The holiday season is behind us. That means retailers almost certainly have a pile of fresh consumer digital data. Now is a good time to set a plan to use it. While there are plenty of short-term measures to boost sales, winning companies use their digital data to build customer equity.
If you aren’t familiar with the term customer equity, be certain that your CEO is. Customer equity is the total lifetime value from all current and future customers,and it has surpassed brand equity as the most important factor in a company’s valuation, according to research published in Harvard Business Review. Using digital data to increase customer lifetime value (CLV) is called customer centricity. Becoming customer centric isn’t magic—it’s a very specific journey that retailers can follow to get results.
Customer centricity requires companies to stop shooting from the hip and shift to a culture of data. It means building a better customer experience by learning what each customer is doing, where she wants to go, what she wants to buy, and how and when she wants to buy. Here are three steps you can take to get in the game.
Step one: Set your data to listen to your customers
Where is your data? Chances are, it’s siloed in buckets across the organization. If that’s the case, then what you hear from the customer is like a mobile call with a bad connection. When your customer says, “Can you hear me now?” you should be able to answer, “Yes!” But, if you have fractured data, you cannot hear what your customer is trying to tell you.
If your company is set to pull that data out of individual siloes into a data lake, you’ll need to line up your information technology team to help. But don’t put it all in their hands. The marketing team needs to answer a crucial question: What actions will you take with this data? Companies can use customer data to focus on personalization, to sharpen marketing skills or to support a whole range of initiatives. Retailers must plan what they need in order to take action on the data when they design and build a data lake. Again, this foundation is extremely important because this is where you capture customer listening signals. Take the time to plan your data lake up front, otherwise you’ll spend triple or quadruple as much time retracing steps.
Step two: Use data to achieve customer-friendly goals
Customer-friendly goals seek to reduce friction by creating a smoother experience, not just increasing click-through rates. If your company is focused on personalization, map out what you need to make it happen. How many people do you need on your team, and what skills do they require? Do you plan to democratize data or tie it to a variety of automated systems? Who will work with the data? What tools do you need? Cloud-based computing tools make it a lot easier to build a data framework, but retailers still need to identify all of their resources.
A typical system would include digital behavioral data, transactional data, customer identification and enrichment records, targeted marketing performance and broader marketing touch points. This can be further enhanced with customer feedback, call center and chat transcripts, and returns information.
Some customer-friendly goals include: call center offset, which is when a shopper can use the website rather than call a help desk when she has a question or an issue, reducing call center costs; look-to-book ratios, which measure how many people are browsing versus transacting; and mobile task completion rates, which measure how quickly and easily mobile customers can get to what they need.
Step three: Use data to please customers even more
If you don’t trust your data, you’re not alone. A common estimate is that 80% of a data scientist’s job is cleaning data to make it usable. The first step to clarity comes when you get a handle on the reliability of your information. No one will take action on your initiatives until they trust your data. It’s hard enough to get people to go along with new initiatives even when the numbers are clear.
Connecting data dots is another step along the journey to customer centricity. A lot of digital data is anonymous until a shopper makes a purchase, which is often when a retailer can first identify a specific customer. Much of the work in customer centricity is understanding how to pin anonymous information to a specific customer, even when they’re not authenticated by something as definitive as a purchase. This step is critical and, luckily, there are many ways to do this and tools to help.
The more you can know and understand each customer, the more you can create the relationships that build customer equity. That enables you to move from making decisions about “our customers” in aggregate to making decisions about “this customer” specifically.
Often the most valuable customers interact with retailers frequently. Use your data to anticipate their needs in the same way that you might anticipate their revenue. When you are “of service” to the customer and create frictionless processes you may find that revenue naturally increases. Quality data used well will keep you a step ahead.
Think this is not important for your customer base? Just wait. Younger shoppers expect personalized recommendations, according to a recent survey by AllianceData. And 60% of shoppers under the age of 50 said personalized recommendations are important.
If all of this sounds like an overwhelming challenge, consider where you are today. Without a plan, a reliable source of all data, and a method for building meaningful customer interactions, you’re stuck with the scraps of your market. Instead, opt to invest in building capabilities that will provide long-term gains and a competitive advantage. Your competitors are already on it.
If you make it your goal to beat the e-commerce average—with a focus on customer centricity to build customer equity—you’ll be ahead of the pack before you know it.
Allison Hartsoe is CEO of Ambition Data, a consultancy focused on customer-centric transformation, the host of the Customer Equity Accelerator podcast and the founder of the Customer Centricity Conference.