Big Data

3 best practices for using locational data to improve retail sales

Locational data from mobile devices can reveal a lot about customers' shopping habits. Here are three tips for using that information to make business decisions.

Right now, retailers are vigorously engaged in employing analytics, both for their ecommerce and their retail operations. One major motivator for this sometimes slow to innovate sector has been Amazon's 2017 acquisition of Whole Foods. The move threatens traditional retailers because formerly secure markets now have new competitive pressures.

"Retailers are waking up and realizing that there is a wealth of data beyond just the first party data that they traditionally collect and use," said Brian Handly, CEO of Reveal Mobile, a mobile marketing provider. "They are reaching out for more data that will enable them to compete against other aggressive retailers, and one of these vectors into the information is locational data."

SEE: Rentable Samsung pop-up shops bring real-time data analytics to retailers (TechRepublic)

What can locational data deliver that other forms of data can't?

It allows companies can find out which aisles customers are frequenting, and what products they're looking at in combination. Having information about purchasing combinations can help companies make decisions about promotions and merchandising.

Outside the store, companies can track location data to find out the geographic areas of online customers, and which other stores customers are visiting.

"Information like this can be highly useful for targeted marketing campaigns," said Matthew Davis, chief marketing officer at Reveal Mobile. "For instance, you can look at your foot traffic patterns year over year, and see where foot traffic increases the most in specific months."

One of the projects that Reveal Mobile is presently engaged with concerns Whole Foods. "What we want to determine is what the effect of the Amazon acquisition has been on Whole Foods' nationwide stores," he said.

SEE: How Wayfair used big data and omnichannel retail to transform shopping (ZDNet)

For retailers that have not fully engaged foot traffic analytics yet, here are three emerging best practices to consider:

1. Identify your goals and then leverage your traffic analytics

Foot traffic and web navigation analytics can assist in retailing and merchandising for physical and online stores, but foot traffic can also be used to track the geolocations of customers to determine where they live and where they shop. This intelligence enables you to perform additional segmentation for your marketing campaigns. Another way to leverage foot traffic is by observing which physical locations your customers visit. This could also help determine which competitor stores customers frequent.

However, none of these analytics are going to succeed if they're not linked to measurable business goals. For example, does your business want to find out what the most popular items in certain areas are, and stock them along with less popular items to improve sales? Or do you want to assess competition from online and brick-and-mortar stores to set more aggressive price points?

SEE: How Sephora is leveraging AR and AI to transform retail and help customers buy cosmetics (TechRepublic)

2. Get "pluggable" foot traffic analytics

Handly mentioned that his company's foot traffic analytics can easily be plugged into larger analytics engines such as those resident in Salesforce and other marketing and CRM packages. Other vendors offer plug-and-play integration as well. However, before you sign on a dotted line for any foot traffic analytics package, closely examine the plug-and-play interfaces that the solution offers. In some cases, integration with your internal systems might not be as straightforward as others. You want something that can easily be plugged in to your existing systems.

3. Challenge your data analytics team

Whenever you add a new source of analytics data, you should challenge your analytics staff to review this data and identify the different ways that existing data can be aggregated with the new data source so fresh insights can be delivered. Vendors can only provide so many best practice data insight approaches. You have to do the rest.

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Image: iStock/shironosov

About Mary Shacklett

Mary E. Shacklett is president of Transworld Data, a technology research and market development firm. Prior to founding the company, Mary was Senior Vice President of Marketing and Technology at TCCU, Inc., a financial services firm; Vice President o...

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