How to Improve the Retail Experience Using In-Store Analytics
Attention, brick-and-mortar sellers: Are you making the most of the in-store analytics your customers generate? And are you using them in ways that viably and tangibly enhance the retail experience? If not, it's likely time to circle back and reconsider how you're using the literal treasure trove of valuable information being generated daily. A data-driven experience is a key part of your overall experience, and the data part is much easier to capitalize on when you know exactly what you're looking for. Let's explore what data-driven decision-making can do to renovate your retail experience, with a focus on questions businesses just like yours have.
What Is a Retail Experience?
For brick-and-mortar sellers in an increasingly digital world, it's the single most important thing to offer customers.
Having products locally may get people through the door, but a pleasant experience gets them to buy it, come back, tell their friends, leave good reviews, and all the other outcomes sellers would bend over backward to achieve. It's why nearly half of relevant big brands plan to invest more in retail showrooms over the next year, according to Shopify.
What Are In-Store Analytics?
In-store analytics refers to the systems and processes retailers use to measure what's happening within their stores and with their competitors. Common metrics include foot traffic, dwell time, and conversion rate (the percentage of visitors who make a purchase), among others.
Have you ever thought it was strange for a furniture store to offer free Wi-Fi? That perk makes clear sense for a coffee shop, but wouldn't a furniture retailer want a shopper to focus on the wares instead of their smartphone?
Well, it's because when a smartphone probes the Wi-Fi spectrum, it broadcasts its unique MAC (media access control) address — essentially a device's specific identification number — to any other device that's listening. As the shopper walks around the furniture store, then, each Wi-Fi probe is like a beacon for their location. With multiple Wi-Fi access points in a single store, it's possible to pinpoint a MAC address. The shopper doesn't even need to join the Wi-Fi network; this all happens passively.
That isn't the only option for collecting in-store analytics. Some physical retailers use apps that access a shopper's smartphone GPS to track their location in the real world while others use video analytics technology to monitor customer behavior, including movement patterns, in real time.
Although the devices don't share anything personally identifiable about their owners, this high-level process can tell store management a lot.
How Do In-Store Analytics Work?
Data like location and behavior tracking can be extremely useful in understanding broad shopping habits and enable stores to build informed communication with shoppers.
MAC addresses can be an essential ally in this process. Based on digital interactions shoppers have with various companies, their "anonymous" MAC addresses are often aggregated by a service and ultimately linked to personal identifiers like the device user's phone number and name.
This is really why a furniture store, or any retailer, would offer free Wi-Fi: It can provide them with MAC addresses, which can then help them access a trove of curated data about in-store shoppers. It also allows the retailer to do some pretty great things for customers, building out the retail experience digitally even as customers shop on-site.
How Can Retailers Use In-Store Analytics?
As the data builds — whether from multiple locations or over a long period in just one location — it becomes useful in crafting personalized communication, which can help increase sales and enhance the retail experience.
Returning to the furniture store example, let's break down a hypothetical situation: Based on data from a third-party service, furniture store management might infer that a window shopper is getting ready to make a large furniture purchase. Knowing customers in this segment are likely coming to either seriously browse or commit to buying, the store could preemptively push an SMS (or push notification if the customer uses the store's app) offering a percentage off certain items in the store in hopes of securing the sale.
The growth of the retail analytics industry highlights the benefits it provides. The global market is estimated to be worth $9.5 billion by 2025, marking a growth rate of over 18% compared to 2019.
How Do Analytics Improve Shoppers' Experiences?
Turning things another way, a retailer who knows a customer lingered in one area of the store on a recent visit and has their email address because it's linked to their MAC address might send the buyer an experience questionnaire, coupon, or tailored sales information based on the areas of the store they spent the most time in.
This kind of tailored communication becomes possible with the thoughtful use of in-store analytics. And that can solidify the foundation of a better overall retail experience no matter how strong the brick-and-mortar seller's current digital experience is. From discounts to personalized rewards programs and beyond, using shoppers' in-store data allows businesses and their customers to form a mutually beneficial relationship.
How Do We Respect Shoppers' Personal Data?
Naturally, consumers bring data privacy concerns to these sorts of transactions. While it's somewhat tongue in cheek, there's a viable reason that RetailWire's #1 rule of retail analytics is "don't be creepy." Customers like to know what you're doing with their data, and they especially like knowing your initiatives don't step too far into the realm of their personal privacy.
A big tip here comes down to a single word: disclosure. When you're open about what you're doing with the information customers provide you — whether you obtain it by MAC analysis, they give it to you directly via your mobile apps, or it's collected by any other means — you make it easier to avoid charges of being "creepy."
Are There Benefits for Both Shoppers and Retailers?
Yes, but this requires two things: First, businesses must be transparent about what they're doing with the data and why. And second, they must provide a genuine benefit from the data they extract. If not, why would customers go along with it?
Just as loyalty strategies involve giving shoppers coupons, cashback, or exclusive store events, retailers can build similar value into in-store analytics and customized communications. Rather than silently tracking customers and later aggregating data, retailers might even suggest customers opt into a smartphone-powered loyalty rewards program when they enter the store.
Location tracking has the potential to transform how retailers communicate with their customers. It can provide the insight to know precisely when to engage and when to leave someone alone. If you use analytics to provide tangible benefits back to consumers, you can curate great retail experiences.
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