How retail, quick serve restaurant (QSR), and fuel and convenience marketers can use driving data to reach customers based on where and when they drive
This blog is the third in a series that will discuss how marketers can leverage private marketplaces and audience targeting to reach their best customers. Read the first and the second post.
In our last blog post, we talked about how auto insurance carriers can use driving behavior data to reach their best customers.
In this article we will cover how marketers for brands with physical locations – specifically, retail, quick serve restaurant (QSR), and fuel and convenience brands – can leverage driving behavior data to understand where and when consumers are driving, and reach them with relevant messaging before they even get behind the wheel.
Brands with brick-and-mortar locations need to find effective ways to entice people into their stores. Digital marketing traditionally has been used to get customers to click on a link and land on a website. But how can marketers use digital ad campaigns to drive traffic into their stores? That can be tricky at best – unless marketers have access to information about who passes by their stores regularly and can reach them with messaging at precisely the right time.
Predictive Point of Interest data
Marketers can leverage driving behavior data to do just that. It’s called Predictive Point of Interest (POI) data, and Arity enables marketers to use it in the Arity Private Marketplace, to reach consumers based on their driving patterns and habits.
For example, if a consumer drives past a certain coffee shop twice a day at 8 a.m. and 3 p.m., the coffee shop can show them an ad at 7 a.m. and 2 p.m. – an hour before they’ll be driving by – with an offer to stop in and enjoy a beverage. In the morning the ad could promote a coffee, and in the afternoon, a light snack. Understanding how people move through the world and getting a specific message in front of them at just the right time is a powerful way to drive foot traffic and sales using digital media.
Let’s look at how different types of marketers can use Predictive POI data to drive traffic to their locations.
Retailers are always looking for more ways to drive foot traffic into their stores. In-store traffic to major retailers fluctuates depending on factors like fuel prices and the economy, so retailers must employ a variety of strategies to get people into their locations to stay competitive.
Retail marketers can leverage driving data to:
- Offer coupons to drivers who frequently pass by their location
- Understand where a customer goes before and after visiting or passing their store
- Display an ad to consumers who often drive past their store and to a competitor’s location
An example: A major beauty supply chain notices that business is down among a key customer segment: 18- to 25-year-old women. By examining the driving behavior data of their customers, they notice this demographic is more often driving past their locations than stopping in. They can also see that this segment is actually driving to the locations of a competitor; a start-up brand whose advertising skews younger. Using this information, the brand creates ads that resonate with younger customers and displays them to people in their target demographic who frequently drive past their stores and to the competitor’s locations.
Quick serve restaurant marketers
Quick service restaurants (QSRs) are constantly vying for the attention of hungry and thirsty drivers. How do you stand out along the crowded roadside? For QSRs, using driving data to attract customers is just the start — more advanced applications could even positively impact operations.
QSR marketers can leverage driving data to:
- Offer specific drinks and meals to drivers depending on time of day
- Identify and predict new “rush” hours
- Better plan ingredient and supply orders
An example: A large national sandwich chain dealing with a dip in business can’t pinpoint why their famous lunchtime deal isn’t attracting the customers it used to. Has the promotion finally run out of gas? A closer look at the data reveals that customers in certain regions are more commonly driving past shop locations in the morning. To remedy the problem, the sandwich chain pilots a new breakfast menu in those areas and runs a location-specific campaign to entice customers to stop in for breakfast instead of lunch.
Fuel and convenience marketers
Higher fuel prices and inflation have led to an increased sense of urgency to attract customers for non-gas items at fuel and convenience businesses. But high prices come and go, leaving marketers in fuel and convenience eager for new ways to get drivers to make a stop.
Fuel and convenience marketers can leverage driving data to:
- Increase foot traffic by more accurately predicting which drivers are most likely to make a return visit
- Offer deals to drivers based on where and when they drive
- Reach drivers who spend the most at the pump
An example: Two regional fuel and convenience chains have competed for customers along the interstate for decades. Amid rising gas prices and inflation, prices in big, flashy numbers on signs outside the pumps won’t work as well as they used to. But the marketing team for one franchise has insight into what’s changed along the highway beyond the numbers on the gas signs — specifically, driving behavior data.
With this data, the team creates a campaign that targets long-haul drivers and super-commuters, rewarding return visits with special offers. The chain captures new customers and drives repeat business before their competitor, solidifying their place as a roadside leader.
Although brands have long used first-party data and online behavior data to understand their target audiences, this information can only offer you so much. Driving behavior data gives marketers a 360° view of their consumer and can help brands better connect with their customers – and get them in the door.
Our next post will cover how the Arity PMP can help automotive marketers find their best customers using Predictive Point of Interest and other types of driving behavior data. Stay tuned, and learn more about the Arity PMP.