Predictive mobility data can help you solve these 3 new retail convenience store challenges

Predictive analytics, meet predictive mobility – retailers’ key to overcoming emerging obstacles. 

The retail business often faces headwinds. For convenience stores – or C-stores – in particular, certain new technology, lifestyle, and market shifts threaten to decrease traffic to these fuel-adjacent stores. So, what are the new challenges for C-stores, and how can predictive data solve them? 

1. The rise of electric vehicles 

Challenge

“The rise of electric vehicles… [is one of] the biggest challenges in the mobility industry,” says Chase Davis, solutions engineering manager at Arity. Sales of electric vehicles have increased nearly every quarter since 2021. Sales of hybrid electric vehicles have also surged.  

With nearly 80% of C-stores selling fuel, the increase in electric and hybrid cars means fewer consumers are going to the pump – or entering the store, where in-store purchases make up 70% of stores’ overall profits. 

While electric and hybrid vehicles are a laudable investment for those who want to reduce their carbon footprints, this shift away from gas-powered cars could mean a decline in C-store traffic – and sales. 

Solution

Imagine your customers coming into the store not because their gas tank arrow is pointing toward “empty” but because they received a deal on their morning coffee. That’s the power of predictive mobility. 

Predictive mobility insights can help C-store apps better understand their customers’ movement patterns. When stores know where their customers are going, they can better cater to consumers’ needs – beyond when the consumers need to fill up on gas.  

2. New work and lifestyle patterns 

Challenge 

C-stores have long sought locations that were easily accessible, especially in cities. “However, as people work remotely, they don’t commute as often and can spread out farther from big cities,” Davis said. “They have different [routes and] drive times, so you need new ways to analyze and understand where those locations should be optimized.”  

These industry shifts underscore a challenging reality: traditional methods of reaching and acquiring customers are no longer sufficient. Retailers must find new ways to attract customers beyond pass-by traffic. 

Solution

In this new era of return-to-office initiatives and hybrid work arrangements, “rush hour” could be any hour. Predictive mobility functionality can help C-stores gain line of sight into these new commute patterns. Using anonymized, aggregated data, these insights can help retailers pinpoint the best times to reach drivers – many of whom have had their work hours and routes upended.  

3. Economic volatility

 Challenge 

With shifts in the economy and the pricing of consumer goods, Americans are looking for everyday ways to save. “Consumer confidence declined for a fifth consecutive month in April [2025], falling to levels not seen since the onset of the COVID pandemic,” said an expert at The Conference Board. The New York Times pointed to a specific metric: An article from May 2025 stated that Americans are starting to cut back on, of all things, snacks. Consumers’ hunger for incremental savings could include searching for the cheapest gas prices, versus going to fill up at their usual location. 

Solution

With pocketbook issues top of mind for consumers, C-stores need to prioritize offering the right deals at the right time. And although rewards programs are good, rewards programs plus predictive data are even better. When you understand how consumers move in the world, you can target them with the deals they need – before the consumers know they need them.  

Don’t think of deals as a race to the bottom. It’s a race to the top – using specialized mobility analytics functionality to serve the best offers, and serve them at scale. 

Although retailers have long used online data to boost ecommerce, predicting offline, real-world behavior is a relatively new phenomenon. This technology has the potential not only to help you better understand your customers but also personalize offers for them at scale. This functionality comes at a particularly critical time for fuel retailers, when their customers may be investing in fuel-efficient vehicles, shifting their driving patterns, and guarding their wallets. 

With Arity as your mobility partner, fuel retailers can feel confident. As the experts in mobility data and analytics, we can work with you and show you how predictive mobility can better enable your sales during this precarious time for retail.