Retail location analytics: Using mobile data to improve product placement strategies

By Karin Kelley

| Retail

To optimize sales, brick-and-mortar retailers have traditionally relied on historical sales figures, seasonal shopping patterns, data from point-of-sale systems or plain old intuition to determine the best product placement. Though these strategies have their virtues, new retail location analytics technologies that tap into the near-ubiquity of smartphones are now available, and these tools can help retailers develop product placement strategies in a much more effective, data-driven manner.

Tactics for collecting in-store customer data

Retail location analytics tracks the behavior of customers while they are in a store by collecting location information from shoppers’ smartphones, in-store wifi networks and Bluetooth beacons, according to Harvard Business Review. The amount of data that can be collected from these low-cost tools is staggering — the source reports that a single customer visit can create more than 10,000 unique data points, and that’s not even including point-of-sale data.

Though wifi is arguably the most popular way to track customer behavior in a brick-and-mortar store, retailers may want to deploy a combination of the following data collection techniques to optimize their data sets:

  • Wifi
    This entails tracking a customer’s physical journey through the store using the unique IDs on their smart devices.
  • Bluetooth beacons
    When users enable the Bluetooth on their phone and consent to be connected to the store’s system, retailers can collect location data and send push notifications with suggested products or coupons.
  • Video
    New 3-D video analytics enables retailers to capture and analyze images and videos to determine in-store traffic patterns.
  • Thermal
    Retailers can use thermal tools to sense infrared heat and determine how many customers are walking through the door, at what time they do so and where they travel within the store.

Making effective use of data

Once the data is collected, retail location analytics can parse through all the information to discern patterns and trends. There are three main stages of shoppers’ visits that retailers should focus on when looking for data insights:

  1. Entry
    At entry, retailers should look at the overall number of visitors, when they actually come to the store and where they go first.
  2. Browsing
    While shoppers are browsing, key metrics to look for include the conversion rate (which customers actually buy a product), the average size of purchases and how long people review products before they actually purchase them. It’s also worth noting how customers actually navigate the store floor during their visit.
  3. Exit
    Finally, upon a shopper’s exit, retailers should determine the bounce rate (how many customers leave the store without making a purchase), how long the customers stayed in the store and whether long checkout lines affected their decision to leave.

Ways organizations can increase sales with retail location analytics

Retailers that deploy these analytics can gain insight and improve product placement in several ways. All of the following strategies should be conducted regularly and in conjunction with one another:

  • Identify the cause of poorly performing locations
    First, retailers can compare data from their best- and worst-performing locations to determine whether it’s the location or the product that is causing poor performance. This information also gives insight into which types of promotions can be offered to improve sales.
  • Provide relevant in-store advertising
    By determining where customers travel and dwell in the store, as well as which purchases they’re making, retailers can place relevant advertisements for related purchases and promotions.
  • Segment the store in distinct zones
    By enabling more granular analysis of which sections of the store customers visit more often and where more purchases are made, retailers can redesign their layouts to boost sales in previously underselling areas.
  • Test, test, test
    By rearranging products and analyzing how changes affect sales, retailers can choose the best spots to place items now and in the future.

The goal of in-store retail location analytics technologies is twofold: improve the customer experience and increase sales. The key to success is understanding your customers and providing the best and most intuitive shopping experience, just as online retailers do with e-commerce.

Written By

Karin Kelley

Independent Analyst & Writer

Karin is an independent industry analyst and writer, with over 10 years experience in information technology. She focuses on cloud infrastructure, hosted applications and services, end user computing and related systems management software and services. She spent nearly eight years…

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