From Reactive to Proactive: How AI Is Transforming Retail Analytics

For as long as retailers have been collecting data, analytics has been a reactive discipline. Something happens — sales dip, a promotion underperforms, a store loses its momentum, a category misfires — and the analytics team is asked to explain why. They explain it, and invariably this raises more questions. 

We’ve grown accustomed to this cycle. But with the accelerating maturity of AI, that’s beginning to change. 

At 11Ants, we’ve spent more than a decade helping grocers unlock insights from transaction and customer data. Our SaaS platform enables both analysts and business users to instruct a virtual analyst to explore patterns in trading performance, promotions, customer behavior, stores and products — all without needing to write a line of code.

The arrival of generative AI creates massive opportunities when coupled with this foundational capability.

AI enables us to see and explain what we weren’t looking for. 

Traditionally, analytics depends on knowing what question to ask. But retailers are operating in a world that’s too fast, too complex and too nuanced for that alone. Decisions need to be made in real time — often before a human would know to investigate. This is where AI offers a step change. 

At 11Ants, we’ve recently infused AI into our platform to create something genuinely new: a proactive, AI-enabled virtual analyst that scans transaction and shopper data for patterns, anomalies and opportunities; surfaces those insights — and now explains its findings in plain English. 

This is how one of our largest customers (500-plus stores) described the new capability in a recent interview: 

“11 Ants now summarizes all our data. It shows us where to look AND tells us what’s important, which is incredibly powerful. With a detailed explanation of the data, we can focus on what matters far more quickly and identifies behaviors and trends we wouldn’t necessarily spot on our own. It’s transforming how we see the business.”