[McKinsey] Marketing’s Holy Grail: Digital personalization at scale

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On this subject, here is an article about the future of marketing: Personalization drives growth. But to scale it, companies need to do four things.

Customers decide very quickly—in a matter of seconds—whether they like your marketing message. Provide something relevant and you’ve got a satisfied customer. Miss the mark, however, and they’re gone.

This issue of relevance in our era of instant gratification is particularly pronounced because consumers are bombarded with messages, most of which are off target. Personalization—the tailoring of messages or offers to individuals based on their actual behavior—promises to address this issue.

While many companies have been able to personalize with a few product lines or segments, most still struggle to scale across all the ways they engage with customers. And although technology has an important role to play, in our experience, most companies already have plenty of tools. The real challenge is to transform the marketing organization’s processes and practices to achieve the full potential of personalization.

Done right, personalization enhances customers’ lives and increases engagement and loyalty by delivering messages that are tuned to and even anticipate what customers really want. These benefits to the customer translate into benefits for the company as well. Personalization can reduce acquisition costs by as much as 50 percent, lift revenues by 5 to 15 percent, and increase the efficiency of marketing spend by 10 to 30 percent.2 2. Matt Ariker, Jason Heller, Alejandro Diaz, and Jesko Perrey, “How marketers can personalize at scale,” Harvard Business Review, November 23, 2015.

Through more than a hundred engagements over the past five years, we’ve found four steps that lead to successful digital personalization at scale:

Step 1: Take a journey lens: Use behavioral data to find where the value is

The foundation of personalization is acting on behavioral data. The first step is to group customers with similar behaviors and needs. For example, mothers who exclusively shop a brand for their children or fashion-conscious young women who buy new private-label styles. Most companies find it useful to start with eight to ten such behaviorally based segments as a first step in their evolution to 1:1 marketing.

The next task is to understand, for each segment, the customer journey3 3. David Court, Dave Elzinga, Susan Mulder, and Ole Jørgen Vetvik, “The consumer decision journey,” McKinsey Quarterly, June 2009, McKinsey.com; David C. Edelman and Marc Singer, “Competing on customer journeys,” Harvard Business Review, November 2015. —the series of interactions with a brand from initial consideration, to purchase and use, and then to subsequent purchases. Marketers can do this by integrating information from internal sources such as visits to the company website, purchases at a store, or calls to the contact center, with information that can be acquired from external sources, such as prospects’ visits to a competitor’s website.

Combining these segments and customer journeys creates hundreds if not thousands of “microsegments,” which form the basis of 1:1 personalization. Not all microsegments are created equal, of course. The potential of each must be evaluated and prioritized carefully, based on relative value. For example, a leading retailer we worked with determined that it is more valuable to engage its customers within their “resupply” window—e.g., by reminding them they may be running out of toothpaste and their favorite brand has a limited-time offer—than by pushing them to go deeper in the category by suggesting other oral-care products such as mouthwash or teeth whiteners.

Step 2: Listen and respond: Plan in advance to react quickly to customer signals

Personalized marketing is a two-way street: The customer provides signals—information about his or her needs and intentions—through activities like purchases, online browsing, and social media posts. The company responds to the signal with a relevant and timely message, which we call a trigger, that is sent to the individual customer.

Doing this effectively requires careful advance planning. The marketing team needs to develop a library of trigger messages matched to individual signals.

Trigger messages can be of different types—images, copy, titles, offers—that can be combined dynamically to match the situation.

Coming up with trigger events involves creative problem solving grounded in sound analytics. For example, a next-product-to-buy algorithm based on machine learning could send a message suggesting a set of related products triggered when mothers have clicked on a different product but not bought it (see sidebar, “How personalization that works creates value for customers”).

For all the preparation, getting the full value from triggers requires a test-and-learn process: sending an initial message, evaluating the results, altering the trigger, and measuring the results again. It typically takes four to five attempts to refine a personalized trigger to capture 80 percent of its potential value. For example, a leading apparel retailer we worked with went through four different iterations of a next-product-to-buy email until it found the winning formula, which ended up yielding twice the impact of the first iteration. Additional refinement after that usually yielded diminishing returns.

These sorts of personalized triggers have been shown to be three to four times more effective than blast messages. They can also introduce the customer to new products and new modes of interaction (such as buying online versus in store) that are more convenient, further enhancing their experience.

Once a signal and associated trigger have been shown to be valid and refined, it becomes a business rule, and all future customers associated with the signal automatically receive the appropriate trigger message.

Step 3: Build the war room: Empower a small group of the right people

Going from the traditional marketing calendar to personalized triggers sent in response to individual customer’s signals means shifting to a radically different way of working. This is where we see many organizations get stuck. The secret to kick-starting this change is to empower a small group of the right people. To quote cultural anthropologist Margaret Mead: “Never doubt that a small group of thoughtful, committed citizens can change the world; indeed, it’s the only thing that ever has.” The same can be said of your company.

We call these small groups “war-room teams.” They are staffed with 8–15 carefully selected people, including a campaign manager and staff from creative, digital media, analytics, operations, and IT. A medium-sized e-commerce company might need just one such team; we have seen large organizations with as many as eight teams like this working at once. To be successful, the war-room teams need executive sponsorship at the very top of the organization to remove roadblocks and empower them to get things done, often through creative workarounds.

This is not a task force where people come together a few hours a week while staying in their prior jobs; the team members must be dedicated full-time to the war room. Their job is to drive business results—not merely clickthroughs or page views, but a materially better customer experience and actual dollars. At a wireless carrier, for example, the objective might be lower churn for multiline households; at a retailer, increased follow-on sales to new customers in their first 90 days by introducing them to more-convenient online purchases or products they did not know about.

A war-room team does this by day-in and day-out searching for the signals with the highest potential value and developing, launching, and iterating on personalized messages that get results. At the start of a personalization program, each team should launch one to two new triggers per week. As they gain experience, they should be launching one to two new triggers per day.

Step 4: Rewire and hardwire: Focus on the processes and technology that really help teams work faster

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