Key takeaways
- Traditional behavioral data misses a critical layer: where and when customers are driving in the real world.
- Mobility data reveals true customer movement patterns, enabling more accurate targeting, timing, and measurement.
- CPG, QSR, c‑store brands and more can use mobility insights to capture pass‑by traffic, a major untapped growth opportunity.
- Real‑world driving patterns enable hyperlocal, context‑aware marketing — reaching consumers at the right place and time.
- Brands leveraging mobility data report measurable lifts in visits and sales, powered by closed‑loop attribution.
- As competition intensifies, mobility data delivers a sustainable edge, connecting marketing actions to actual store outcomes.
Traditional vs. emerging sources of behavioral data for retailers
To understand and engage your customers, you’re most likely relying on purchase, digital, loyalty, and in-store behavioral data. While these sources are still valuable, their effectiveness can be limited. So, how do you solve for this? The answer lies in mobility data.
Emerging sources like driving behavior data (mobility data) offer a powerful new lens — enabling marketers to:
- Reach and measure audience cohorts based on real-world driving
- Unlock new targeting opportunities
- Drive measurable business outcomes
That’s where Arity comes in.
About Arity, a mobility data and analytics company
Arity believes that brands can go beyond traditional demographic and behavioral targeting. By leveraging real-world driving behavior data, brands can reach specific audiences when and where they’re most likely to buy — and prove campaign impact with closed-loop attribution.
Different behavioral data types for the retail industry
Each data type has strengths and limitations:
- Purchase and transaction data: Helps you understand actual buying behavior and segment high-value customers but it doesn’t capture intent or pre-purchase consideration
- Website and app analytics: Offers insights into intent and interest but may not always translate to purchases, especially if customers shop across channels
- Loyalty and CRM data: Enables long-term customer relationships and predicting future value but only covers enrolled members
- Email and digital engagement data: Streamlines communications but can be limited by changing consumer preferences (e.g., email fatigue)
- In-store behavior data: Measures offline engagement but requires investment in hardware and fails to capture driving cohorts who passed by and didn’t enter the store
Of course, the most effective retail marketers integrate multiple sources to build a holistic, omnichannel view of the customer. However, none of the above types of behavioral data can capture where and when cohorts of customers may be driving. When brands have that information, they can reach customer segments at the right place and the right time, in the real world — when they’re most likely to make a purchase.
Emerging sources of behavioral data: Driving behavior and mobility data
- What it is: Anonymized, aggregated data on how, when, and where consumers drive, sourced from drivers who have opted in to share their data through their smartphone apps, connected vehicles, or telematics platforms.
- How it’s used: Segmenting audiences based on real-world movement patterns (e.g., frequent shoppers, commuters, or visitors to specific retail locations)
- Timing offers when consumers are near a store or likely to be in-market
- Measuring the impact of digital campaigns on actual store visits (closed-loop attribution)
- Effectiveness: Driving behavior data provides a unique, real-world layer of insight that goes beyond digital intent or past purchases. It enables marketers to reach consumers based on actual mobility patterns, optimize media spend, and prove ROI with store visit attribution. Early adopters in such as a fuel retailer and the spirits brand Suerte Tequila have reported lifts in foot traffic and sales when using mobility data for targeting and measurement.
Why mobility data is highly relevant to retail, QSR, and fuel/c-store brands
1. Mobility data reveals real-world customer journeys
Traditional retail and QSR marketing has long relied on static location data or foot traffic counts. However, mobility data offers a dynamic, real-world view of how, when, and why consumers move through their day. This enables brands to, predict and influence customer routines and when they are likely to pass by store locations.
2. Pass-by traffic is an underleveraged opportunity
For QSRs and c-stores, the majority of potential customers are literally passing by every day. According to QSR Magazine, drive-thru and off-premises dining now account for nearly 75% of all restaurant traffic, and drive-thru lanes alone can represent 60–70% of a QSR’s business. Yet, most brands only convert a small fraction of this pass-by traffic into actual visits.
Retailers and QSRs can use mobility data to:
- Target drivers who frequently pass their locations with timely, relevant offers
- Understand which intersections or areas receive the highest pass-by volume
- Optimize store formats, staffing, and promotions based on real-world flow, not just historical sales
3. Attracting customers at the right place and right time drives measurable results
Mobility data enables hyperlocal, context-aware marketing, reaching consumers when they’re most likely to convert. For example:
- Predictive mobility data can trigger a coffee coupon just before a commuter’s routine stop, or a bundled QSR/retail offer when a family is running weekend errands.
- Mobility data solutions can help QSR brands take advantage of the holiday bump in retail traffic and encourage shoppers to visit nearby dining locations
4. Mobility data powers operational and marketing efficiency
- For QSRs: Mobility data can help optimize drive-thru throughput, staffing, and service speed, closing the gap between marketing and operations.
- For c-stores: Mobility data can identify driver cohorts most likely to make a return visit or spend more at the pump, enabling targeted loyalty offers and maximizing checkout spend.
5. Competitive advantage and closed-loop measurement
- Brands can use mobility data to “conquest” drivers who frequent competitor locations, intercepting them with timely offers and measuring incremental visits driven by campaigns.
- Closed-loop attribution — linking ad exposure to actual store visits — gives marketers confidence in their spend and enables rapid optimization.
Conclusion
Mobility data is transforming how retail, QSR, and fuel/c-store brands understand and engage customers. By moving beyond static location data to embrace real-world driving patterns and pass-by traffic, brands can reach consumers at the right place and right time, drive measurable increases in visits and sales, and optimize both marketing and operations for maximum ROI. As competition intensifies and consumer routines evolve, mobility data is becoming increasingly relevant for brands that want to win the battle for attention — and conversion — on the road.
