Big Data In Traditional Retail – Part II

Bill Schmarzo By Bill Schmarzo August 13, 2012

Part I of my “Big Data In Traditional Retail” series covered some areas where Big Data is having immediate impact on today’s brick-and-mortar retailer (note:  I will be covering online retailers in a separate blog).  The purpose of Part II is to look at some new innovations occurring in the Big Data space, and how those innovations could transform the very fabric of their relationship with their customers.

New Big Data Retail Application Opportunities

Smart Shopping Cart.  The smart shopping cart extends the trend in using sensors and RFID technology to provide new sources of customer interaction data.  Much like what we’re seeing across other industries (smart grids, the connected car, Positive Train Controls, intelligent appliances, Progressive Snapshot), the smart shopping cart will capture the in-store shopping behaviors and traffic patterns of customers.  When coupled with the customer loyalty card information, this will enable brick-and-mortar retailers to compete on equal footing with the on-line retailers in their ability to capture key in-store information like time in store, store routing, and time spent at specific store destination areas (cereal, frozen foods, produce, deli).

Personalized Shopper.  Leveraging the smart shopping cart, or just a smartphone app, coupled with QR and RFID codes, retailers can create a shopping experience customized to the shoppers buying behaviors and shopping objectives.  Based upon the customer’s shopping needs and meal objectives (weekend BBQ, birthday parties, Thanksgiving dinner), the “personalized shopper” could do the following for the customer to “personalize” their in-store shopping experience:

  • Construct the optimal shopping list (given that the customer has input their shopping and meal objectives)
  • Optimize the shopper’s route through that particular store’s layout (heck, you could even add green/yellow/red indicators to identify in-store traffic jams!!)
  • Make customer-specific product and meal recommendations
  • Provide real-time coupons based upon what’s already in the shopping cart (“I see that you have toothpaste in your cart, how about a 50% discount on a new toothbrush?”)
  • Optimize the shoppers budget (given the customer has input budget constraints)

The challenge for any retailer is to balance the need to move certain products (sale products, private labels) at certain prices (given price optimization and yield optimization models) with the needs of the shopper.  The retailer must always keep the needs of the customer as the #1 over-riding priority if the retailer really wants to be the shopper’s strategic partner.

Shopping Budget Optimization “Dashboard”.  One of the most interesting opportunities is to fundamentally change the nature of the customer relationship.  Instead of focusing on just selling products, retailers have the opportunity to become the trusted shopping advisor.  Much like some financial services companies (e.g., Mint) have been working to become more strategic financial advisors, retailers could put themselves in a similar position by helping shoppers to optimize their shopping budgets given the customer’s shopping, meal, and budget objectives.  For example, instead of a sales receipt that really tells the customer nothing new, what if you leveraged the customer’s historical purchase data to provide a “spending report” much like financial services companies provide to their customers.  Let’s walk through what that might look like.

Improving the Shopping Experience

Today, the shopper receives a shopping receipt like the one to the left (by the way, this discussion is not a slap at any particular retailer.  This is a general observation that seems relevant for a large number of retailers).  The shopping receipt tells the shopper what they purchased, how much of each item the shopper purchased, at what prices, and total money spent.  In some cases, the receipt also tells the shopper how much they saved using their customer loyalty card, and maybe even things like how many credits they have earned for a free coffee or whatever.


Instead of this traditional sales receipt, what if the sales receipt become more of a shoppers shopping budget “dashboard” (like the image on the right) that could provide some of the following shopping optimization capabilities:

  • Provide benchmarks against like or similar shoppers’ buying preferences across different product categories, stores and geographies
  • Highlight individual purchase trends in the types of products and product categories, and the frequency of those purchases
  • Provide Amazon-like product recommendations to make specific product or meal recommendations
  • Provide insights and specific recommendations to help customers optimize their shopping budgets

Now let’s take this one step further.  Let’s look at how we might leverage all of the retailer’s customer loyalty and shopping data to transform a retailer’s smartphone app into a shopping optimization tool.

From the mockup below, the example app on the left (“Current Smartphone App”) shows the current smartphone app (the smartphone app provides information on local promotions and personalized offers).  However, the enhanced app on the right (“Potential Shopping Optimization App”) provides not only the current local promotions and personalized offers, but goes a big step further in helping the shopper to optimize their shopping budget (given their particular shopping objectives and constraints) while improving the overall shopping experience.

Clicking on the “Grocery Budget Analysis” button would open a module that not only shows the shoppers purchasing trends, but could also provide insights into that shopper’s buying preferences versus a benchmark group to identify ways to spend their budgets more effectively.  Also, the module could provide specific budget, product, and meal suggestions (“You seem to buy lots of Mr. Crunch.  Purchase 3 extra boxes and get 50% off the regular price”).

Big Data Innovations In Traditional Retail

The traditional brick-and-mortar retail industry is ready to challenge the online retailers’ ability to affect the customer’s real-time shopping activity with their own in-store recommendations and insights that will improve the experience.  Not content to be just another channel, Big Data and new developments in the retail industry hold the potential to transform the customer engagement from a tactical purchase occurrence into a more strategic, long-lasting relationship.  Helping the shopper to optimize their budget and improve their experience will create a sticky relationship that draws them back to the retailer time and time again.

Bill Schmarzo

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