Part 2: The Great 28 – Twenty-eight windows into retail performance

In this two-part series, StrataVision’s VP of Analytics Brian Field explores why traditional retail metrics often fail to explain store performance and introduces The Great 28, a practical framework for connecting shopper behavior, operational capacity, and business outcomes.

Successful retailers assess store performance differently. In Part One, I argued that retail metrics become far more valuable when viewed as behavioral signals rather than isolated data points. The next question is obvious: Which observations matter most? 

The Great 28 answers that question. 

It isn’t a scorecard that needs to be monitored daily or another collection of disconnected KPIs. Instead, it is a collection of twenty-eight observations that already exist within most retail operations. Collectively, they provide a more complete understanding of what happened inside the store. More importantly, they offer a practical framework that helps retail leaders see what shoppers experienced, how stores responded, and why performance turned out the way it did. Together, they transform data into visibility, and visibility into better decisions. 

Its focus is store operations and customer experience. Retail organizations will, of course, continue to rely on many other metrics for merchandising, finance, loss prevention, marketing, and other functions. The goal wasn’t to identify every retail metric worth tracking. It was to identify the observations that, when viewed together, provide a practical understanding of store performance. 

The observations naturally fall into four themes, each answering a different question about what happened inside the store. 

Opportunity: What demand existed?

Opportunity begins before a single purchase is made. It measures the demand that existed independent of whether the store converted it into sales. Without understanding shopper demand, it’s impossible to know whether disappointing results were caused by a lack of customers or a failure to serve the ones who arrived. 

Observations such as Perimeter Traffic In Counts, Departmental Traffic, Shopper Paths, Feature Engagement, Fitting Room Usage, and store Dwell Time together help reveal where shoppers went, what attracted their attention, and how they spent their time. 

Opportunity isn’t a measure of how well a store performed. It’s a measure of the customer demand that existed before the store had any chance to influence the outcome. 

Collectively, these observations answer a simple question: Did shoppers have the opportunity to become customers? 

Capacity: Was the store prepared to serve?

Service doesn’t have to mean one-on-one selling. It involves every task and every role necessary to ensure that the store is ready to take care of shoppers throughout the day. This requires having the right number of associates in the right places at the right times. Capacity isn’t measured by the number of labor hours scheduled. It’s measured by whether the store has the ability to execute its plan.  

Scheduled Hours describe the plan. Worked Hours reveal what actually happened. The difference between the two, Schedule Compliance, reveals where labor capacity was lost before customer service was ever affected. Paired with shopper Traffic, Customer-Facing Labor creates the Shopper-to-Associate Ratio (STAR), revealing whether the store has created enough service capacity to respond to customer demand. Delineating the Customer-Facing Labor results in a better understanding of the Non-Customer Facing Labor hours that are more closely tied to tasks and other duties that are easier to set labor standards for than working with shoppers. 

Experience: What actually happened inside the store?

We’ve observed how the shoppers are shopping and we’ve set up the store team to appropriately engage them. Now, we see how it all comes together. Whether your store has dedicated sales associates or relies on operational teams focused on stocking and recovery, the shopper still experiences some level of contact with them. It could be consultative or it could be looking for merchandise or checking out.  

Several connected observations reveal whether shoppers actually received the experience the store intended to provide. Shopper/Associate Engagement helps identify the times where shoppers and associates are in the same place at the same time. This is uniquely different from STAR or comparing a schedule to Traffic. The schedule review is like a first draft of what will happen on the sales floor. STAR reflects the level of service to be provided. But engagement identifies real shopper behavior and real associate interaction. Linked to engagement is Department Level Dwell Time. Together, these observations reveal how often shoppers were engaged and how long they spent in any given area. Fitting Room Dwell Time provides a similar understanding that can help identify room capacity gaps and how engaged shoppers are with trying on merchandise. 

A critically overlooked experience is what happens at the checkout counter. This is typically the last stop in a shopper’s visit and the experience there can make their transaction go smoothly, even add to the bag or become so frustrating that the shopper leaves without purchasing. The Length of the Queue and the Time In Queue address observing what the end of the visit experience is like. 

To this point, we haven’t even mentioned any sales-related metrics. Sales don’t occur in isolation. They are the result of opportunity, capacity, and experience working together. Until those are understood, sales metrics tell only the ending, not the story that produced it. 

Outcome: Together, what did opportunity, capacity and experience produce?

Finally, we get to the place where retail reviews typically start, and dashboards give way to misinterpretations of what really happened in the store. These are among the most important metrics in retail. The problem isn’t the metrics; it’s the lack of context surrounding them. That context comes from the three areas that preceded this section. Let’s take this in the form of the standard retail equation: 

Units Sold / Transaction Count = Units per Transaction 

Sales / Units Sold = Average Unit Retail 

Units per Transaction x Average Unit Retail = Average Transaction Size. 

Average Transaction Size x Transaction Count = Sales 

Or: 

Average Transaction Size x Conversion = Sales per Shopper 

Sales per Shopper x Traffic Out Counts = Sales 

What’s important here is that there are several levers to work with that result in sales. And you could drill many of these down to the department level, like Department Sales and Department Conversion for even more clarity. 

But what if you attached Dwell Time, from the experience window to Units per Transaction? Could longer department dwell time be associated with higher Units per Transaction? Does more frequent engagement influence Average Transaction Size? Are stores with stronger STAR patterns converting more shoppers? These are just a few examples of taking the outcome and working with what came before it to reveal how the store really operates.  

28 Windows: Turning results into understanding

Viewed alone, outcome metrics tell you what happened. Viewed alongside Opportunity, Capacity, and Experience, they begin to explain why it happened. That’s the difference between reporting results and revealing what produced them. 

The Great 28 isn’t intended to replace management judgment. It’s intended to improve it. By making demand, capacity, experience, and outcomes more visible, retail leaders can coach more effectively, allocate labor with greater confidence, and make decisions based on what actually happened in their stores rather than relying on intuition alone. 

Operational visibility doesn’t happen by accident. It requires traffic, labor, and POS data to work together in ways that reveal how stores actually perform. That’s why StrataVision’s AI-powered traffic solutions and reporting platform are designed to work together, helping retailers transform data into the visibility needed for better operational decisions.