Once upon a time, customer service and support operations were viewed as the “complaint department” – a back-office function, a necessary evil, and above all a cost center whose role should be reduced as much as possible. These days, it has become increasingly clear that businesses must prioritize data quality. As Thomas Redman advised is a recent guest post, “Getting in front on data quality presents a terrific opportunity to improve business performance.”
While some organizations still have a break/fix mentality about customer support, the very best organizations now view their customer contact operations as the strategic voice of the customer – and leverage customer engagement as a strategic asset. Thanks to tools ranging from CRM and social media, many businesses manage their customer experience as closely as they manage their products and services.
The Strategic Role of Data Quality
This leads us to an important analogy about data quality. Like the “complaint department” days of customer service, many organizations still view data quality as little more than catching and fixing bad contact data. In reality, our experience with a base of nearly 2500 customers has taught that data quality plays a very strategic role in areas like cost control, marketing reach, and brand reputation in the marketplace.
This worldview is still evolving slowly. For example, according to a 2017 CIO survey by Talend, data quality and data governance remain the biggest concerns of IT departments, at 33 and 37 percent respectively – and yet their top priorities reflect more trendy objectives such as big data and real-time analytics. And back in 2012 Forrester vice president Kate Leggett observed that data quality often remains the domain of the IT department, and data projects for customer service rarely get funded.
Meanwhile, data quality has also become an important component of customer experience. Leggett notes that instead of an IT-driven process of “cleaning dirty customer data,” organizations should reframe the conversation towards the impact of data quality on customer-facing functions, and understand the connection between investments in data quality and customer service metrics.
Here at Service Objects, we see three key areas in the link between data quality and customer experience:
Customer Engagement
When you have good data integrated with effective CRM, you have the ability to market appropriately and serve customers responsively. You can target your messages to the right people, react responsively in real time to customer needs, and create systems that satisfy and delight the people you serve.
Service Failures
Mis-deliver a package because of a bad address, and you make a customer very unhappy. Do things like this even a small percentage of the time, and you gain a reputation as a company that doesn’t execute. Keep doing it and even many customers who haven’t been wronged yet will seek other options where possible, because of the “herd mentality” that builds around those who do complain publicly and on social media.
Strategic Visibility
Your customer data is an important asset that gives you the ability to analyze numerous aspects of your customer relationships and react appropriately. It holds the knowledge of everything from demographics to purchasing patterns, as well as their direct feedback through service and support. Having accurate customer data is central to leveraging this data strategically.
One heartening trend is that more organizations than ever now see the connection between data quality and their customer relationships. For example, one 2017 article in PharmExec.com cited a European customer data survey showing that nearly three-quarters of life sciences respondents feel that having a complete and real-time view of customers is a top priority – while only 40% are satisfied with how well they are doing this. We are seeing similar figures across other industries nowadays, and view this as a good sign that we are moving over time towards a smoother, more data-driven relationship between organizations and their customers.
