Location Analytics and Retail — Friends At Lastby@YoavVilner
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2,224 reads

Location Analytics and Retail — Friends At Last

by Yoav VilnerOctober 26th, 2017
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It might seem that retail never changes. At least, that’s how many retailers would like it to be.

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It might seem that retail never changes. At least, that’s how many retailers would like it to be.

Instead, retail is constantly shifting — with retailers slow to adopt new technology and strategy. Being slow to adopt new technology isn’t always a bad thing but at a certain point, retailers will be left in the dust.

With the rise of online stores and eCommerce, traditional retail stores are forced to adapt to changes and to be more innovative than ever. Online stores present many advantages to their customers: they’re available anywhere and anytime, have “endless aisles” and, for the most part, can predict and analyze customers’ behaviour to offer them products they’re actually interested in.

Recently, traditional stores have begun to understand the power of digital technologies and to integrate them directly into their stores. One of the most interesting implementations of new technologies in retail is the use of location analytics to improve customers’ in-store experiences.

What is Location Analytics?

The most basic definition of location analytics is the ability to gain insight from location data. But that is a bit too simplistic. A more accurate description is as follows:

Business data usually contains geographical or location data which mostly goes unused. This data can be as broad as city and country or as specific as GPS location. When this data is placed within the context of big data dashboards and data science models, it allows companies to discover new trends and insights.

In retail, location sensing technologies typically require customers to use the retailer’s app and grant it permission to track their location in return for a reward. In this case, the customer’s location is determined through the phone’s GPS or, more accurately, via WiFi or beacons.

Examples of Location Analytics in Action

Many retailers are already using data analytics to improve the customer experience.

One particularly promising opportunity allowed by data analytics is the creation of heat maps. In-store heat maps help retailers have a better idea of customers’ traffic patterns at particular hours of the day or even in real-time.

Let’s imagine you’re planning to open a store that sells clothes for teenagers. In order to find out the best location for that specific store, you’ll first want to know which areas teenagers are most likely to shop in.

Once you learn which area is best for your target group of consumers, you can increase your sales revenue and your marketing efforts can be more specific and effective.

Heat map data can also be used to compare different stores and departments, and can eventually help optimize the retail experience for particular customer segments. This information is useful for making rapid course corrections and for granting customers an improved, more personalized experience.

One of the leading providers of Geographic Information Systems (GIS) technologies is Esri. The company’s location-based analytics tools have helped several retailers boost their competitive edge, reduce their environmental impact, mitigate their operational risk and lower costs across the board.

Wendy’s, the world’s third largest quick-service hamburger chain, is a great example of a retail company that cleverly implemented Esri’s services for good. Specifically, Wendy’s interest was to determine how far customers are willing to travel to come to a Wendy’s. Location analytics has allowed the staff to easily view sales records and customize demographics on existing restaurants. More than that, Wendy’s was able to predict the value and risks for new and existing restaurant locations.

Why Locations Analytics Hasn’t Seen Widespread Adoption Yet

Exciting as the possibilities are, retailers have to deal with a crucial obstacle when implementing location analytics in their business strategies, which is getting customers to download and use their apps in the first place.

A study conducted by Harvard Business Review has shown that consumers are willing to share their precious information only to a handful of retail apps. Consumers are, in fact, more likely to download retail apps if they’re compelling enough to use within the store.

An interesting example of this is Home Depot, which developed an app with store-specific navigation that solved a major customer pain point — difficulty finding items without the assistance of a store employee.

Other factors that could lead customers to download a retailer app are special discounts on purchases, convenient payment methods, loyalty programs or even just better assistance over the phone.

Why it’s Time to Adopt Location Analytics in Retail

Another interference that has limited locations analytics from becoming more widespread is that, until very recently, the computational power needed to analyze location data in real time wasn’t affordable.

But today, the GPU SQL databases like SQream, have allowed retailers to process and visualize location data more efficiently.

Location analytics provide an immense amount of benefit to all retailers. It can be used to create more accurate shipping estimates, change the products promoted to different areas and more.

You could even create heat maps and identify which regions purchase the most expensive products. This can then be used to improve regional performance and in turn overall performance.

But why adopt location analytics now rather than five years from now? After all, won’t it only become cheaper and more effective with time?

Sure, but you’ll also have dropped behind your competitors by a significant, possibly irrecoverable margin. In retail, it’s important to get ahead of the curve now more than ever. You’re competing against both giants of industry like Amazon and smaller, savvy retailers. Both are adopting the latest tech to gain an edge.

If you don’t your orders will slowly dwindle and, if you’re lucky, you’ll be acquired by someone else. Both “too big to fail” brand and smaller niche brands are going out of business left and right.

Today’s brick-and-mortar retailers are in a constant race with online competitors. With the results they can gather from location analytics, retailers now focus on innovating and improving their services, while offering their customers an even more personalized experience along their journey.

The technology to do it is already here, and retailers who win will be the ones that have built their analytics structure ahead of time.