In the world of brick-and-mortar retailers, businesses are on a continual quest to create a more personal and relevant experience for their shoppers.  In order to create this tailored experience, understanding each individual shopper becomes a necessity.

Unfortunately, much of the shopper data available today is incomplete, and many shoppers are unknown to retailers and manufacturers (brands). In turn, some businesses have become reliant solely on POS and loyalty data to create a relevant in-store experience, which is potentially short sighted.

To avoid the potential pitfall, here are three of the biggest mistakes brick-and-mortar retailers make when working to understand shoppers, and a few alternatives:

Problem #1: Focusing Only on the Shopper’s Personal Information

In an attempt to know the shoppers better, most turn to the data. Whether it’s mobile tracking, POS data, loyalty programs or purchased research, more and more retailers and brands are trying to “crack the code” of what shoppers really want. There’s just one problem: this data is incomplete and doesn’t provide a comprehensive view of all of your shoppers and what they do when in the store.

Also, at a time when shoppers are hypersensitive to how their personal data is accessed and used, most shoppers don’t want to reveal their information.  According to a study on ‘The Store of the Future,’ nearly three quarters of shoppers (74%) said they find it creepy when associates greet them by name.

The good news is it’s not always necessary to identify or recognize who the shopper is to tailor the in-store experience. There are sensors which do not retain a shoppers’ personal data, but enable tracking and identifying personas without their images or personal information. These sensors simply detect a specific persona and their associated behavior. For example, a female millennial shopper in front of a particular running shoe. With this type of analytical information, you are able to enhance the experience by responding with real-time product recommendations or relevant promotions to each individual shopper.

Problem #2: Relying Too Heavily on Transactional Data

Not every shopper entering a store will make a purchase. In fact, many never do: According to the 2018 Global Path to Purchase Survey, nine in ten shoppers leave a store without buying a thing. There’s a real opportunity to engage with these shoppers who are coming into stores yet not making purchases. Unfortunately, much of the information gathered is dependent on what happens at the register.

In this view, driven largely by POS and loyalty information, only the shoppers making purchases matter, which creates a massive gap in understanding the entire shopper audience. As a result, there’s little understanding as to how to convert the shoppers that don’t purchase. In addition, only analyzing POS and loyalty data misses the most important point – understanding the in-store shopper behavior.  

To determine what works and what doesn’t, insights must be captured during the entire shopping journey. Specifically, the ability to analyze the shopper behavior and journey throughout the store, categories, and around specific products. This allows businesses to understand what works and doesn’t for different types of personas. Only these insights will reveal how to tailor displays, categories, associate behavior, and other factors to create a better shopper experience.

Problem #3: Making False Assumptions Based on Select Data

The final mistake being made in the brick-and-mortar world is making decisions based on limited or select data. Maybe it’s only looking at the POS data, or evaluating store traffic based on the results from the door counter. Unfortunately, this causes us to overlooking key nuggets that could make or break decisions.

A key to evaluating this data is to begin with benchmarking it to establish a point of reference, and then correlate these analytics against each other to generate greater insight. For example, how many people that walk in the store make a purchase, and what is their basket size based on the shoppers demographics. It’s these in-store analytics and insights that are the key to presenting the complete picture – not just a subset that reinforce the obvious. In-store analytics and insights get to the heart of the pain points, helping to uncover findings that resolve issues such as why certain shoppers leave with disappointing basket sizes, where the branding or display choices may be failing, and how associate assistance could make a positive impact.

Learn More About In-Store Technology

Do these challenges sound familiar? If so, learn more tips about how brick-and-mortar can strengthen its retail strategy by measuring shopper behavior in another one of our recent blog posts.