Step 3: Set Up a Foot Traffic Attribution Study to Tie Visits Back to the Campaign
The holy grail for any advertiser is proof that your advertising resulted in a sale. For advertisers in verticals where purchases largely occur offline, like furniture stores, online to offline attribution is more complicated.
This is where a foot traffic attribution study through a location intelligence platform, like Placed or Cuebiq, can make all the difference. These companies collect data from opt-in users to determine the real-world behaviors of smartphone consumers, like their location or proximity to a specific retailer. The goal is to measure how many people saw your ads and then went into one of your stores.
Here’s how it works: GPS captures device IDs as people enter your store. Then the platform matches those IDs back to the IDs of those who saw your ad through your cross-device identity graph. This gives you a clear answer on if your ads actually worked to bring in more foot traffic. By comparing your exposed visit rate to the unexposed visit rate (those who came into the store without seeing your ad), you can quickly calculate the lift from your ads. Plus, many platforms allow you to send panelists who visit your store a short survey to further evaluate product awareness and purchase intent between exposed and unexposed users.
You can also apply user attributes and behaviors tracked in a foot traffic attribution study to optimize your campaign. For instance, if a retailer sees that Hispanic audiences had a low delivery compared to other demographics but demonstrated a higher lift in visits, that meant this audience was more likely to visit the store but didn’t have to see as many ads as other groups to do so. With this in mind, you could increase bids on impressions to Hispanics for better cost efficiency.
However, it’s important to know that foot traffic attribution studies require a large volume of data to make these optimizations and comparisons. So you should work closely with your partner to ensure you have the scale necessary.
Knowing the advantages of using a foot traffic attribution study, we set up one to track users who saw our client’s connected TV furniture ads and then visited a store location. This opened the door to impactful insights that not only helped us optimize the campaign for better performance but also allowed our partner to prove their connected TV ads positively impact a person’s likelihood to visit their stores.
After running for nine weeks on premium connected TV inventory, the campaign doubled foot traffic into the furniture retailer’s stores. While the campaign delivered impressive performance results, our optimizations also ensured the campaign remained cost-efficient — saving on average $7.85 in cost per store visit. A win worth talking about!