How Well Do You Know Thy Customer?

Press enter to search
Close search
Open Menu

How Well Do You Know Thy Customer?

By Ed Avis - 05/01/2013

Grocery retailers and CPG companies spend millions of dollars annually gathering, analyzing and applying consumer shopping data. But are those investments paying off in a competitive advantage?

In today's hypercompetitive grocery retailing market, operating without regard to the vast reams of available data seems foolish, but investing in that data without measuring the financial return is equally shortsighted.

"Retailers are in more of a dogfight for customer loyalty than ever before," says Patrick LaPointe, executive vice president of MarketShare, a predictive analytics firm headquartered in Los Angeles. "Knowing which programs and promotions are truly driving not just incremental traffic or incremental revenue, but actual incremental profit, is more important than ever before."

"Knowing which programs and promotions are truly driving not just incremental traffic or incremental revenue, but actual incremental profit, is more important than ever before."

–Patrick LaPointe,

MarketShare

The following five ways to create a competitive advantage from consumer insights include three top applications for shopper data and two key techniques to use the data to boost return on investment. Regardless of the application chosen, a strategic approach is essential. "Strategy is absolutely critical, especially so with big data. Simply diving into big data without an end in mind, or a clear view of what objective or challenge this is solving, will only result in wasted time and resources," notes Jeff Weidauer, vice president of marketing and strategy for Vestcom International, an in-store marketing services company based in Little Rock, Ark.


"Simply diving into big data without an end in mind, or a clear view of what objective or challenge this is solving, will only result in wasted time and resources."

– Jeff Weidauer,

Vestcom International

1. One-to-one personalization

Experts consider personalized promotions the ultimate marketing use of shopper data. "Leveraging big data in the grocery industry today is all about being relevant and timely with individual consumers," says Wanda Shive, retail product manager at SAS, a business analytics software firm based in Cary, N.C. "Grocers who do so have a huge competitive advantage in today's marketplace."

Sobey's, a chain of Canadian grocery retailers with more than 1,300 locations, uses SAS software to create personalized promotions based on shopper loyalty card data. "We're tailoring offers directly to shoppers based on their purchase history, which has increased the effectiveness of communications sent out by the marketing department," says Dave Eddy, director of decision support systems for Sobey's, in a case study.

By using loyalty card data, point-of-sale data, information from social media sites and other shopper information, retailers can increase the efficiency of virtually any promotion. It's a challenge, but careful analysis of the data to create personalized promotions can pay off.

"The amount of POS, loyalty card and panel data is immense," says Julie Nelson, senior vice president of the shopper division at TRIS3CT, a independent marketing agency based in Chicago. "Looking at the shopper behavior of the consumer is essential. You want to understand what else the shopper is buying, what else is in that basket, whether they are shopping across different retail channels, what information they are using to decide what they buy, etc. It all helps us better understand shopper behavior and leads to cross selling [and other promotions]."

2.Assortment optimization

It's no secret that shelf allocation is essential to maximizing sales; why else would big CPG companies pay for prime shelf space? Shopper data can play a key role in assortment optimization and product placement, Nelson says.

Shopper data doesn't all come from loyalty cards and POS data, of course. A less common source of shopper data is direct observation of consumer behavior. For example, shopper analytics firm RetailNext sets up cameras in stores to discreetly observe shopper behavior, resulting in data that helps retailers and CPGs create more effective stocking arrangements, promotions, etc.

A three-way collaboration between Syracuse, N.Y.-based Green Hills Farms supermarket, General Mills and RetailNext observed 46,390 shoppers over a three-week period, including 9,756 who wandered down the cereal aisle. It revealed that a special display of General Mills' cereals resulted in 8 percent more shoppers buying the cereal, valuable information that both the CPG and the retailer could use to develop future displays.

"We bring a lot of data sources together to let retailers understand what's driving the behavior in their stores," says Tim Callan, RetailNext's chief marketing officer.

3.Demand forecasting

Out-of-stocks can be a profit killer. If you run out of something a customer wants, not only are you probably losing that particular sale, but you're also creating a dissatisfied customer. Big data can help retailers optimize their stocking situation by providing information about sales patterns.

"By leveraging the analytics of market research, including consumer paths to purchase and key drivers to activation, grocery retailers are informing their decisions with a better understanding of consumer behaviors and motivations," says Tara Armstrong, vice president of strategy and analytics at Realtime Media, Bryn Mawr, Pa.

Now consider the following key ways to make sure you're getting the most from big data investments, regardless of how you apply them:

4.Evaluate the success of your investments

Spending hundreds of thousands of dollars on big data applications might seem to make sense, but if you're not evaluating the success of those applications and appropriately adjusting them, that money might be wasted.

"In our experience, about 20 percent of marketing programs tend to be big winners, driving about 130 percent of the [return on investment]," MarketShare's LaPointe says. "Another 20 percent tend to be big losers, actually costing the retailers money. The rest tend to fall in the middle between being marginally profitable and minor losers."

How do you know where your big data-based promotions fall on that continuum? It's not an exact science, because any promotion can affect multiple areas beyond just immediate sales, including brand recognition, customer loyalty, ancillary purchases, etc.

Nevertheless, attempting to evaluate your promotions is an essential exercise. An evaluation begins with a decision about what to measure, Nelson says. Once a retailer or CPG has identified the success markers, they need to analyze the relevant data to see if the promotion delivered the expected return on investment.

The analytics help retailers understand their marketing results, LaPointe says. "Our analytics help them understand which programs fall into the top group of performers, the bottom or the middle. Then we help retailers understand how to reallocate their marketing investments to get more ROI by dumping the things that are draining profit and expanding the things that are working."

5.Balance the long-term and short-term gains

The most obvious measure of success with any big data-related endeavor is short-term gain. Did the sales tick up? Were stock-outs reduced? Did margins improve? A promotion's effect on long-term customer relationships also should be considered.

"There's a longer-term ROI that takes into account what you might call softer elements of value: increases in brand awareness, consumer shopper loyalty, those kinds of things."

–Julie Nelson,

TRIS3CT

"There's a longer-term ROI that takes into account what you might call softer elements of value: increases in brand awareness, consumer shopper loyalty, those kinds of things."

A one-time price discount will probably lift sales of the item, but how many of the people who buy that item on sale will become regular customers and buy it when it is full price?

"Long-term conversion of consumers to customers is essentially a process of building trust in the retailer's brand promise," notes Venkat Viswanathan, CEO of LatentView, a big data analytics firm based in Princeton, N.J.

Big data holds big promise for retailers and CPG manufacturers, but not every application of big data is worth the investment. Choosing the right applications, measuring the results carefully and considering the long-term effects can increase the odds of success.


"In the recessionary, low-growth economic environment of the past few years, pricing and promotions analysis has provided considerable competitive advantage and better ROI to retailers."

– Venkat Viswanathan,

LatentView

"In the recessionary, low-growth economic environment of the past few years, pricing and promotions analysis has provided considerable competitive advantage and better ROI to retailers," Viswanathan says. "Retailers who had a superior understanding of promotional mix, store clusters, timing of promotions and competitive action, and translated that to designing winning offers, were able to achieve better ROI."

Ed Avis has written for Crain's Chicago Business, the Chicago Tribune, Specialty Coffee Retailer and many other publications.