Knowing Your Customers Starts with Knowing Who They Are

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Click to learn more about author Graeme Thompson.

It’s almost a cliché to say competitive pricing isn’t enough to please today’s customer. You already know they want value for their money. You know they expect a great experience. And you know that to deliver it, you need to build products and services around them. But many companies fail at delivering that great experience because they don’t actually know who the enterprise customer is or what the customer considers to be a great end-to-end experience.

For example, sales could define your customers as entities that have bought a product or service from you in the last 24 months, but finance could define them as anyone with a maintenance contract, even if their last purchase was 10 years ago. Both departments have the same data, but they have different goals for it, and neither one has the data to tell you how many (or which) products the customer has bought.

Then there are the multiple core technologies where various pieces of customer data live that help different parts of the business run smoothly, plus front- and back-end systems like e-commerce platforms, customer service, point-of-sale, and warehouse management solutions. If they aren’t all talking to each other, it’s a good bet the processes are disconnected as well, and the resulting data is often inconsistent, unreliable, and siloed. 

When a company with three departments has bought three different products from you over the last five years, and is defined in one system as a current customer and in another as three former customers, how can anyone understand how many customers they have or their total worth to the business? 

That’s where Master Data Management (MDM) for customers can help. An MDM system serves as a central hub that cleanses, de-duplicates, and synchronizes your customer (or other) data across the enterprise. MDM systems take in information from the existing databases throughout your infrastructure to create a golden record of customer data, a key that ties the systems together into a picture of your entire customer universe – which drives additional value in your existing systems.

We had a customer data master in place, but we were facing a more subtle problem: changes in leadership resulting in new priorities. As many CIOs know, it’s easier for people outside IT to complain about poor data quality than to commit time and resources to solve it given conflicting priorities. So ensuring data quality in customer MDM became IT’s responsibility.

Then a data-savvy new CFO wanted automated reports and a new CRO changed the sales strategy, and voila! Data quality and governance were once again an enterprise-level problem, with everyone inside and outside IT motivated to help solve it.

With this experience came some valuable lessons:

  • Executive sponsorship matters to value-creation: If the CFO had not prioritized data quality, maintenance, and governance as an enterprise-level initiative, and defined the baseline for what is/is not a customer, IT still would be prescribing medicine to patients who didn’t think they were sick.
  • 100% automation is a myth: When we tried to automate everything, we learned that a few incorrectly auto-matched records could snowball into a giant hairy mess. It’s like when you don’t train Pandora when it starts to wander off the path and the next thing you know, your Led Zeppelin station is playing Yanni.
  • You’re only as good as your worst data: Your team members must be interested in the details and willing to do the hard work necessary to realize the value in those details. You cannot achieve a customer data master that drives seamless and memorable customer experiences from 30,000 feet. Digging into the details, finding the corner cases, and putting processes in place will stop the snowball effect. 
  • Consistency is everything: Just as you can’t fight cavities and gum disease without brushing and flossing every day, you have to stay on top of the quality of your data in a consistent way or the customer master data you worked so hard to establish will rot. One of our most strategic assets is our full-time data steward, who reviews exceptions daily, finds patterns, makes improvements, and collaborates with partners like D&B to find better ways of attaching reference data for the best insights possible. We have also standardized on five core exception reports and instituted weekly CFO progress reports because it’s hard to stay motivated when the horizon doesn’t get any closer.
  • There’s no such thing as over-communicating: We are lucky enough to have people who really care about the success of the company. However, because we did not communicate across the enterprise on a regular basis, people who didn’t know we had a customer data master spun up redundant projects thinking they were helping. When new, influential people join the company, we take the time to sit down with them and explain our customer data master goals, business impact, the progress made to date, and their role in achieving those goals.

Simple Advice for a Complex Issue

This is a complex challenge that can impact every aspect of your business in some way. Here’s my advice to my fellow CIOs and technology leaders blazing the MDM trail:

  1. Make sure the patient understands they are sick. Be very clear on the business problem you’re trying to solve and have solid use cases.
  2. Do not pick the most difficult problem first. Build trust and momentum with a problem you can break down into solvable chunks. Then you’ll have the right rig for the big fish.
  3. Find an executive to push prioritization enterprise-wide to ensure everyone buys into the goals and commits the corresponding resources for the hard work.
  4. Have a way to measure your progress. Just like when you’re on a long flight and you pull up the map to see how much closer you are to your destination you need proof that you’re getting closer to your goal to keep everyone motivated.
  5. The enterprise, not IT, must own the outcome. If the enterprise thinks this is simply an IT project, each operations team will use their own solutions to create their own “customer” view of the world and mistakenly blame IT for bad data when comparing customer data across their enterprise. While it’s not their job to have a deep understanding of “the how,” it is their job to own “the what.”

I often say that MDM is the right data, to the right person, at the right time. MDM is the genius that simplifies something as complex as having terabytes of data across multiple systems.

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