Brick-and-mortar retail stores have always tried to make customer context work. That’s why grocery stores put candles next to cake mix and why clothing stores make sure socks aren’t far from the shoe department.
Customer context is a bit different in e-commerce, but it’s essentially the same: instead of endcaps or specific aisle layouts, you’ll see “You May Also Like…” or other sections trying to convince you to buy more.
These recommendations are typically based on data gleaned from past customer interactions. E-commerce marketers do their best to predict what shoppers will do next, and they use those predictions to figure out what to show them at what time.
However, there’s really only so much predicting marketers can do. Even with analytics suites, click tracking, and customer surveys, they can’t ever really know exactly what a customer is going to do next every time. It’s easy enough to make inferences and spot trends, but short of precognition, it’s impossible to predict exactly when someone will buy, for instance, Band-Aids and grout.
According to the theory of customer context, the important thing to focus on isn’t when your customer is going to buy something next, nor is it even why she’s buying what she’s buying. What’s important is far more simple: give her the best experience possible, no matter how she shops.
The Basics of Customer Context
An Example
Glen Hartman, managing director of Accenture Interactive, paints a brilliant picture of how much of an impact customer context makes—even if, by traditional standards, it’s not an ideal session for the store:
“Emma runs in one Tuesday—her daughter’s sick and she needs some essentials. Today her goal is to get in and out as quickly as possible. If the store knew that her context was different, instead of coupons it could send her phone a store map to help her find the nonstandard items she needs, then enable her to auto-pay without waiting in line. This experience breaks every rule in the grocery store’s book; it would be classified as a failed trip on all of its metrics. Yet Emma would likely tell everyone she knows about that empathetic experience, and shop nowhere else.”
How it’s Helpful
Customer context in a nutshell? Your business’s goals aren’t what’s important—your customers’ goals are what truly matter. After all, when you help a customer achieve his or her goals, they’re more likely to either come back to you or recommend you to someone else (or, ideally, both).
That’s not to say that you shouldn’t try to make your business successful! All it means is that instead of focusing solely on traditional business goals—such as gaining new customers and increasing consumer spending—companies should instead focus on retaining happy customers and creating brand loyalty through great experiences.
According to the Boston Consulting Group, improving customer experience benefits business performance: “…brands that create personalized experiences by integrating advanced digital technologies and proprietary data for customers are seeing revenue increase by 6% to 10%, according to our research—two to three times faster than those that don’t.”
Make Customer Data Work for You
You’re already collecting data on your customers, no matter what your business. But all of that info isn’t much use if you don’t know what to do with it. And according to Carlton Doty, VP of Emerging Technology Research at Forrester, a business’s “ability to stitch together a customer’s identity across fragmented channels and sessions lies at the core of contextual marketing.”
So what is a stumped marketer to do?
Analyze It (with a Human Touch)
It’s not enough to simply hoard every piece of data you can. The Boston Consulting Group recommends “an approach that is data-driven, consumer-centric—and grounded in everyday customer experiences.”
When you’re looking at the data you’ve collected, consider looking at it in multiple ways. For example:
Customer #6549 just shopped with you for the first time, buying a black dress and black shoes. Is she…
- …likely to return and buy even more black clothes because she looks great in black? Or, is she…
- …preparing for a funeral—meaning she’s unlikely to shop with you again until she has another event she needs to dress appropriately for?
The correct context for Customer #6549’s shopping trip will have to be determined—and based on that knowledge, you will have to decide how to treat her when she returns. Since algorithms aren’t likely to take funerals into account, humans are often necessary to be a part of this process.
If she just loves black clothes, great! Send her follow-up emails recommending the best black outfits you have to offer. On the other hand, if she’s mourning a dead relative, it may not be the best idea to bombard her with emails insisting she come back to see what’s new.
The bottom line? As long as her experience with you was great, she’s more likely to come back—regardless of her state of mind while she was shopping. Your job, from a customer-centric view, is to figure out what exactly “great” means in each different circumstance.
Organize It (with the Help of Technology)
Obviously, it’ll be rare for you to need to analyze a single customer’s context—it’s much more likely that you’ll be collecting data in very large amounts. But how can you possibly sort through it all?
One solution to parsing often-confusing sets of data is a customer data platform, or CDP.
“A CDP is a living, breathing agile source of structured and unstructured data from across channels and devices,” explains Aaron Brennan, a senior product marketing manager at Redpoint Global. “It’s the golden record; the fuel that drives customer engagement and decisioning. Marketers can use a CDP to help understand customers and deliver compelling, contextually relevant experiences.”
The more platforms you have for tracking customer interactions, the messier data can get: “62% of companies have 6 to 20 engagement systems—all with their own set of business rules, data processes, and system of records designed for those processes,” says Brennan. “The more engagement systems, the greater the proliferation of data. What’s lacking is an enterprise view of the customer.”
By integrating several data-collecting channels into one CDP, marketers can more easily access and interpret all the complex info they’re getting from their customers’ habits. Even better, monitoring several points of interaction can go from a multiple-person job to something even just one person could handle—making it that much easier for account executives to monitor and present data as needed.
Implement it ASAP (with the Power of Big Data)
There’s no time to waste! All of that valuable data needs to be used as quickly as possible for it to be as useful as possible.
“Without real-time data, information provided internally and externally is out-of-date and risks being inaccurate and out of context,” says Ken Morris of BRP Consulting. When data is up to date, he writes, it’s easier—and more effective—to “offer customer intimacy and enhanced services like…personalized offers that are relevant to the individual customer.”
In other words, using the info you got from a customer months ago may not help you much if you try to use it today. Using big data technologies to ensure your data is time-relevant will make a big impact—and prevent you from being left behind as your customer generates more and more data you’ll have to sift through.
“Traditional analytics processes that rely on sampling at-rest data from marketing or customer databases will not deliver insights to fuel contextual marketing,” says Doty on managing floods of data. “Instead, focus on using big data technologies and data science approaches to wrangle in-motion data and compress the data-to-insight process.”
Customer Context and Your Business
Now that you know all of the ways customer context can benefit your business, it’s time to make it work for you. Contact Kirkpatrick Creative today and we can start developing a plan.