By Cameron V. Peebles, Global Chief Marketing Officer, Locala
Location-based businesses – including retailers and restaurants – have undergone more change in the last two years than in the previous 10. Now, as pandemic restrictions lift, these location-based businesses are looking at a hybrid future that will require them to embrace digital strategies that support their brick-and-mortar stores.
But brands should no longer settle for typical location marketing vendors who stitch together progressively smaller radiuses to form a general store proximity area. As technologies for driving physical and digital traffic progress, brick-and-mortar businesses should expect more advanced techniques.
Here are four essential components that location-based businesses should seek out in building a modern drive-to-store campaign:
1. Dynamic location targeting should go beyond traditional geo-radius assumptions
Real-world campaign data reveals that traditional geo-radius proximity areas – even those that offer hexagonal targeting – capture only a fraction of brands’ high-affinity customers. The problem with these geo-radius models is they are too static and don’t account for dynamic “catchment” areas, or where people go on their way to and from a store.
For example, it shouldn’t come as a surprise to a QSR [quick-service restaurant] brand that its high-affinity consumers may live to the far west and far east of its store locations. People who live in these distant areas commute near the store locations regularly. Conversely, people who live to the more immediate east and north of a location may rarely, if ever, patronize it.
Technology can account for fluctuations in high-value customer clustering. By dynamically adjusting the matching of affinity and location, a brand can more effectively drive a high volume of incremental customers.
2. Pinpointing the consumer stage in the shopping journey is critical
Typically, offer awareness happens at home via a range of omnichannel engagements, including connected TV, desktop and iPad. A successful drive-to-store campaign needs to track and engage the consumer from this initial impression all the way to the door.
Leading drive-to-store platforms take an omnichannel approach, using machine-learning technologies to pinpoint the stage of a given consumer journey and customize their messaging engagements to keep them moving toward the store.
For example, once the consumer has left home, a platform can deliver intent-driving messaging to their mobile device, using ad units whose creatives are dynamically optimized for multistore campaigns. These intent-driving offers take into account all of the store locations that are close to the user at any given time, delivering additional value and additional intent to purchase. Finally, geotargeting around the location is activated to drive customers through the doors.
3. Time is of the essence for a “drive-to-store” campaign
To account for dynamic demand and consumer traffic patterns, every successful drive-to-store program must optimize based on time of day and day of the week. Any tier-one drive-to-store platform will be capable of identifying the highest-value prospects based on historic and time-stamped foot traffic data from your locations and your competitors – and this time-stamped data can reveal timely opportunities.
For example, if you’re McDonald’s and you know Chick-fil-A is famously closed on Sundays, then a drive-to-store campaign targeting consumers that have traveled near the location on the same day represents a golden opportunity.
4. Lean into competitive conquesting
Machine-learning technologies can take traditional competitive conquesting to the next level. The technology can analyze frequent customers of competitive locations in an always-on manner, optimizing delivery of targeted creatives toward consumers most likely to switch allegiances to your brand.
This next-level conquesting requires a deep understanding of the competitive battlefield: the overlap between locations, where consumers live and where they regularly travel during their day-to-day lives. Modern drive-to-store platforms use machine-learning optimization to execute this advanced campaign structure and gain advantage in the modern competitive landscape.
The pandemic accelerated the arrival of the hybrid future for location-based businesses and amplified competitive pressures in the process. But technology can make door-to-store campaigns more effective than ever, too.
Savvy businesses can drive foot traffic to their physical and ecommerce locations if they can optimize based on these four dimensions of a door-to-store campaign: location, stage, time and battleground. These are the hallmarks of a best-in-class drive-to-store methodology, and the combined strategy is light years beyond what traditional location services can provide.