Closing the Retailer Purchase Loop: Solving the Challenge of Attribution

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You’re on your way to work when you pass a billboard featuring Nike’s newest running shoe. That reminds you: you just signed up for a half marathon, so you’ll need some new gear. You start googling top-of-the-line running shoes on your phone. You forget about the race until days later when looking at Facebook on your laptop, and there they are: the same shoes that caught your eye. Still, you won’t purchase them until you try them on. So what a pleasant surprise when, on your walk home, a banner ad appears across your phone: “You’re 3 minutes from a Nike store,” it says. Why not stop by?

If you go into that store and purchase those shoes, which ad was it that led to the conversion? Was it the original billboard, the social media ad, or the location-based banner? Perhaps a perfect combination of all three?

These questions reflect the challenges every marketer is currently facing when it comes to attribution. Today, a typical path to purchase is no longer a straight line to the point of sale. It looks more like a latticework of ads both online and offline, on our devices or in our neighborhoods.

Yet despite this added complexity, brands can begin to solve the mystery of attribution and determine the value of each marketing touchpoint. They just need to follow the footsteps.

Understanding Footsteps to Purchase

Brands can get a better understanding of which campaigns are boosting their ROI by taking a look at how digital ads directly relate to foot traffic.

First, advertisers can conduct an A/B test to determine which ads are bringing people into their brick-and-mortar retailers. By comparing how many devices were seen in store from an exposed group (devices that received an ad) to a control group (devices that didn’t receive an ad), brands can figure out what’s working and how well. This is the kind of study we conducted on a series of CPG brands earlier this year—where we found an astonishing 47 percent uplift in foot traffic for the exposed group.

Location data can also reveal more than just how many devices made it into stores. It can also tell advertisers the average time it takes for someone to enter a store after seeing an ad, or which locations are performing best. Brands can also layer this data with purchase histories and sales data for even more insightful stats and figures into how their customers are responding to ads.

So once brands have uncovered all these clues into what’s driving conversions and how, what do they do with it all?

Step Up Your Campaigns

Brands don’t strive for accurate attribution just for the sake of it. They want to know what’s causing conversions so they can do more of it—and cut out what might not be working at all.

An energy drink brand, for example, can use data about foot traffic and sales to make sure the next iteration of their campaign performs even better. Let’s say the brand discovers that people are 50 percent more likely to go into a store that stocks the energy drink when they receive an ad within 200 feet of the retailer. Rather than targeting everyone within 500 feet of the retailer, the brand can eliminate waste by just reaching out to those within a much smaller radius.

What if advertisers discover that no matter what distance, more people seem to be purchasing the energy drink from Walgreens than CVS? Perhaps next time, they can put a greater share of their ad budget into targeting those near Walgreens.

By solving some of the mysteries around attribution by finding which campaigns are driving sales, advertisers can continuously optimize their campaigns. And that means less waste and a greater bang for every marketing buck.

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