October 26 2015

Understanding Location-Based Analytics

The amount of market research available today is astounding, and ever-growing. 

In order to make the most out of time and get the most conversions, truly understanding a customer is paramount, and location-based analytics allows you to take that a step further.

But what is location-based analytics?

This is the process of measuring the interaction customers have within your store. Not to be confused with mystery shopping, location-based analytics pulls information from random customers, usually anonymously, to help generate more accurate information about the shopper’s experience. Location-based analytics provide data about an in-store shoppers’ behavior from the time they enter the store, until the time they leave.

This information can be used to identify several key pieces of information, such as:

  • Frequent paths customers take within the store
  • A comparison between time spent in the store to conversion
  • How long a customer is willing to wait in a zone before leaving without service
  • Let’s take a look at a hypothetical situation:

A customer, Judy, pulls up to a grocery store. Her phone is set to connect automatically to unsecured WiFi networks, at which point your location-based analytics system kicks in.

Judy enters the store, and heads down isle five, past a wall of bread. She continues to the end, where she grabs some milk before heading to the baking isle.

In the baking isle, Judy looks for a very specific ingredient she needs, but is having trouble finding it. Your associates are instructed to make contact with a customer within a certain number of seconds when they’re close to them, but no associates are around. Judy continues looking, but after about five minutes gets fed up, and heads to buy her one product and leave.

Behind the Scenes of the Customer Experience

Location based analytics give us better understanding of the customer experience and the opportunity for improvements. Using our previous example, the grocery store would be able to see how long the Judy’s of the world are willing to wait for assistance, ensuring that Judy gets the service she wanted, makes that additional purchase, and perhaps even keeps shopping for other things that may be on her list. This is just one example. Location-based data can be remarkable and allow you to ensure that you’re providing the best service you can for the customer, in turn allowing yourself to make the most conversions possible.


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