Consumer Behavior

Using location data to create a more personalized in-store shopping experience

John Kavulich, VP, IoT Solution Sales, Acuity Brands Lighting, Inc., shares insight on how retail leaders can close knowledge gaps when it comes to customers and gain greater insight into shopper behaviors. The answer: location data.

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December 17, 2020 by John Kavulich — Vice President, IoT Solution Sales, Acuity Brands

Consumers' online activities and shopping habits are well known to big retailers. E-commerce teams use every opportunity to observe shopper behaviors: how they find preferred products, how they respond to ever-so-subtle user experience adjustments and how many programmatic ad impressions it takes to influence them to make a purchase. Such insights power hyper-personalized shopper journeys, optimized product recommendations, finely-tuned email outreach and more. None of this is new. In the year 2020, consumers are familiar with, and even expect, online shopping experiences to match their personal desires and interests. So, why can't they get equally personalized experiences in the store?

One reason is that consumers do not leave the same digital breadcrumbs throughout stores that they drop online. They do not produce browsing histories or leave behind items in a shopping cart. While loyalty card data can connect in-store purchases to digital profiles, the in-store behaviors that precede those purchases are opaque for most retailers.

How location data fuels a more personalized in-store experience

Many aspects of existing retail operations rely heavily on data to drive revenue and shopper loyalty. From brand choices to product placement, extensive, ongoing research drives retailers aiming for maximum customer engagement and high value transactions. Yet, even with this volume of information, some retailers still haven't closed the knowledge gap of how shoppers behave within the store. A strong starting point to address this lack of knowledge is understanding how to enrich current data sources like sales receipts and loyalty accounts with location data that provides a glimpse into the customer's in-store behavior.

Beyond anecdotal feedback from associates and interactions with customers, retailers have very limited understanding of customers' purchase psychology and purchase-decision thought processes. While receipt data will show items and quantity purchased, the critical component of how a shopper navigated the store prior to check-out is missing. For instance, what could a retailer do if they knew a shopper has been in a certain aisle for more than ten minutes and didn't purchase an item from that section? Perhaps they need a sales associate to unlock an item.

Or maybe the customer can't find pricing or a product they thought was on sale. Receipt and loyalty member data will not explain why someone might have spent so much time in a specific aisle without purchasing anything from that section. Indeed, without the right data, retailers don't even know what questions to ask regarding in-store behavior or what role it plays in purchase decisions.

So, how do retail leaders close these knowledge gaps and gain greater insight into shopper behaviors? How do they apply customers' navigational patterns or the psychology behind product choices to improve the on-site shopping experiences? Fortunately, there's a better way: location data. Indeed, accessible technology already exists to understand how shoppers engage inside physical stores.

How in-store location data improves the customer journey

It's likely only a matter of time before consumers begin demanding big-box retailers offer individualized in-store shopping experiences like the online customer journey. Team leaders need to untangle how customers navigate the store and discover which specific areas they spend time to create a more personalized experience.

We believe meeting these expectations requires investing in location data driven through visible light and Bluetooth technology, using real-time location services infrastructure along with either tags embedded into shopping carts and baskets or opt-in location sharing from mobile phones through retail mobile applications.

When retailers understand where shoppers are in the store, their existing data points, like receipt data and loyalty account holders, become more useful. For instance, retailers can overlay existing receipt data on top of location data collected from tagged shopping carts or baskets to identify high traffic areas. Do purchases in these areas align with foot traffic? If not, it might be beneficial to station more associates in these popular areas; the presence of a helpful hand might be all customers need to make the purchase! If a loyalty card shopper spends a significant amount of time in one aisle, this a perfect opportunity for the retailer to send sales alerts and promotions for products in that aisle through their branded app.

As these technologies become more commonplace, and as retailers increase their understanding of the power of location data, we believe they'll also recognize the value of this information extends far beyond the customer experience.

Capturing in-store data can also identify high priority design changes, such as wider aisles and improved flow patterns to accommodate physical distancing. Easily navigating store layouts are a critical part of a positive customer journey. Collecting and applying this type of otherwise hidden location data can help retailers mirror the customercentric online shopping experience within their physical locations and fulfill their in-store business objectives.

John Kavulich is VP, IoT Solution Sales at Acuity Brands Lighting, Inc.