Get personal with your retail customers with hyper-personalized location driven engagement.

As the internet and mobile device usage blend in with traditional physical store locations, the retail industry is experiencing massive changes in the way it does business.

Fri Oct 19 13:16:00 EDT 2018
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As the internet and mobile device usage blend in with traditional physical store locations, the retail industry is experiencing massive changes in the way it does business.

The primary mission, however, hasn’t changed: Demand high quality customer engagement, which is essential to a successful business. That means even companies with millions of customers must treat each of those customers as an individual. Consumer expectations are driving changes and the retailers need to act. Hyper-personalization, driven by good quality data with accurate location context, helps to fulfill the expectations.

Personalization is the key for high quality experiences. For those that practice ‘clienteling,’ some staff have always had their black book—notes related to transactions, maybe even future recommendations for purchases. The trending practice—clienteling and online personalized online customer journeys—provides more personal and informed customer service that may influence customer behavior related to shopping frequency, average transaction value, and other retail key performance indicators. At the same time, the customer experiences a personal touch.

Today technology is replacing this black book with a valuable cache of customer data including preferences, prior transactions, recent web browsing and recommendations. Simply gathering the data, however, is not enough. Knowing how to use it is what makes the difference between business-as-usual and an uplift in transactions, and that’s where data is being used to make the personal touch better.

Many customers walk into stores knowing pretty much what they want. However, armed with such detailed information, a retail employee is on a level playing field with the customer who walks in the door. Based on shopping history, the employee can make relevant recommendations, creating a personalized shopping experience that equals excellent customer engagement.

The practice has worked online for some time now. Customers who purchase a specific item can be notified about similar items. Drilling down even further, a male customer with no children should never receive offers for diapers.

To pull all this together, data must be organized across channels. The first step is to collect data, and cleanse that data—that is, eliminate duplicate or false entries, validate different addresses, and so forth.

The next step is to connect that data across store locations and online or mobile devices. With the data as the foundation, the blending of channels—and hence, transactions--becomes more seamless, simpler for the customer and more profitable for the retailer. At Pitney Bowes, we layer in location data, gathered and cleansed over years of addressing experience and providing more precise data.

But wait, there’s more.

Connecting to physical stores, research proves there’s an uplift of online sales where a physical store is present.[1] Many previously wholesale-only companies are opening physical stores and selling directly to customers.

Retailers may not always know the best place to locate a new store. Accurate location data can lead to putting those physical stores in the best location. For example, a coffee store that customers must pass before reaching a competitor must be factored into the plans. And variations in local demographics can seriously impact a retailer’s choice of locations. Using the diaper example, it might not be wise to heavily stock a store in a retirement community. Up-to-date demographic data will help avoid any unwelcome surprises.

Once the location is agreed, data can also be used to establish the optimum layout and product mix. Based on web transactions from the area, demographics, footfall patterns, traffic flow, points of interest and additional customer attributes, a retailer can determine what products are most likely to sell in a particular store and how to place them.

Life with data.

Once retailers have the right data and can trust it, they must know how to use it to capitalize on opportunities. Customer data and location analytics platforms can help, enabling retailers to make sense of the information they have and act appropriately.

Learn more:

Learn how to extract more value from your data by registering for an upcoming webinar titled Data-Driven Retail: Extracting Value from Customer Data, sponsored by Pitney Bowes.

[1] According to the Digital Shopper Relevancy Report of 2014 done by CapGemini, 72% of the analyzed consumers consider physical stores as the best driving purchasing channel which means that brick-and-mortar point of sale are still relevant in the path to purchase of the consumers. (Retail World, July 15, 2017)

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