attribution problem:
(1) Determine a reasonable (and meaningful) conversion window – Depending on the type of retailer, a shorter conversion window might tell you more about a campaigns impact. This is particularly true for large big-box retailers (WalMart, Target) where there is a ton of foot traffic. This piece is particularly key to solving the offline attribution problem.
(2) Pick one data set to benchmark against – If you are using multiple data sets, it becomes much more difficult to measure the offline conversion lift (particularly against different segments) and the offline attribution problem becomes greater.
(3) Explore “store visits.” Instead of installing a costly CRM system, consider exploring the store visits method. Many leading attribution vendors have developed unique solutions in this field and are solving this piece of the problem in big ways.
(4) Make sure to align your attribution system with internal KPIs (all of them). If you don’t do this early on, it becomes very difficult to measure lift, both online and offline, and truly understand the impact of your media campaigns.
Below we have compiled a list of metrics that could be relevant for most B2B marketplaces and hope that it serves as a framework for tracking KPIs for success.