Popular Pizza Franchise Generates Online Orders and Identifies Considerable ROAS with Highly Localized Messaging
YEAR
2022
ROLE
Media Strategy & Placement
COMPANY
Multi-Location Franchise
A franchise of a popular pizza chain with six stores in the northwestern U.S. wanted to better understand how its marketing efforts were driving results for its stores. The franchise typically places a heavy emphasis on direct mail advertising, so we took advantage of its existing relationship with its direct mail provider to leverage advanced targeting and hyper-local attribution solutions.
The advertiser wanted to promote special offers in six small towns in Idaho and Montana where it operates storefronts. It sought to drive physical visits to these locations, generate online orders, and achieve a positive Return on Advertising Spend (ROAS). Working directly with the franchise and the direct mail company, I developed a strategy to implement both location-based and online behavioral targeting tactics. They planned to track the number of customers who received an ad and later visited the pizza chain in person, as well as measure the revenue generated from online orders through their Slice POS.
The franchise wanted to promote its specials to “foodies” who were 25+ years old. Therefore, we curated addressable audiences at the household-level in real-time, based on hundreds of demographic and location variables through their direct mail provider. I then enlisted the help of a data scientist to develop audiences for each town that featured users who matched the target demographics, and loaded that targeting data and identified 37,029 relevant households through Meta and programmatic ad channels.
We also used 1st party customer data to upload an address list of customers from its loyalty program, which we uploaded into the ad platforms at an 87% match rate for an additional 18,907 households. We then used geofencing to pinpoint the exact shape and size of every address using publicly available plat line data, and drew target fences around each property to reach relevant users at the household-level across all of their devices.
Furthermore, the advertiser wanted to conquest customers from its competitors to gain additional business, so again, we used geofencing to target every person who walked into a competitor's location, then showing them our ads and tracking their walk-ins to our locations. I drew target fences around 68 competitors, including other pizza chains and local restaurants, to retarget users for up to 30 days after they visited those businesses.
To measure offline conversions on a store-by-store basis, I added Conversion Zones around each pizza store. This allowed us to identify the number of users who were
served ads and later visited the pizza chain, with clear, measurable attribution.
The franchise wanted to reach users who were interested in ordering pizza, so I deployed Search Retargeting and Keyword Contextual targeting to reach users based on the keywords they searched and the content they read. Targeting consumers at the keyword-level rather than using pre-packaged segments allowed us to ensure precise targeting. It also provided transparency into the data guiding impressions, including when and why users were targeted. For each store, I even adjusted the time frame during which it retargeted users, ranging anywhere from one week to one month later to test ideal messaging times.
Finally, to reach users who were already interested in the brand, I also implemented Site Retargeting. This enabled the franchise to retarget users who visited its website, thereby reminding customers to place their orders online and re-engaging them at the bottom of the sales funnel.
In addition to tracking online orders, the franchise wanted to understand how customers interacted with its website. Therefore, I tracked and reported on multiple conversion audiences to measure the number of users who completed online orders and clicked on buttons such as “Get Directions,” “Order Carryout,” and “Order Delivery.” The advertiser then used Transaction Value Reporting to identify the total revenue that was generated from orders placed by targeted users, ultimately helping the advertiser gauge the campaign’s ROAS and its effectiveness at generating online sales.
Mama Mia. They were juicy.
I now get free pizza for life.
© Guy Stuff Ventures, LLC
