Customer frequency analysis - Retail gets to know its customers better


© Data Components K+S GmbH

By now, most users have gotten used to the fact that in theory, every click on the Internet can be traced. Based on the collected data, online retail is for instance able to make customized recommendations for other products. Brick-and-mortar retail stores need precisely such solutions, because they don’t just want but also have to get to know their customers well. One of the tools that retailers have available for this is customer frequency analysis.

According to the Gabler Wirtschaftslexikon (“Gabler Dictionary of Economics”), customer frequency analysis is the ”analysis of customer activity in a retail store. The goal of the analysis is to gain insight on customer behavior and to optimize productivity on the sales floor“. However, with this slightly older definition, the focus is still on the analysis of customers’ paths, which provides new insights for the design and the set-up of the store.

The analysis possibilities are varied

By now, the current solutions provide retailers with the chance to draw from a much larger data pool. After all, they are simply not able to compensate for the information disadvantage compared to online stores with data on how many customers remained for how long at which shelf. This is why more and more retailers adopt the tricks and methods of their online colleagues with the objective to get to know their customers, preferences and behavior patterns better.

One example for this is the solution offered by the Berlin startup 42reports. It measures visitors based on the MAC address sent from their Smartphone and even recognizes individual visitors again if they are returning to the store. Depending on the clientele, between 40 and 70 percent of visitors are being identified. In a EuroCIS-Interview founder Christian Wallin explains how brick-and-mortar business benefits from this data and analysis, which are also used in controlling E-commerce.

On the one hand, retailers do not obtain direct personal data on the Smartphone users through the readable MAC address of the devices, compared to online stores where customers also provide their name and address. On the other hand however, the customer activity pattern in the store along with the data on previous consumers provide a good data base with which the customer in the store can be more specifically addressed with personalized ads than was previously the case for instance.

Hidden camera systems make customers feel uneasy

Of course, the development does not stop there. Plus it yields peculiar results in some cases. Last year, the mannequin and display form manufacturer Almax and Kee Square – a spin-off of the Technical University of Milan, Italy – developed the concept for a new type of information acquisition: mannequins are no longer just showcasing collections and enticing customers to come into the store. These mannequins can do much more: thanks to cameras in their eyes, they provide retailers with details on the person that looks at the garments such as his/her age, gender, ethnicity, customer crowds and how long they lingered. The mannequin’s pupil contains a camera that is connected to special facial recognition software. It gathers statistical data on the person who walks past the mannequin.

This also demonstrates the perennial crux when it comes to data acquisition: early reactions on this hidden surveillance have been consistently negative. It is not just that the retailer needs to be in accordance with privacy policy, – after all, gathering sufficiently anonymized data is definitely permitted – the retailer also needs to communicate these measures to the customer. Aside from data protection issues, many people consider this type of hidden surveillance as an invasion of their privacy. The hidden cameras result in people feeling uncomfortable while being watched during their shopping endeavor.

Current solutions can do more than just counting customers

Customer frequency analysis through video surveillance is not a particularly new invention. Retail has tried for some time to measure customer frequency with light barriers or – in a very old-fashioned way – by manual count. However, none of these methods delivers the extensive data the newer available solutions are able to provide.

The advantages of a solution like the one by 42reports are obvious. The retailer doesn’t just find out where and how long customers remained at the store, but also how often they frequent the store, what they are interested in and which products attract special attention. Whereas until recently, software was not able to read any data besides customer paths from the video images, more current versions are clearly able to help the retailer to improve the customer’s shopping experience and the product choices and to understand his/her customers better.

Linking online and offline: utilizing voluntarily provided information

Even today, another step in development already provides even more extensive options for data collection. Since many retailers today pursue a multichannel strategy, - meaning they operate one or several stores as well as an online store – with a little effort they are able to link the data gathered at the store with voluntarily provided information by customers from the online stores. An email address is already enough to incorporate online buying behavior with the customer behavior analysis. The retailer is then able to send personalized offers to the Smartphone while the customer is still in the store and is able to for instance also check out the effect of different ad formats.

Walking a thin line in data privacy

Of course, from the retailer’s point of view, there is nothing to be said against the new forms of customer analysis, but customers oftentimes have a very different attitude on how their personal or individual data is being handled.

Here you need to walk a thin line between the advantages the retailer gains by using customer information and the potential damage to the image, if the retailer is suspected of data abuse.
However, retailers can counteract this with an intelligent communications strategy. After all, customers also gain advantages and new services by becoming “better acquainted” with the retailer.

Ultimately, customer analysis at its core is meant to show the customer products that could be interesting to him/her. Ideally, the retailer plays it safe by using a mix between anonymized and voluntarily provided information. And the customer is also satisfied, because he/she receives meaningful shopping ideas.

Daniel Stöter,