How can location-based analytics help retailers in targeting customers

Instruction Details

Quiznos Targets Customers for Its Sandwiches

Quiznos, a franchised, quick-service restaurant, implemented a location-based mobile targeting campaign that targeted tech-savvy and busy consumers of Portland, Oregon. It made use of Sense Networks’ platform, which analyzed the location trails of mobile users over detailed time periods and built anonymous profiles based on the behavioral at- tributes of their shopping habits.
With the application of predictive analytics on the user profiles, Quiznos employed location-based behavioral targeting to narrow the characteristics of users who were most likely to eat at a quick-service restaurant. Its advertising campaign ran for 2 months—November and December 2012—and targeted only potential customers who had been to quick-service restaurants over the past 30 days, within a 3-mile radius of Quiznos, and between the ages of 18 and 34. It used relevant mobile advertisements of local coupons based on the customer’s location. The campaign resulted in over 3.7 million new customers and a 20% increase in coupon redemptions within the Portland area.
1. How can location-based analytics help retailers in targeting customers?
2. Research similar applications of location-based analytics in the retail domain. Provide at least 3 examples and explain how they are used. What information from these apps do you think is important to the businesses that have them?

Answer Guide

1. How Location-Based Analytics Help Retailers in Targeting Customers

Location-based analytics offer retailers valuable insights and tools for effective customer targeting by:

  • Geo-Fencing: Retailers can create virtual boundaries (geo-fences) around their stores or specific areas of interest. When customers enter these zones, retailers can send targeted promotions or notifications via mobile apps.
  • Understanding Foot Traffic: Analytics can track the flow of customers within physical stores, identifying popular areas and product placements. Retailers can optimize store layouts and product displays based on this data.
  • Customer Profiling: Location data combined with user behavior provides insights into customer demographics, preferences, and habits. Retailers can create personalized offers and recommendations.
  • Competitor Analysis: Retailers can monitor foot traffic at competitors’ locations to identify market trends and potential customer overlap.
  • Real-Time Targeting: Retailers can send real-time offers when customers are in close proximity to a store, increasing the likelihood of a visit.

2. Examples of Location-Based Analytics Applications in Retail: a. Retail Mobile Apps

Many retailers have their mobile apps that use location data to enhance the shopping experience. For example, Walmart’s app provides in-store maps, item location, and real-time promotions based on the shopper’s location within the store. Businesses gain insights into shopping patterns and product preferences. b. Beacon Technology: Retailers like Macy’s and Target use Bluetooth beacons to send location-specific discounts and alerts to customers’ smartphones when they are near or inside the store. Beacon data helps retailers track customer movement and optimize store layouts. c. Google Maps Advertising: Retailers can advertise on Google Maps, targeting users based on their location and search history. For instance, a coffee shop can display ads to users searching for “coffee” when they are nearby. This allows businesses to reach potential customers at the right moment.

Information Important to Businesses:

  • Customer Foot Traffic: Data on the number of customers visiting physical stores and their paths within the store help businesses assess store performance and optimize layouts.
  • Customer Demographics: Knowing the age, gender, and interests of in-store customers aids in creating personalized marketing campaigns.
  • Real-Time Location: Businesses benefit from real-time location data to trigger timely promotions and increase foot traffic.
  • Competitor Insights: Monitoring competitor foot traffic can inform pricing strategies and marketing tactics.
  • Customer Engagement: Tracking customer engagement with mobile apps, including which products they view or add to carts, helps in tailoring recommendations and offers.

Overall, location-based analytics empower retailers to make data-driven decisions, enhance customer experiences, and improve the effectiveness of marketing efforts.

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