While formal industry penetration data on retail traffic counters are hard to come by, a quick stroll through any mall will reveal that more major retailers track traffic today than those who do not. Part of the reason that retail traffic counting is becoming so ubiquitous is because the insights have so much practical value across so many functional areas. From store operations and merchandising to HR and marketing, basic store traffic and conversion data can help inform a multitude of important decisions. If your chain doesn’t have retail traffic counters installed at the front door today, there’s a good chance it will, probably sooner rather than later. But before we get to some specific retail industry uses for traffic data, let’s start with the biggest “why”—why even bother?
What Will Retail Traffic Counters Tell Us That We Don’t Already Know?
If this question has crossed your mind, you’re in good company. Many senior executives have asked me this question. It’s especially relevant when you consider the significant investments retailers are making in sophisticated customer relationship management (CRM) and point-of-sale (POS) systems that seem capable of capturing every imaginable morsel of customer data.
So, what can a simple traffic counter tell you that you don’t already know? A lot.
Traffic and conversion analytics focus on what happens before the transaction is recorded in your POS or CRM system…if one is ever recorded at all. That’s what makes traffic and conversion data especially useful. Together, they tell us about the sale we almost had—a perspective on what might have been.
No transaction-based system, even the most sophisticated, can tell you about the sale you almost had. It all starts with traffic. If prospects don’t visit your store, you have no chance at making a sale. So, understanding prospect visitation is vital to understanding the sales opportunity. But getting prospects to visit your store is merely step one. Step two is “converting” the traffic into a sale.
So, the big “why” of traffic counting is that it enables retailers to understand the potential sales opportunity (traffic) and helps measure how well stores are doing at capturing the opportunity (conversion rate). Without knowing something about the sales opportunity, how can you fully understand how your chain is performing? I say you can’t. Here’s a simple example to illustrate.
Let’s say your same-store or “comp-sales” are up 5 percent compared to last year. In isolation, this may appear to be a good result. Without traffic data for context, we have no way to understand how good a 5 percent sales increase is. Now consider the 5 percent increase in same-store sales, but this time you have traffic data for context. What if you knew that overall traffic in the store was up 15 percent compared to last year? The opportunity (traffic) got 15 percent larger, but sales were only up 5 percent—an improvement that seemed good until we understood the opportunity. I would argue that the store under-performed versus the traffic opportunity.
Now consider the same 5 percent sales improvement, but this time we discover that store traffic was actually down 15 percent. If the traffic opportunity shrunk by a whopping 15 percent, but same-store sales were still up 5 percent, this suggests that the store over-performed compared to the shrinking opportunity. Without traffic data, it’s impossible to tell if the 5 percent sales improvement is good, bad, or great. (Related: “Do Retailers Need to Increase Foot Traffic?“)
Context can dramatically change how we view results and help guide what actions we take, and that’s what makes it so important. Conversion rate (sometimes called “close rate”) is a measure of the percentage of buyers to visitors. Think of it as the store’s batting average. Conversion rate is calculated by simply dividing the number of sales transactions by the traffic counts. If you don’t know your traffic count, it’s impossible to calculate your conversion rate.
This article was excerpted from “Using Loss Prevention Technology to Support Traffic Counting and Conversion” and updated July 20, 2017.