Avoiding Mistakes When Deploying In-store Analytics

The use of in-store analytics in grocery is growing, along with an appreciation of their importance. Such things as Wi-Fi and beacons provide critical intelligence about who the shoppers are. Video monitoring identifies shopping patterns and gives clues on how to optimize placements of displays and product categories.

But some grocers make several basic mistakes when starting to deploy in-store analytics. When researching this topic recently, experts agreed on five mistakes that grocers must avoid. Some of them are obvious, but these mistakes are still made nonetheless. Here’s the list:

Failing to Obtain Management Support: Management support is critical for the required changes that will benefit the company’s strategic objectives. All levels of management need to understand what analytics can do, how they’re being used, what the business hopes to learn from using analytics, and what actions need to be taken to succeed.

Under-investing: A lack of strategic vision for the role of in-store analytics in all aspects of retail management results in investing to address a specific opportunity, versus recognizing the larger set of opportunities that could benefit from in-store analytics.

Inadequate Training: Grocers need to sharpen operations and train people to execute quickly, to react smarter and more nimbly, to glean insights, and to turn them around in days or weeks, not months. Without the proper due diligence, training and socialization internally among key stakeholders, deploying a new source of analytics and data can fail right from the start. Proper understanding of their utility and ultimately the benefits that they’re intended to create, combined with the proper tools and support in place, can make the difference between success and failure. 

Creating Complexity: Many grocers create complexity at the start, either because their vision of how the analysis might be used isn’t clear or is too narrow. Many create shopper segments without a specific business problem in mind, so the segmentations don’t help resolve the challenge.

Aiming for Perfection: Do the best you can. Deploy, learn and improve. Use what works, discard what doesn’t. Take the next step. Don’t aim for perfection. 

“It is very difficult to convert complex data into simple and actionable insights,” says David Ciancio, senior consultant for customer strategy at dunnhumby, a consultancy. “Unfortunately, much of the industry thinking is around analytics as applicable to CRM and marketing only, and so grocers rarely translate insights into the operations of the business or into ‘store’ understanding.”