The first steps of overhauling and cleansing a customer database include adopting contact data quality software and encouraging employees to realize the importance of managing and governing the records.

However, as Dylan Jones notes on the Data Roundtable, it's also vital to periodically check in on the project and assess whether the efforts are making a difference. In order to do that, it's necessary to determine what state the data was in prior to the initiative and measure the current condition of the system against the company's ultimate goals.

"Whilst it's easy to show the before and after impact on data quality, it’s often much harder to demonstrate the impact on service quality, revenue, profit, customer satisfaction, lead times and any number of strategic drivers that matter to executive management," Jones writes.

He suggests using the data quality split testing technique, in which the company distributes its data quality attempts across a product line or specific service. Doing so allows the company to create test and control groups, simplifying the analysis process. Companies will be able to assess the impact on product delivery times, customer complaints, lead times and many other business factors, Jones says.