Working together, retailers and manufacturers can leverage purchase data to improve products, promotions, and services

What do the Oakland Athletics baseball team, Investor's Business Daily (IBD), and your average grocery retailer have in common?

Each has already found and applied—or has the capacity to find and apply—new knowledge about their businesses, and can succeed in environments where their competition appears to possess vastly superior resources.

For the Oakland A's, this takes the form of recognizing inefficiencies in the marketplace for baseball players. They've learned that the market often overlooks and undervalues players who possess the characteristics that are most predictive of the key element in winning ball games: scoring runs. As Michael Lew is showed in his brilliant book Moneyball: The Art of Winning an Unfair Game, the A's have boldly applied their knowledge to confound conventional baseball wisdom, and consistently compete for division titles despite having one of the lowest payrolls in Major League Baseball.

For IBD, the national daily newspaper positioned as an alternative to the venerable Wall Street Journal, it involves using 50 years of data and ongoing daily research to identify and repeatedly highlight stocks that possess the characteristics common to the most successful growth stocks before they make their greatest gains. This innovative financial information draws readers by giving them a set of rules to do the one thing they care about most as investors: choose winning investments. By providing more relevant information for the target audience, they're able to charge more for their product than the competition.

Though very different businesses, the common thread uniting these two examples is the identification and employment of data that is useful in predicting specific and desired outcomes. The imperative to discover and exploit this kind of new knowledge exists no less for retailers of all types, but especially so for grocery and drug store operators. This is because they compete in an industry of famously thin prof it margins, with new channels of competition appearing almost daily.

Card-based marketing initiatives, also known as "frequent shopper" or "loyalty" programs, have long been considered treasure troves of customer behavior, the envy of all marketers who lack such data. Now, faced w it h unrelenting competitive pressure and the omnipresent need to demonstrate return on marketing investment (ROMI), retailers—and by extension, the consumer packaged goods manufacturers who supply them—are increasingly committed to using loyalty data to measure improvements in marketing effectiveness. Their prospects for success as businesses are linked in obvious ways—most notably their desire to please the same customer. A corollary to that linkage is that they can work together on the search.

CONSUMERS INCREASINGLY DEMAND AN ENHANCED SHOPPING EXPERIENCE BASED ON KNOWLEDGE OF THEIR PAST PURCHASES.

The good news is that the card-based programs so many retailers operate do go a long way toward the discovery of new knowledge. They do carry the potential to yield radical insights that improve business performance. The challenge lies in using them wisely, recognizing that the databases themselves are not enough, and in identifying and obtaining the missing pieces that complete the new knowledge puzzle.

Constraints of the past are receding

Retailers who possess frequent shopper data are often criticized by "experts" for underutilizing what they blithely consider an easily leveraged information asset. They say that the programs are operated largely as a "temporary price reduction on a card ." The criticism is of ten self-serving, because effectively incorporating the data into marketing and operations is, in fact, a painstaking and detailed process. Nevertheless, there is validity in the criticism, as well as valid reasons why retailers have been slow to exploit their own data advantage.

First, privacy considerations have led retailers to be cautious in their use of these data as enablers of marketing programs. But times change; today, most consumers know and expect that their data will be "out there" and used. That expectation is rapidly evolving into a demand that it be used to simplify and enhance the customer experience.

Additionally, grocery and drug retailers are operationally focused, not always staffed with trained quantitative analysts with the skill sets required to use the mountains of data generated by these programs effectively. But this situation is changing, as well; recognizing the potential of their purchase data, more retailers are devoting resources to this opportunity. In addition, partnering with companies like Knowledge Networks/PDI, which maintains a national panel of shopper data, can take the analytical burden off the store or chain.

Liberated, then, from some of the past constraints, and armed with the customerdriven imperative of using data to improve product choices and shopping experiences, leveraging the data to enable discovery of "new knowledge" involves a four-step approach. Enacting any one of these can vastly improve insights and efficiencies; together they represent a program for exceptional learning and success.

Add value with a demographic perspective

Retailers can understand their businesses better by segmenting their customers on the basis of spending and applying that learning. For an excellent resource with report examples, see Brian Woolf's 1996 book, Customer Specific Marketing. Retailers need to know whether the 70/30 rule applies to their sales (70 percent of purchases are driven by 30 percent of customers), or is it more like 80/20? Who is it that visits their stores most frequently, and how often is that? Who are their most profitable customers?

ATTITUDINAL DATA CAN REVEAL WHERE THE COMPETITION IS VULNERABLE.

Demographic data enable an even more extensive segmentation than can be done with spending information alone. However, detailed and substantive demographic information is not captured as a matter of routine with frequent shopper programs. This is typically because it represents a cost layer (collecting and refreshing data) on top of the basic program investment.

Therefore, retailers should invest in a third-party demographic overlay to enhance initial, spending-based segmentation work. These two elements of segmentation turn the findings from a simple "database" to "information clusters" with greater depth and usefulness. When the new knowledge is revealed, and the time comes to act on it, understa nding t hat a customer is a Health-Oriented Soccer Mom who spends $50 per week in a given store will inform more decisions than simply knowing that Customer 010001 spends $50 per week.

Finding the "why" behind store choices

While understanding who a retailer's customers are and how much money they spend is crucial, it is incomplete information in the search for "new knowledge." This is because that same customer very likely shops two or three other stores with very similar product offerings.

Because of this, attitudinal information, collected through customer surveys, is essential to uncovering the "why" of top spenders' behavior. Why do they shop in Store X? Is it convenience? Cleanliness? Fresher meat? Lower prices?

Attitudinal data reveals what drives consumers to shop in your store in the first place and, importantly, can provide a view of their total spending, including that which occurs elsewhere. This enables an understanding of whether there is an opportunity for you to gain an even greater share of spending. After all, why devote finite marketing resources against a target that carries no upside—even one that spends heavily today?

If an upside opportunity exists, the attitudinal data can also reveal where the competition is vulnerable, relative to the things that drive this customer's shopping choices. Knowing these vulnerabilities, retailers are in a position to make informed choices about whether and how to spend money against a given customer.

Manufacturers, retailers partner for insight

Consumer packaged goods (CPG) companies play a ke y role i n t he sea rch for new knowledge about the shopping experience— and should always be in the hunt for new ways to understand their consumers. Moreover, they can call on resources that are not readily available to most retailers. Often, they have entire departments whose primary focus is framing an understanding of "the consumer." Yet purchase data can still prov ide new perspectives on their own research efforts—creating an ideal opportunity for partnership between retailers and manufacturers.

One "low-hanging fruit" example of this interdependence lies in the introduction of new items. New, innovative products are the lifeblood of CPG companies; carrying items customers want is a critical success factor at retail. Reducing the new product failure rate is in the interest of all. Testing and measuring new product acceptance, through Trial and Repeat purchasing and comparisons to benchmarks, serves both ends by limiting risk and more rapidly weeding out losers from winners.

It also enables testing elements of a marketing plan and specific in-store activ ities. The results manifest themselves in new knowledge about which in-store marketing levers most effectively and efficiently communicate the "news" about a product to the customers that drive the business.

The fact is that CPG marketing dollars migrate to activities that can be tested, measured, and adapted to learning. Retailers and manufacturers, therefore, have a shared interest in discovering what works on the most granular and actionable level.

Find the metrics that make a difference

Most of the statistics we can derive from customer purchase data, even once the "best customers" are identified, are irrelevant in terms of their ability to predict key outcomes such as Total Spending, or Average Monthly Store Visits, or Retailer X's Share of Customer Y's Total Spending. Similarly, many of the things that will drive a customer to shop in a particular store cannot be affected without spending significant sums of money in the effort. One immutable truth about marketing budgets is that they are not limitless.

The key, therefore, is uncovering the metrics that do have predictive power (i.e., measures that matter), are capable of being affected, and can be acted on in an affordable way. Then, based on the known drivers and your standing among the competition, you can choose among different marketing levers based on your ability to spend as well as your expected return for that investment.

CPG MARKETING DOLLARS MIGRATE TO ACTIVITIES THAT CAN BE TESTED, MEASURED, AND ADAPTED.

Imagine a retailer who knows that about 20 percent of its customer base is driving most of its sales. Through survey research, this chain has determined that many of its top customers claim to spend a lot of money in competitive stores, as well; but they have learned that the competition is vulnerable on the dimensions of "good customer service" and "has sales on items I like." Armed with this knowledge, the retailer could

• hire and train more staff to provide even better service
• drop prices on many items that are popular with top customers

While both of these ideas may prove effective at winning a greater share of total spending by top customers, neither of these alternatives is likely to prove efficient. The former involves increased labor expense, while the latter will put pressure on margins even though it may increase top-line sales.

But alternatives exist. If this retailer has been developing an email database as a marketing tool, this can be used to customize weekly advertisements to customers. Programs that enable electronic customization of an ad that is also running in print are available, and carry the bonus of being able to highlight, by customer, the sale items that history suggests they are interested in buying. This would deliver

• enhanced customer service in the form of personalized notification of sales
• reinforcement of the sale price perception with no need for additional discounts, which are already funded

In addition, this effort benefits manufacturers by ma king their promotion dollars more efficient—and, ultimately, by simply bringing their product to more likely purchasers.

Claiming a marketplace advantage

The combination of card-based marketing databases, relevant analysis, and communication technology makes the discovery and application of new knowledge possible today. The payoff lies in the ability to test and measure each step of the way—and, not incidentally, the fact that some notable retail players lack the databases necessary even to begin the search. Once uncovered, if new knowledge is acted on correctly, there is little the competition can do to counter the effect.

This opportunity also provides a way for manufacturers and retailers to build or deepen a mutually beneficial partnership, because efficiency of retail sales delivers returns to CPG companies in the form of more-streamlined product development and lower promotion costs.

As purchase data becomes more pervasive, and perhaps more detailed, the ways it can be leveraged will only grow—if motivated companies create the programs for claiming this marketplace advantage.

Patrick Millea is Vice President, Client Service, at Knowledge Networks. You can reach him at pmillea@knowledgenetworks.com.

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