How to use foot traffic analytics to boost your store’s performance

Big Data. Analytics. Mobile-enabled foot traffic technology. These aren’t just buzz words that people throw around to sound clever (okay, maybe sometimes they are…) but  they can actually help you increase engagement and sales. Advancements in Big Data and mobile now let you analyze how people are behaving inside your store, thus giving you tremendous insights on how to improve layout, marketing, and customer experience.

To shed light on how in-store analytics can help retailers, we sought the help of our friends from Software Advice, a company that researches retail technology. They recently published a report by tech expert David Strom about how retailers are using mobile-enabled customer analytics.

Vend caught up with David to get more insights on what retailers can do with the technology, and we’ve incorporated some his answers in the post below:

What tools can retailers use to track shopper behavior?

There are a number of companies you can check out to help you analyze foot traffic. Depending on the company, in-store analytics vendors aggregate information from a variety of sources, including Wi-Fi signals, payment systems, surveillance cameras, and more. They then generate reports and tools to help you make sense of the data and take action.

According to David, some of the vendors in the space include:

Indoor Tracking Technologies Vendors

(You can check out his original table here.)

How do you know which analytics vendor is right for you? Consider the type of store and the kinds of information you need to collect. Also be sure to look into data sources you already have. For instance, if you collect customer data from your Wi-Fi network, surveillance tools, or POS system, find a solution that integrates with those existing tools to make it easier to plug in the information.

Do note that some solutions are more advanced than others. According to David, some “can track the movements of customers down to a few feet, while others can locate a shopper within ten or 20 feet or only collect data on an aggregate store level. Figure out what kind of location data you need and make sure your solution can deliver to that precision.”

Do your research, see what similar retailers are using, and test out the solutions in your store.

What types of data should retailers collect?

David named 5 key data points that can give you useful data about your customers. They are:

1. Dwell time in the store

2. Average shop times across a particular time of day or day of the year

3. Parts of the store that customers visit the most and the least

4. Where customers live or work in relation to the store

5. Cross-store data comparisons

What should you do with all that information? The first step to turning data into something useful is to analyze what those numbers mean and figure out how you can improve. For example, if the numbers tell you that checkout time in your store is longer than the industry average, use that information and find ways to streamline the checkout process.

Or, say you know which parts of your store are getting the most and least traffic. The next step is to figure out why certain store sections are getting more visits than others. Is it because of the products in those departments or is it their positioning in the shop?

And don’t forget to consider factors outside your store, such as the weather, environment, time of year, etc. As David put it:

Retailers need to understand what the above metrics mean and how to explain the differences, such as was there bad weather one day that increased or decreased the dwell time? Did some other store nearby run a major sale that brought people into the mall or the block? Did a special advertisement bring more customers in for a particular reason? Did a store layout encourage or discourage shoppers from going to a particular place? It is more than just analyzing spreadsheet data.

 

Examples of stores using foot traffic analytics

One well-known retailer invested in in-store tracking is Godiva. According to a case study by ShopperTrak, the chocolatier used people counters to gain insights about the foot traffic in its stores. After looking into the traffic trends for their branches, Godiva used the data to “plan staff rotas to ensure that there is always a healthy associate to customer ratio and to place the best staff on the floor at peak traffic times.”

In addition, the data also allowed Godiva to figure out which window displays reeled in more traffic, so it could optimize them accordingly.

Hugo Boss is another great example. According to David, the store is making use of heat sensors to help determine how products should be placed and arranged in its high-end clothing stores.

Your take

Do you analyze foot traffic in your store? Are you planning to do so in the future? Share your thoughts in the comments below.

About Francesca Nicasio

Francesca Nicasio is Vend's Retail Expert and Content Strategist. She writes about trends, tips, and other cool things that enable retailers to increase sales, serve customers better, and be more awesome overall. She's also the author of Retail Survival of the Fittest, a free eBook to help retailers future-proof their stores. Connect with her on LinkedIn, Twitter, or Google+.

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