Three Ways to Solve for Foot Traffic Attribution
Tying ads to online conversions, purchases, and sales is simple and straightforward. Most ad platforms display these metrics on their dashboard home pages. They show you your ad spend per channel, click-through rate, and conversion value. Here’s what that looks like in Google Ads.
What most ad platforms cannot tell you is how your ads drove foot traffic to stores and other physical locations you care about. If driving foot traffic to retail locations is your job, Google Ads and other digital ad dashboards can’t help you. When in-store foot traffic attribution is crucial, how do you solve for it?
In this article, we cover three ways to solve for attribution, ranging in difficulty from easy to hard. We look into easy options that are inexpensive but tend to be unreliable. We evaluate a medium option that has a moderate cost but is highly reliable and bypasses human error. And lastly, we look at a hard option that incorporates several tools and, while highly reliable, comes at a high cost and is difficult to scale.
The simple question “how did you hear about us?” may seem like the best way to find out where your customers heard about your store, but there are drawbacks to this solution.
First, you can only ask customers who gave you their information or are making a purchase in store. This dramatically reduces your data set. Stores will not capture casual shoppers who pop in or who are never entered into the POS system. FocusVision, a consumer survey company, reports that response rates may be as low as 5%.
Second, when customers do answer how they heard about your store, you have to rely on their memory. They may have heard a radio ad, seen a billboard and heard from a friend, but they may have forgotten some of these channels, or the survey may ask the shopper to select only one answer. Answers, when accurate, may be highly variable, making it difficult to discern patterns.
This tried and true option is still viable. Use a keyword in your CTA on your digital ad or send a flyer to the zipcodes you hope your customers live in and tell them to bring in the coupon to receive 20% off their purchase. Codes are typically campaign-specific and can easily tie ads to in-store traffic. This option has its weak points. Customers may forget the keyword, leave their flyer at home, or come in when the coupon is expired.
Location Data-Powered Foot Traffic Attribution
The power of location data drives the most reliable solution to foot traffic attribution, tying digital ad spend to in-store visits. With location data, advertisers create custom audiences of visitors to locations they care about and serve ads to those people. These audiences can be made up of current customers, your competitor’s customers, and visitors to locations advertisers otherwise care about. In your location-based marketing software where you created or accessed the audience, you can see what portion of your target audiences showed up in the locations you are advertising and calculate attribution.
Depending on the tools you’re using, location-based marketing software can also show you more detailed reports, such as foot traffic by day and comparisons to your competitors’ in-store traffic.
Advertisers can take foot traffic attribution powered by location data a step farther by using pixels within their ad serving platform. With the addition of a pixel, marketers can see who was actually served the ad and tie that cohort of viewers to in-store visits. Combining location data and pixel tracking makes foot traffic attribution even more granular and powerful.
The final and most difficult option for tying ad spend to in-store activity is what happens at checkout — what the customer actually buys and how much they spend. This provides the most detailed analysis of ROI on digital campaigns; however, visit, point-of-sale, and transaction data intersect with several layers of the tech stack, and the data can be siloed and difficult to integrate. Brands and retailers run multiple systems, and these depend upon complex, tight integrations. This takes engineering time and dollars.
Solving for foot traffic attribution is not hard when you take the right approach. To determine which is best for you, you must define your goals and decide how much you want to invest in attributing digital ads to in-store visits or transactions. The middle path is an ideal option for the many brands and retailers and the agencies that work for them.
Street Fight recently reported on other ways marketers are making in-store metrics more reliable.
Laura Conway is the marketing manager at Reveal Mobile, a provider of location-based analytics, audiences, and attribution software.