Marketing trends come and go, but the actions that foster brand loyalty stay the same. Here's how one brand has cultivated customer devotion for 155 years.
There isn't a company out there that doesn't have some sense of "customer-centricity," but few brands have analyzed what it really means to put customers at the center of all decisions.
Marketers know that they need information -- and lots of it -- in order to tailor advertising efforts to customers. The problem is that there is so much data out there that it becomes a challenge to discern what should inform their strategy.
This is precisely the challenge that Macy's faced as it shifted focus from products to customers. For the past 30 years, Macy's has used point of sales systems to deliver key insights into the types of products it sells, quantity of sales, and margins. "[The problem is that] we've become so product centric -- because of the data that was being supplied by our point of sales systems -- that we somehow lost sight of the customer," said Julie Bernard, group VP of marketing and advertising for Macy's Inc., during her keynote address at the iMedia Brand Summit in Amelia Island, Fla.
"For us at Macy's -- what we've been trying to do for the last four or five years -- is to elevate beyond the rhetoric, beyond the tagline, and say, 'What are we really doing here? What does it mean to put the customer at the center of all decisions?'" Bernard said.
In order to do this, Bernard and her team decided to embark on the following "customer-centric journey."
First, in order to streamline all marketing processes, Bernard insisted upon unifying "customer language" across the company to distinguish the differences between practical spenders, loyal shoppers, and other terms used to identify consumers.
Then, it was time to break down the data.
The Macy's database includes 33 million active households and more than 500 million transactions per year. Of those 500 million transactions, seven out of 10 can be matched to a unique user. Given the overwhelming amount customer data, Bernard decided that it was best to focus on where the information was coming from -- loyal brand followers.
Bernard began to think of the consumer pool as a pyramid. At the base, the largest amount of effort is put into retaining and growing loyal customers. These customers are easy to cater to because Macy's has retained their purchase habits. These are not the folks who spend the most money at Macy's, but rather the loyal customers who come back time and time again. In fact, Bernard said that her real "aha!" moment came when she discovered that dollars spent have absolutely no correlation to retention.
Bernard went on to explain that loyalty stems from emotional and rational connections. Given this information, Macy's has set out to deliver a "thank you" back to the customer. This might come in the form of a free manicure, coffee, or lunch with no strings attached. Or it might be a coupon that extends an offer on products that the loyal customer loves.
"We come up with a pool of offers, and all these offers are scored," Bernard said.
On the second, smaller tier of the pyramid, Bernard placed the "non-loyals," or occasional shoppers. These shoppers inevitably see how loyal customers are treated and convert to "loyals" when they see the perks of brand loyalty.
These customers, just like the "loyals," benefit from personalization. "Personalization is not 'Dear Julie,'" Bernard said. In other words, offer up custom recommendations based on data analysis and deliver it at every decision moment.
The third and final tier of the pyramid represents the effort to convert non-purchasers. This is where Macy's exerts the least marketing effort.
Stick with it. Marketers must have the perseverance to make changes stick.
Resource expertise and learning curves. Hire more thinkers who actually analyze the data and draw conclusions from it.
Work flow and processes. Streamline processes so there are no hiccups.
Costs. Break down all real and perceived costs.
Speed to positive sales results. You're here to run a business. Get far enough in your data analysis to get insight, and go for it. According to Bernard, "80 percent is good enough. Don't wait for 100 percent [certainty]."
And above all, remember to keep the balance between art and science.
Jennifer Marlo is associate editor of iMedia Connection.
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