Are your customers visiting your location – or passing you by?

Many retailers collect and analyze a wealth of consumer data, but they lack the resources or expertise to understand a key piece of the puzzle – the real-world driving patterns that could bring a customer back to the area for future purchases.

From mobility data to predictive analytics 

Mobility data can be the key to optimizing your predictive analytics tools. With mobility data, retailers can unlock insights that help brands better understand the driving patterns of their target customers.

Mobility data takes predictive analytics one step further. Predictive analytics leverages mobility data and extrapolates future driving patterns. Brands can gain line of sight into, for example, when someone will likely be on the move, where they are going, when they are going, and the route they take to get there before they head out the door.

Mobility data is the new frontier for predictive analytics for retailers.

Predictive mobility as a customer growth and engagement strategy 

Predictive mobility enables retailers to:

• Understand how and when people are driving past your and your and competitors’ locations, in aggregate
• Optimize out-of-home (OOH) advertising opportunities based on traffic patterns
• Increase downloads of your own mobile app by advertising it across Arity’s mobile publisher partners
• Drive in-store and online revenue by displaying ads for your brand to highly engaged audiences
• Enhance user engagement by delivering timely personalized content, offers, and recommendations based on predicted behaviors
• Expand loyalty program membership by reaching consumers more likely to join

Predictive mobility to transform the customer experience 

By leveraging predictive mobility data, retailers can craft a more relevant and personalized experience for users by providing insights such as:

1. Customer behavior: Understand a fuller picture of their real-world consumer behavior through the lens of driving data.
2. Common routes: Insights into frequently traveled routes can indicate when someone may be passing a specific location on a drive they often make. Before they even get in their car, the consumer may receive a notification such as: “Stop in for 25% off any breakfast item, today only” which happens to be along the route they will take that day.
3. Location: Strategic decisions can be tailored to location details to help narrow down points of interest for consumers and yield a better understanding of their buying needs for more accurate messaging and offers.
4. Trip frequency and duration: Gain insights into average times on the road or durations at various locations to understand where consumers are spending their time. This can help you determine where and when your consumers should receive certain types of messaging.
5. Mode of transport: A mobility data SDK can help you understand top methods of transportation in specific regions.

Marketing use cases for retail 

Retail marketers can use driving data in many ways to improve their customer lifecycle strategy, turning consumers into loyal customers and active app users.

• Precision targeting: A person who makes regular morning commutes sees an ad with a coupon for a QSR that they often pass on those drives.
• Enhanced customer engagement: A QSR app user sees in-app offers for coffee on the days they drive in the mornings and snacks on the days they drive in the afternoon.
• Competitor insights: A person who often goes to one QSR realizes that another QSR they pass regularly has a similar menu at a better price based on the ads they see.

Arity’s solutions for retailers 

Unlike basic location data, mobility data offers retailers deep insights on real-world behaviors based on people’s driving patterns throughout the day. With continual access to current consumer driving behaviors, retailers have continuous insights on how to attract and engage with ideal customers.

You can’t meaningfully connect with your best customers if you don’t know where they are. With predictive mobility data, you can anticipate customers’ movement based on their historical driving patterns. With a better understanding of the consumer’s journey, a retailer can discover crucial moments and behaviors. Retailers can then better understand and predict consumer opportunities before they happen.

Don’t let growth pass you by.