Use of Data Mining Remains Modest Among Grocers
Predictive analytics — that is, mining data for information to predict trends and behavior patterns — can be used by grocers in several areas: category management, pricing, inventory planning, e-commerce and mobile marketing, among others.
While some major chains deploy this analytical tool throughout their companies, widespread use by grocery retailers remains modest to moderate at best.
“Most grocery retailers do not yet have the capabilities in-house to fully leverage predictive analytics within their organizations,” says Tony Kleiner, senior business consultant at Dayton, Ohio-based Teradata, a provider of Big Data analytics. “Some are in the process of trying to develop these capabilities, while many others are still waiting to determine whether they want to make the commitments necessary to become data-driven organizations.”
Reena Kapoor, of You Technology, admits that grocers’ overall use of predictive analytics is “modest,” but recommends it as an essential strategy in any chain’s business and growth planning.
“They need strategies to improve their top-line growth and margins,” says the VP of product for the Brisbane, Calif.-based provider of digital-offer networks. “Predictive analytics can help with this. Moreover, they operate in close competition, and their competitive space is only getting more diverse with the advent of Amazon, Google and other online players who have a lot more cash to throw at their business.
“Analytic behavioral and value segmentation can — and should — be built to not only help grocers understand their customers’ shopping/ spending habits but personalize the customer experience as well,” she goes on to say. “Predictive modeling is a must when addressing customer retention and promotional strategies. Grocery chains simply cannot afford to lose money. Having the means to predict shopper behavior targeted marketing trends for category management and/or pricing could be the golden goose for their long-term health, and even survival.”
Other technology executives say that most grocers are far from operating that way. For example, Ziad Nejmeldeen, of Infor, finds that too many decisions are still handled through a mixture of “significant human effort” and Excel, when the data and technology have long existed to make those decisions more intelligently.
“How many grocers use store-based sales data to make localized assortment decisions for that store?” asks the chief scientist for the New York-based provider of business applications. “And then there is the data that is newly available — such as loyalty — which has yet to be seriously leveraged. This data means we can track customer spend over the course of the year, see what they like to buy by time of year, and use that information to effectively market via email or mailer campaigns. We see some grocers starting to do this, but they are still in the minority.”
True Practitioners
So which grocery retailers are the true practitioners of predictive analytics today?
Whole Foods Market is one. Infor’s Dynamic Science Labs has been working with the Austin, Texas-based retailer to identify the localized products that require price protection to maintain long-term customer loyalty.
“In the U.S., Whole Foods stands out for their strong focus on localization,” notes Nejmeldeen.
“‘Right product/right store/right time’ is said far too often, but that is exactly what they are going for by leveraging store-level historical transactions, that is, market basket data. We can also add ‘right price’ to the list.”
Another grocery retailer that has implemented predictive analytics is Europe’s Aldi Nord for its more than 1,400 stores. The Germany-based chain recently incorporated SAP technology for in-store stock and replenishment planning. The solution enables Aldi to generate order proposals based on sales forecasts. This empowers in-store personnel to make real-time, informed decisions based on data captured on mobile devices.
Brookshire Grocery Co. recently launched a project to digitally transform more than 150 stores to meet consumer expectations. Upon completion, the project will gather accurate, consistent data to help Tyler, Texas-based Brookshire align its actions with the company’s brand promise and create an omnichannel experience for shoppers. The most recently completed phase uses SAP technology, which now allows Brookshire to gather sales information to design personal, profitable promotions. Additionally, the company has been able to collect and analyze behavioral trends to respond to shoppers’ changing demands.
Minneapolis-based Target also makes great use of predictive analytics, according to Graeme McVie, VP and general manager of business development at Toronto-based Precima. “They’re successful because they have highly visible support from senior management and they have a central merchandising strategy team that acts as a center of excellence to consistently support the category management team. Tis enables Target to retain internal expertise in analytics that they can then use to support the category management team in how to best use the analytics to make decisions on a day-to-day basis. The team can enable and support the required change management around internal processes and the organization to ensure that Target acts on the predictive analytics and maximizes the value that is captured.”
John Kelly, managing director and a leader of Emeryville, Calif.-based Berkeley Research Group’s predictive analytics practice, says that Safeway is advanced in predictive analytics partly because it’s based near Silicon Valley and has been able to attract some innovative data science talent.
You Technology works with retailers, including ShopRite, Kroger and Big Y, on predictive analytics integrated with digital offers for loyalty and promotions, according to Kapoor.
Getting Started
Not every grocer has the resources to deploy full-service predictive analytics across several parts of their operations, but experts recommend that they take small steps to increase their use of predictive analytics, or at least get started.
“The first step is to understand the business systems that will provide a singular view of your customer data. This digital core, a full set of centralized data points, is a critical success factor,” says Randy Evins, senior principal IVE food and drug at Scottsdale, Ariz.-based SAP Retail. “Data consolidation and the creation of a digital core will allow grocers to implement custom promotions, enhanced product searches, variable pricing, and more.”
This is just the starting point, according to Evins. Retailers and their suppliers need to take a holistic view of their supply chain to respond quickly to consumer demand. “In the long term, whether a purchase is digital or in-store, a tighter supply chain will enable retailers to use predictive insights to alert a supplier of a coming need, and that translates into a better customer experience,” he says.
Grocery has a distinct advantage over other forms of retail, because consumers typically make frequent shopping trips, points out Alan Lipson, global retail and CPG marketing manager at SAS, a Cary, N.C.-based provider of business analytics software and services. Frequent-shopper card data also help grocers track a customer’s purchases over time and understand a shopper’s evolving buying behaviors.
“By combining shoppers within a single household, grocers can create a more complete picture of that household’s needs, then use analytics to put together marketing programs that can help increase basket size, improve margin and increase consumer satisfaction,” Lipson notes.
“Analytic behavioral and value segmentation can — and should — be built to not only help grocers understand their customers’ shopping/ spending habits, but personalize the customer experience as well.”
—Rena Kapoor, You Technology