Case Study: QSR Achieves 20% Sales Increase with Location-Based Targeting

Tracking foot traffic with location-based ads in QSR restaurants is often the first step towards increasing sales and revenue, and maximizing operational efficiencies. 

According to a new case study from the adtech firm Simpli.fi and Commerce Signals, a company that connects advertisers and publishers with insights from financial institutions, a well-known quick-service restaurant chain with 135 locations nationwide was recently able to leverage location-based targeting and online retargeting to achieve a 20% sales increase in just 27 days. That sales lift resulted in 9,635 actions—either via online or in-person visits—at a cost per action of $4.89. 

To achieve those results, the QSR chain worked closely with a national broadcast company that acted as an advertising partner, and launched a digital campaign relying heavily on Simpli.fi’s geo-fencing and online retargeting solutions, along with Commerce Signals’ payment data sets that matched store-level transaction data to served impressions. 

Utilizing a longtime partnership with Simpli.fi, the national broadcast company and the QSR chain were able to establish a strategy based on location-based targeting and retargeting. They then recruited Commerce Signals to match store-level transaction data to served impressions, in order to determine the sales lift for both in-store and online purchases.

Simpli.fi built target fences around a one-mile radius of each restaurant location and served display ads to users in those areas. The company’s team also drew smaller conversion zones around each of the QSR’s 135 locations to measure the number of users who visited the restaurant in-person after being served an ad. 

At the same time, the broadcasting company deployed CTV ads via a proprietary segment for the QSR chain. Simpli.fi retargeted users who were served those CTV ads with display ads across their other devices. This allowed the QSR’s marketing team to track online actions taken across devices, regardless of where the ad was served.

Increasing online and in-store visits at a low cost per action (CPA) wasn’t the QSRs only goal. Executives at the restaurant chain were also interested in understanding how much sales lift could be attributable to the campaign. To achieve this, they compared actual transaction figures to advertising impression data using technology from Commerce Signals.

Commerce Signals Chief Marketing Officer Nick Mangiapane says the QSR in this case study is far from the only restaurant chain to use transaction-based audiences to match store-level transaction data to served impressions. In fact, he says the approach is actually quite common in the industry.

“Many restaurant marketers are already using transaction-based audiences, they just don’t shout from the rooftops about it,” Mangiapane says. “They have no incentive to tell their competitors what’s working for them. That’s why our case studies are usually unbranded.”

Customer loyalty has become a major challenge for QSRs in 2023. Because most restaurants don’t know who their customers are, it makes it hard to influence them or encourage them to return. By targeting past customers using anonymized payments data, like this QSR chain did, Mangiapane says restaurants can get their marketing in front of the people they’re actually looking to influence.

“Restaurant marketing teams are often asked to do a lot with relatively few resources, making it difficult to keep up with changes in marketing technology,” Mangiapane says. “The good news is that targeting using transaction-based audiences is as easy as asking your media agency or digital marketing team to do it.”

For restaurant chains that are interested in leveraging a similar targeting strategy in a privacy-safe way, Mangiapane suggests only working with companies that use anonymized data, and choosing audiences that are modeled, but not precise, in order to avoid “creepiness.” He also recommends that brands avoid bringing any data in-house that isn’t compliant with those first two suggestions.

“Connecting ad impressions to purchase transaction data is so valuable because it shows marketers what works – which creative, promos, ad types, day parts and DSPs drive incremental revenue,” Mangiapane says. “Armed with sales lift measurement, marketers can optimize for better outcomes.”