Small data, big difference: How understanding shopper behavior leads to more revenues
Businesses have been trying to understand their customers for a long time. The process is not new, but it has required long-term, in-person observation. This not only requires intensive human resources, it also requires a lot of guesswork to process those small details into actionable insights.
Insight-based change is the seed of competitiveness. In highly competitive markets, like retail and quick service restaurants, you will find savvy leaders wielding nickel-and-dime optimizations to great effect. For example, one Director of Operations of a quick service restaurant noticed a problem with the drive thru one day. Having multi-brand experience, he knew that what he saw was not normal. He had recently implemented a new drive thru, and as he watched, a car turned into the lane, but then hesitated and backed out a moment later. This had rarely happened, so he took note of it.
Over the next few days, he saw this behavior repeat — not every time, but often enough to know something was wrong. He spent dozens of hours over the following weeks observing the drive thru to try to answer that question.
The drive thru layout looked great on paper, but in reality when people entered it looked like the line was longer than it really was. People were hanging back because the curb was really sharp. People would block the order point, and everyone behind them would think they were waiting for a full line of traffic ahead of them. It didn’t always happen, and not everyone would turn back, but eventually the Director figured out that changes needed to be made. Five more $10 sales per day is another $1,500 per location per month, not a small amount of revenue.
Retailers can find themselves in similar situations. Major brands will have different layouts, and they deploy these nationwide. But nothing is perfect, especially in a moving system. The kind of layouts that look great on paper do not always perform seamlessly in execution.
As costs increase, retailers will need to do more than ask difficult questions; they’ll need to find answers to those questions in weeks, not years. “Do we need 20 feet of dead space between the register and the aisle?” and “Do we need three registers? Can we change the aisle configuration slightly?” These questions are answered best by customer behavior, by looking at patterns, making changes, and seeing the impact on patterns.
This is the sort of problem that in-store analytics can help with. Accurate, automated dataflows from the store floor to the cloud can speed the process of optimization and overcome the limitations of human observation.
On-premise analytics solutions like Walkbase do not miss details. They record the entire story in real-time, saving those salient details for further exploration at any point in the future. Deviations from our expectations can be analyzed, investigated, understood and optimized. Over time, these optimizations can impact profitability and make the difference between staying competitive, and moving aside for those who can make more money on that real estate.
Tying in-store analytics with digital signage
Digital signage is another big opportunity for retailers to do more with less. But tying these two technologies together, and allowing them to talk to each other allows retailers to optimize the customer experience in some truly impactful ways.
eCommerce websites have an incredible advantage over traditional retailers. A/B testing allows online stores to constantly optimize their content, so that shoppers are ever-more likely to convert.
Tying in-store analytics with digital signage gives physical stores the same capability. Tracking anonymous shopper behavior allows retailers to see key metrics like average dwell time and pathing, enabling leadership to see whether that “jaw-dropping ad” actually led to a change in behavior after all. Conducting a test can help retailers answer those questions about merchandising and marketing effectiveness, leading to increased sales and profound insight into their customers.
These insights can help retailers make significant changes to how shoppers engage with their stores. Do you want shoppers to head down aisle 5? Suddenly this question is answerable, with digital content and the sensors to track effectiveness. Within a few days, you know whether shopping patterns have changed.
In-store analytics allows the store to see how they’ve influenced behavior, even when that influence does not lead to a direct purchase. When we see that behavior, we might decide to continue the experiment by introducing an A/B test on that transactional content. Maybe we just need a different video, or a product comparison in order to give the shopper that confidence that they need to put the item in their cart. We can deliver different content and then see how it influences behavior.
What would Amazon do?
“56.29% of shoppers want to see product reviews featured in physical stores.”
— What do online shoppers want from the in-store experience?, 2021
Amazon excels at inducing purchase behavior. That’s because eCommerce is their home; they run experiments, updating their services, pricing, and display constantly. Incremental improvements have led to increased conversions and critical understanding of customer behavior — also known as customer centricity.
Along the way they figured out that they make more money when they help shoppers make more confident purchase decisions. They do that with tools for product comparisons, and with product reviews.
Now that shoppers have experienced eCommerce, they are starting to want the same features in their physical stores. According to a Reflect Survey conducted in September, 2021, 56.29% of shoppers reported that they would like to see product reviews featured in physical stores (“What do online shoppers want from the in-store experience?”, 2021). Amazon makes it extremely simple to find all of that information at the moment of purchase, and along the way they add Amazon’s choice, user reviews, Prime, etc., to increase the shopper’s confidence in the product.
This process can only occur because of the user data they receive every day on user engagement. Interpreting this information helps them understand what elements are working, as well as those elements that are only half-way working and could be made better.
Many retailers now are full of subjective information regarding how customers interact with the store environment. Either they rely on customer surveys (which are expensive and rely on biased feedback), or they are built on old assumptions. Some of this information, maybe even most of it, is accurate, but some is not. How do retailers tell the difference?
As we move forward, we expect to see a large divide between digital innovators and traditional retailers, with store analytics solutions like Walkbase TREQ playing a decisive role in competitiveness.