That was the recurring theme at the 2017 Research Conference of the International Council of Shopping Centers (ICSC) in Toronto last week. This annual event brings together the best and brightest research leaders from the top retailers, shopping center owners, and analytic consulting firms in the US, Canada, and other countries.
It’s no secret that online shopping has taken a big bite out of brick-and-mortar (“B&M”) store sales in recent years, and the trend is accelerating at double digit rates. Many traditional B&M operators including Wal-Mart, Target, and Nordstrom have dramatically expanded their online presence, and any retailer that wants to survive is doing the same. However, it’s not as simple as standing up a website and waiting for the customers to come.
According to experts at the conference, B&M retailers are pursuing these strategies to maintain profitability:
- Minimize the size of the selling space; use the “back room” for local distribution to online buyers
- Provide a rich customer experience that may include online kiosks in the store
- Use technology to simplify logistics for the customer, i.e. allow them to browse, purchase, and return merchandise from a smartphone, computer, or in the store
- Use analytics to study customer behavior online and around the stores to maximize the value of advertising and promotion and place stores in the best locations
The use of analytics has been transformed in recent years through the availability of powerful analytic software and data. In addition to traditional statistical models applied to transaction data, retailers are using geospatial analytics to visualize and quantify shopping behavior. Several presentations at this year’s research conference referred to the use of smartphone location data to track the movement of shoppers who respond to online ads and turn on the GPS in their phones.
Wireless carriers identify each phone with a unique ID that does not reveal the name of the subscriber. A smartphone user that transmits location information can be tracked from home to work to shopping trips. These data points include a time-stamp and are sold to third party providers who store them in massive databases for resale to retailers who want to see the shopping patterns around their stores.
Here’s the process:
- The retailer submits a digital polygon to the data provider that represents the boundary of the store or shopping center. This boundary is called a “geofence.” The retailer might also provide a boundary for the shopping center in which the store is located and other competitors or nearby stores.
- The data provider uses the geofence boundaries to identify smartphone users who entered the geofences during a specified period of time.
- The data are summarized by time of day and the paths taken by the smartphone users. In addition to the sequence of stops, the time stamps are used to calculate “dwell time,” which is the amount of time that the phone was inside the geofence.
- The trip patterns also include the presumed “home” and “work” locations for each smartphone user. “Home” is where the phone has a high dwell time during normal sleeping hours and “work” is where the dwell time is high during working hours.
These data can then be visualized in a “heat map” such as the one below:
The heat maps and summarized customer data can be used to find the best store locations, identify potential new customers (based on the neighborhoods where large numbers of smartphones “sleep”), and evaluate traffic to competitors that might suggest new merchandising and promotion strategies.
As retailers chart their course in an Amazon-dominated world, insights from powerful analytic software and data may be the key to survival.
Learn more about how location intelligence can help retailers save money and make money in our webinar on Nov 16th