Customer Data

Learning from Failure: The Upside of Downturn in Big Retail

Customer Data | April 05, 2017

Early 2017 has been eye-popping for big retail, with The Limited filing for Chapter 11 and iconic brands like Macy’s and Sears announcing major store closures. However, within these landmark events, we can find an equally important theme: sometimes the biggest failures in life give way to the most important successes. After all, “Failure is but success in progress,” Albert Einstein once said.

Before we go to the lessons learned, let us reflect briefly on the factors that brought about these downturns. The Wall Street Journal noted The Limited had become “stale.” Fortune points to Sears’ singular focus on self-protection vs. “transforming the company in response to changing times.” And a contributing factor to the Macy’s downturn may have been a dramatic miscalculation of customers reactions to off-price offers.

At the heart of the matter, each of these iconic retailers has struggled to adapt their approach to consumer understanding, engagement and commerce. The surprising disconnect? There’s simply no excuse for a brand to lose touch with its customers like these brands have. Consumers willingly expose their behaviors and preferences every day. Data such as location, wish list information, unchecked shopping carts and shopping history is there for the taking, and it’s not a stretch to say consumers have come to expect retailers to use this information to market to them better, in a highly informed and respectful way.

As such, three marketing tenets rise to top of mind in the aftermath of recent debacles at The Limited, Macy’s and Sears.

Bring Online Convenience to the In-store Experience

Evolving a brand in lockstep with customers’ tastes and needs is necessary for sustainable success. In retail, this is about enhancing the customer experience in a way that builds upon observed behaviors and preferences. In its report, “Making the digital connection: why physical retail stores need a reboot,” Capgemini found that four in 10 shoppers say in-store shopping is a chore, a chore that’s even less appealing than washing the dishes! That’s some fairly damning evidence.

But dig deeper, and the report has findings that reflect more positively: a full 70 percent of respondents say they want to “touch and feel” products before they buy, which indicates that stores still have a significant role in consumers’ lives.

So, how might a retailer reconcile these incongruous findings in a way that makes a brand more memorable?

When we analyze recent mobile trends data, we see that half of all in-store visits are driven by mobile devices. Huge swaths of just about every demographic (teenagers, college students, moms, dads, etc.) now use their mobile devices to learn about products and find a place nearby that sells it. The logical takeaway from these findings is that to remain relevant, retailers really need to up their mobile game. In practice, this means the following:

  • Implement digital loyalty programs that customers can easily manage on their smartphones.
  • Sign customers up to receive text messages from your brand, then use geofencing technology to send instant coupons, promotions and other offers when they’re nearby or in-store (or even in your competitor’s store).
  • Tilt the store environment to have a mobile-first feel, which starts by giving salespeople tablets so they can instantly look up product information, check on inventory levels, place orders and pull up promotional offers.
  • Modernize the checkout experience with mobile payment technologies, which will shorten checkout lines, let people check out anywhere, and generally start to blur the line between online and in-store experiences.

‘Personalization’ as We Know is Evolving

Just as it’s important to find ways to marry current trends and preferences with the in-store culture, it’s also vital to engage customers on the digital marketing side on their terms. In other words, to make marketing programs memorable, it’s about using data to build personalized experiences.

One interesting place to start is to segment customers into layers of transactional, behavioral and customer-interest data. With that you can begin to fuel informed interactions, make cleaner suggestions and actually help customers make buying decisions that are of highest value to them.

For example, consider gourmet coffee retailer Boca Java. The company’s marketing department segmented its customers by how many bags of coffee they ordered. Then, it offered a specific discount to three unique segments: customers who had previously purchased two bags, three bags and four bags. Interestingly, customers in the two-bag segment turned out to be most likely to act on the discount. This unique insight into response likelihood gave Boca Java the means not merely to carry out future upsell opportunities more efficiently, but to do so in a way that matched customers’ perception of value. That is personalization.

Focus, Above All, on Measuring for Loyalty

In the (very) recent past, much of the metrics for a given marketing campaign focused on factors like open rates, clickthroughs and other types of “counting stat” KPIs. These are still important, but there’s a much subtler set of loyalty indicators emerging, which includes:

  • Customer Activation Rate: A measure of the percentage of customers who made a purchase within 60 days of joining a mailing list or signing up for special offers. For example, if you added 100 contacts to your database during the past two months, and 20 of them purchase within the same time frame, you would have a customer activation rate of 20 percent.Early Repeat Rate: A measure of new purchasers who make a subsequent purchase within 60 days of their initial purchase. Following the previous calculation, if 20 customers make purchases within 60 days of signing up, and then five of those new customers make another purchase during the following 60 days, you would have an early repeat rate of 25 percent.
  • Early Repeat Rate: A measure of new purchasers who make a subsequent purchase within 60 days of their initial purchase.Following the previous calculation, if 20 customers make purchases within 60 days of signing up, and then five of those new customers make another purchase during the following 60 days, you would have an early repeat rate of 25 percent.
  • Orders Per Active Customer: A measure of the average monthly order rate for customers who have made two or more purchases while they’re “active” (i.e., making a new action within 60 days of the previous action).

There are many strategies to test for increasing customers’ repeat rates, starting with affinity campaigns that target those customers who have a high likelihood of purchasing specific products, categories or brands. Different tactics may work better — or worse — for a given retailer, but again, the key is to develop a surgical understanding of micro-segments within and across your digital and physical engagement touchpoints. If you can show growth in each of the KPIs called out above, your brand’s personality is probably getting through.

Ultimately, if this series of unfortunate retail events has taught us anything, it’s that loyalty is king. The only foolproof way to maintain relevance in a market as crowded and cutthroat as retail is to make smarter use of data to keep up with what customers want. When you do that, you can inspire loyalty and — dare we say — passion, and stack the deck such that disasters befalling even big retail stalwarts will pass you by.

Paul Mandeville is the chief product officer for QuickPivot, a provider of real-time, omnichannel marketing automation software solutions and services.

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