With stiff competition and an increasingly connected world, many organizations are finding themselves suddenly focused on customer experience (CX). Customers have more information, more options, ever-growing expectations, and a more powerful platform for expressing their opinions. In short, customer experience is no longer an optional part of corporate strategy.
In our work helping clients turn CX into a competitive advantage, we start by defining their customer experience strategy. That means assessing their current customer experience, mapping customer journeys, defining their targeted future customer experience, and designing individual touchpoints and a holistic customer experience that will make customers and shareholders happy.
And while defining your CX strategy can be quite challenging, it’s the next step – implementing your strategy – that often trips up even the most advanced organizations. In their recent HBR article, Ryan Smith and Luke Williams discuss the many reasons why CX programs fail, noting that failure to collaborate across departments is one of the key reasons why CX transformation efforts come up short.
In our experience, it is often the collaboration between CX leadership and your “data” counterparts that makes or breaks customer experience endeavors. The most successful CX leaders have a data co-pilot helping them translate innovative business strategies into data-powered solutions.
In this three-part series on Data-Driven Customer Experience (CX) Transformation, we outline three ways CX programs can leverage data to transform the customer experience.
First up, let’s talk about creating a single view of the customer.
As we discussed earlier, one of the first things you’ll want to do when embarking on your CX transformation journey is to segment your customers. But before you can do that, you have to figure out who your customers are.
In a subscription-based business model (think cable or utilities), every customer interaction will often be tagged with the account number. Whether it’s a web portal login, a billing phone call, or an in-home technician visit, you’ll be able to tie that activity and its corresponding data back to a single customer.
Why is it so difficult to identify a customer?
But in other industries, figuring out who your customers are is easier said than done.
Consider the retail store that historically has known very little about who is buying their products, other than perhaps some basic info captured in the point of sale system. Several years ago, they launched a website – a golden opportunity to gather more information about their customers during the payment process. Then they added a loyalty program, and now they’ve rolled out a mobile app.
The good news is that all of these platforms are capturing information about their customers: demographic data, purchasing patterns, and loyalty, among others. The bad news is that the company can’t tie together the information from these disparate data sets to inform better decision-making in their CX transformation journey. Is John Doe in the point of sale system the same as John H. Doe in the mobile app? What about J. Doe in the loyalty program?
Answering these questions requires a master data management (MDM) solution – an automated way to match and merge records for a particular domain (in this case, the customer domain) across many systems. “Mastering” the customer data allows the organization to understand each customer and their buying patterns holistically.
Technology is not a silver-bullet for MDM.
No matter which MDM technology you choose (Informatica and Orchestra Networks consistently come out on top in Gartner’s magic quadrant), the key is to define your master data use cases first and then build your technical solution.
If your primary goal is to enable more robust customer analytics, you’ll likely want more attributes tagged on your master record. If, on the other hand, your end goal is to leverage the master record to integrate multiple customer-facing systems, you may choose to focus only on attributes required for identity resolution.
Regardless of your end goal, consider the following six-step methodology for designing and implementing an MDM solution:
- Define Your Master Customer Record
- Identify Your Source Systems
- Profile Your Data
- Standardize, Cleanse, and Load Your Data
- Define Match & Merge and Survivorship Rules
- Create and Use Your Master Records
For a business user or CX champion, MDM may sound like a very technical endeavor. But it’s a necessary investment to enable many of the components of a modern customer experience program: customer segmentation, self-service portals, integrated mobile and web applications, differentiated or “white glove” service, and customer-centric analytics, just to name a few.
Without a single view of the customer, you may be embarking on your customer experience journey without a compass.
In fact, Gartner recently noted that by 2020, 75% of organizations that neglect MDM will “adversely affect CX metrics via the use of inaccurate data during customer interactions.”
But with a clear picture of who your customers are, you’ll be able to segment them into customer types and tailor every interaction based on their unique wants and needs.