The mobility data advantage: Unlocking retail insights from driving patterns 

Retail marketers, imagine attempting to understand your customers based on outdated footage from a low-budget security camera. The image is blurry, the video is delayed, and the footage only shows who walked in your door hours ago. That’s what it’s like using traditional location data alone to target retail audiences. 

You may be able to discern whether someone was near your store. But consider these examples: 

• What about the commuter who drives past your coffee shop every morning at 7:42 a.m.?  

• What about the weekend road-tripper who always stops for fuel, just one exit before your store?  

If you’re only relying on standard location data, you might never detect them. 

That’s where mobility data comes in. These richer, high-frequency signals can capture how, when, and where people drive. Mobility data captures the full journey — not just whether they ended up at your location. With this data, retailers can uncover hidden patterns, build smarter segments, and launch more timely and personalized campaigns. 

Whether you’re a QSR, a fuel station, or a grocery chain, the road to more effective marketing starts with understanding your audience’s real-world movement. 

Let’s explore how this information can benefit different verticals. 

Quick serve restaurants (QSR) 

Mobility pattern: Routine commutes 

A remarkable 76% of U.S. workers surveyed drive alone to work, according to the U.S. Census Bureau’s American Community Survey. This statistic highlights how ingrained commuting routines are in individuals’ daily lives. And if people are driving alone, then driving data can reveal their specific day-to-day habits. 

Strategic applications of mobility data

• Segment: Identify morning commuters who pass by your QSR locations on consistent routes. These habitual drivers are prime candidates for breakfast promotions. 

• Target: Serve mobile ads just before early drive-time windows to promote specials like a coffee and egg sandwich combo. 

• Measure: Use mobility data to attribute store visits to ad impressions — particularly with short visits like drive-thru pickups — to capture real-time ad ROI. 

Hypothetical example

A national QSR chain uses commute patterns to target morning drivers with timely, relevant mobile offers. They observe a notable increase in breakfast purchases and attribute this activity to the digital ads pushed that morning on mobile. The marketing team confirms that drivers who saw these digital ads were significantly more likely to visit within 30 minutes. 

Fuel and convenience retail 

Mobility pattern: Weekend vs. weekday behavior 

Travel behavior differs dramatically between weekdays and weekends.  A 2022 survey by the Federal Highway Administration shows that weekend trips are significantly less work-driven than weekday commutes. 

Strategic applications of mobility data

• Segment: Differentiate between weekday commuters and leisure-focused weekend travelers; the latter, on average, drive longer distances and may stop at highway-adjacent locations. 

• Target: Deliver timely promotions like “Free coffee with fill-up” to weekend travelers approaching your location, based on real-time route prediction. 

• Measure: Evaluate uplift in transaction sizes and visit frequency by comparing cohorts exposed to ads versus control groups. 

Hypothetical example

A fuel and convenience brand uses mobility pattern triggers to target drivers on long weekend trips. By delivering promotions 10 – 15 minutes before potential stops, they achieve an uplift in average spend per visit and confirmed conversions through mobility-based attribution. 

Supermarkets 

Mobility insight: Strong store loyalty 

Industry data indicates that 70 – 80% of grocery shoppers choose the same store or chain,  highlighting the significance of habit in choosing where to buy everyday foods and goods. 

Strategic applications of mobility data

• Segment: 

• • Routine loyal shoppers: Frequent visitors with predictable patterns. 

• • Infrequent or multi-stop shoppers: Those whose supermarket visits are part of broader errand runs or less frequent trips. 

• Target: 

• • Offer weekly circulars and loyalty bonus deals to users who consistently visit. 

• • Encourage visits from infrequent shoppers with timely promotions like “Double points today only” tied to predicted shopping windows. 

• Measure: Track changes in visit frequency, basket size, and dwell time after campaign exposure to prove incremental visits and enhanced engagement. 

Hypothetical example

A regional supermarket chain identifies infrequent shoppers with targeted digital ads offering delivery discounts. They observe a significant lift in store traffic and an increase in average basket size, validated by mobility-based attribution models.

Measurement and attribution: Closing the loop 

The true power of mobility data lies in going beyond footfall. With mobility data, you can link digital ad exposure to physical store behavior and prove ROI. Key advantages include: 

• Incrementality detection: Distinguish between habitual visits and visits spurred by advertising. 

• Trip-level insights: Validate dwell time, return rates, or post-exposure return visits. 

• Real-time optimization: Adjust targeting and creative based on what’s actually driving incremental outcomes. 

Mobility data provides the rich, temporally detailed signals necessary for confident attribution and effective campaign optimization — especially when validated with control groups and behavior-rich segments. 

Final takeaway 

Mobility data can transform the way retail marketers approach targeting. By unlocking insights into how people drive — commutes, leisure trips, and errand patterns — brands can tailor messages to real-world behavior, ensuring relevance and timeliness. 

Consumers may be fueling up, grabbing a fast bite, or stocking their fridge – but if retail marketers don’t understand the real-world context behind this consumption, they’re missing an opportunity. Understanding driving patterns is the key to engaging consumers more precisely — and proving that your campaigns drove results.  

Let mobility data be your North Star in retail marketing. 

Sources 

• U.S. Census Bureau, American Community Survey: ~76% of workers drive alone to work. 

• Industry mobility studies: Weekend travel behavior differs significantly from weekdays (e.g., longer, leisure-based trips). 

• FMI, U.S. Grocery Shopper Trends Report: ~70–80% of shoppers frequent the same store or chain.