Give Them What They Want

You've collected data to learn who your customers are and what they want. Now it's time to leverage those data to deliver the right store brand solutions.

Many of today's leading retailers are known for managing their world-class store brand programs with the gusto of a true brand. To do so, they rely on sophisticated consumer data to make decisions regarding product development, tiering, pricing, packaging and promotion.

And although a retailer might have perfected its data-gathering methods, analyzing and leveraging the data often present a challenge.

"There is simply too much data collected for anyone to 'sift through' meaningfully," says Jim Hertel, managing partner with Barrington, Ill.-based Willard Bishop. "We meet so many people who have access to tons of data but don't have tools and approaches to organize [and] create insight. The result is 'analysis paralysis,' frustration and suboptimal decision-making."

Size matters

According to Mike Kowalczyk, vice president and general manager of Valassis In-Store, Livonia, Mich., smaller regional retailers actually have an advantage when it comes to analyzing and leveraging data.

"They're typically quicker; they're a little bit more nimble; their trading areas look much more like each other than unlike each other, so they have that inherent 'advantage' by being small and lean," he says. "Whether you're talking about H-E-B or Winn-Dixie or A&P, those retailers — because of the operating environment that they're in — can use that data to not only to respond quickly to competitive threats, but also ... to spot opportunities."

For example, smaller retailers generally are not able to source products in the vast volumes larger retailers do, so they might not be able to secure the lowest price on a store brand product. But Adam Holyk, vice president, client solutions at Cincinnatti-based dunnhumbyUSA, points out that a smaller retailer can leverage data to refine price strategy.

"There have been case studies in that space, where by understanding who your price-sensitive customers are in your store and understanding the products those price-sensitive customers buy, you could then tailor your margin investments and promotional discounts into only those products," he says.

On the other hand, larger retailers operating in multiple regions could use data to avoid trying to be everything to everyone, Kowalczyk points out.

"The old saying is, 'All politics are local,'" he says, "and one size should not fit all."

Different demographics might place different demands on a retailer's store brand program; therefore, a large retailer shouldn't simply take the "average" of what customers across all regions of operation want — it will want to divide data up by region instead.

"What do they say? 'If I have one foot in boiling water and one foot in freezing water, the average is pretty good,'" Kowalczyk adds. "These retailers who are aggregating that data at the national level [might get] a misleading perspective of what the market is really looking like."

Another advantage larger retailers have, Kowalczyk says, is the ability to drive scale. A larger retailer could promote its store brand goods by day part — guided by data, of course — and profit greatly. Kowalczyk says Dallas-based 7-Eleven employs such a strategy.

"They know people are really clamoring for breakfast sandwiches between 7:00 and 8:30, and at 9:00, they might change that out to a temporary display," Kowalczyk explains. "That drives tremendous scale with nuggets of information like that — being able to capitalize on that type of insight across thousands of stores versus dozens can result in millions of dollars of profit … to the bottom line."

Should it stay or should it go?

Regardless of size, retailers could use data for many other store brand purposes, says Mike Blyth, president of Groupe Aeroplan's LMG Insight & Communication North America division, Montreal. They could use such information to inform SKU or brand rationalization, for example, which reduces clutter, improves a section's shopability and opens up room for SKUs that possess a higher return opportunity. Time for reviewing categories and tiers should be set aside on a regular basis.

"Creating a set schedule for category reviews makes sense and provides discipline," Stern says.

Holyk agrees, adding that data reveal not only which products should be cut, but also which products should be introduced, readying retailers to meet consumer demand as the popularity of a certain category or tier begins to grow.

"When you think about private label, there are clear opportunities within customer data to drive that type of business," he says. "And there are opportunities in the data to identify where customers have a new product need and a want that the branded products are not fulfilling."

As examples, Holyk points to a couple of retailers that have unveiled own-brand products in response to found consumer needs. He notes that UK retailer Tesco originally launched its Healthy Living line to fill a health-minded niche that wasn't being met by the national brands. And Kroger brought out a Hispanic range of products a couple years back to respond to its growing base of Hispanic customers.

Blyth believes data also could help retailers put together more-effective circulars. By knowing what their most popular store brand SKUs are — and what other SKUs customers generally throw into the basket when buying them — retailers could better determine which items to feature on the front page and which ones to pair in promotions throughout the pages. During online shopping sessions, retailers also could use this information to provide pairing suggestions when a product is viewed — much like Amazon.com does with its "Frequently Bought Together" promotions that put a few products together in a specially priced bundle.

Getting social

Speaking of online operations, some retailers have had success leveraging insights gathered from social media activities. For example, Fresh & Easy Neighborhood Market, El Segundo, Calif., which merchandises mostly store brand products, mines a lot of information from what its customers say about its products on Twitter and Facebook, particularly when it comes to the retailer's store brands.

"Sites like Facebook and Twitter allow us to have direct conversations with customers about our products and our offerings," says Brendan Wonnacott, spokesperson for Fresh & Easy. "We've been able to closely monitor feedback on what we have in our stores, tailoring and adding offer[ings] based off what we hear."

Wonnacott says the retailer expanded several product ranges based on the feedback garnered from social media, adding "suggested favorites" to the mix. The retailer also listens through social media to figure out where it needs to rethink specific private brands.

"For example, we've brought back a number of discontinued products after hearing from customers online that they wanted them back," Wonnacott adds.

But in the end, a retailer must make sure the information is being used to serve the needs of the right customers — it cannot expect to satisfy every single customer. This is especially true when it comes to tiering, explains Brian Ross, president of Toronto-based Precima. He says retailers should introduce a tiering system only if the need is there and the structure can be supported.

'Sites like Facebook and Twitter allow us to have direct conversations with customers about our products and our offerings.'