RESEARCH & INSIGHTS

Featured Insight

How next-generation capabilities are delivering winning results in the world of personalization

Today’s customers are dissatisfied with the relevance of communications, while retailers are still struggling to show demonstrably improved campaign performance. Is Big Data to blame? Sure, the increased information flow can improve marketing ROI, but it also presents the rather significant challenge of how to build the capabilities to make sense of all that data.

Fortunately, with the power of emerging technologies, neither customers nor marketers have to feel helplessly resigned to the current situation. Today, better analytical approaches and improved technologies are easing the strategic journey toward true one-to-one personalization, helping marketers move past obstacles and seize opportunities for generating sustainable growth and earning customer loyalty.

Download this whitepaper to learn more about an approach that’s more profitable than traditional campaign-based marketing. 

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For many marketers today, the key challenge in collecting customer information is figuring out how to best use it. In the near future, that challenge may change to putting a dollar sign on the data.

Consumer data and similar intangible assets could be worth more than $8 trillion, according to a recent Wall Street Journal story, citing Leonard Nakamura, an economist at the Federal Reserve Bank of Philadelphia. “That’s roughly equivalent to the gross domestic product of Germany, France and Italy combined.”

When those insights start making money, regulators pay attention. The Kroger Co., for example, is estimated to sell $100 million worth of data to suppliers such as Procter & Gamble Co. and Nestlé, according to the report. Sure enough, in September, members of the Financial Accounting Standards Board were advised to research intangible assets again; the third time since 2002.

It is no longer up for debate that customer data is becoming a more valued and tangible asset, as is evidenced in FASB’s repeated review into how to record these elements in financial records. Regulatory agencies are already pointedly asking companies to share their accounting methods regarding reward points and similar currencies. The Securities and Exchange Commission, for example, in the spring asked CVS/pharmacy to explain how it accounts for its outstanding loyalty currency, as it was not detailed in its quarterly report.

(CVS responded that while its ExtraCare expenses are charged to its cost of revenue, it does not believe the liability of its program offerings are material due to their short-term duration.)

When it comes to general data, however, those quantifications get murky. Consider that the value of today’s assets may change markedly in six months as consumer behaviors change, for instance. Further, the cost of time spent collecting and analyzing data would offset that value.

Despite these variables, there are some general guidelines marketers can follow to better prepare for regulatory guidelines when they come, and to understand the value of their data:

• Consider a CDO: Roughly 100 large organizations employ a chief data officer, according to research firm Gartner. Companies that manage large amounts of data will likely be better off in a year if they appoint someone now to manage information use. They also should ensure the position is well integrated with the executive team so everyone knows his or her role.

• Be perseverant: As earlier stated, data is fluid. Today’s best customer may be gone tomorrow, or replaced by another with completely different purchase preferences and behaviors. If a company is serious about tracking the value of its data assets, it needs to do so diligently and flexibly. This requires a regular auditing schedule and accountability. Companies that involve all logical teams in the process will likely fare better in this exercise.

• Reach out: Accounting strength comes in numbers. Merchants that lack the resources to invest in a suite of in-house data analysts have the opportunity to benefit from third-party consultants. Fortunately, several organizations specialize in loyalty marketing and data analysis, including ours.

• Keep future value in mind: Concentrate on efforts to capture only the data the organization needs, recognizing in the process that the data not only is a valuable asset now, but in the future the acquisition, management and maintenance of that data asset may have beneficial accounting implications.

The customer experiences that data insights make possible can be, to quote MasterCard, priceless, but the value it brings to companies is not. Accounting standards are likely just a matter of time, and smart organizations will be ready.


Do bricks and mortar cost more than bytes and channels? For Macy’s Inc., the question may not matter as much as whether the two investments, combined, sell more sweaters, suits and shoes.

Macy’s is willing to pay to find out. The nation’s largest department store chain has distinguished itself over the past few years by testing new technologies, including omnichannel distribution strategies that enable customers to order items straight from the warehouse, as well as in-store iBeacon communications.

It is part of a steadfast effort by Macy’s to be where its customers are. In mid-September, the Cincinnati-based merchant announced a series of additional technological advancements and partnerships, including the testing of same-day product delivery, participation in Apple Pay (learn more about the impact of Apple Pay on the retail industry here), and a snappy image search app that will respond to any digitally submitted photo with a similar item available at Macy’s. It’s pretty sharp stuff.

And it is expensive. Macy’s second-quarter report, filed Sept. 8, details that the cost of sales rose $139 million in the quarter, due in part to higher markdowns “as well as the growth in the omnichannel business and the resultant impact of free shipping.” Likewise, the investments in Macy’s omnichannel strategy partially offset higher income from the company’s credit card operations.

The fact that Macy’s is upping its investment, post report, makes it clear the retailer and its CEO, Terry Lundgren, expect a payoff.

And why shouldn’t it? Macy’s at this point is not only besting its peers in terms of its investment in innovations, but also in terms of risk. By incorporating the ability to order a specific product in a select size and color, at the store, online or by phone, Macy’s has removed many barriers to sale. Added services such as same-day delivery eliminate a lot of the remaining barriers, and it has upped the ante for others.By incorporating the ability to order a specific product in a select size and color, at the store, online or by phone, Macy’s has removed many barriers to sale.

Further, Macy’s early embrace of new technologies, from iBeacon to Apple Pay, indicates the company executives are inside players with many innovators, giving Macy’s a leg up on tomorrow’s trends.

So to me the question is not about the cost of bytes and channels, but the extent to which Macy’s loyalty data is informing these decisions. The company’s Star Rewards program includes a “My Wallet” feature that stores offers and payment options online, as well as an app through which members can manage their accounts and receive Macy’s texts. This translates to lots of brand interactions, yet the program is not mentioned anywhere in Macy’s quarterly report and gets only a brief description in its annual report.

It’s a notable omission, but despite it, Macy’s clearly must be using its program data to support these initiatives. I can only imagine how customer data could help shape the offers it provides to customers and the way it prioritizes its investments in new technologies. Evidence of its potential already exists in its performance: Macy’s posted second-quarter sales of $6.2 billion, up $200 million from the year before.

That’s a lot of sweaters, no matter how they are purchased.

Watch a discussion I had recently with the Business News Network on the importance of Right Data vs. Big Data here.