The opinions expressed here are those of the authors. They do not necessarily reflect the views or positions of UK Finance or its members.

An important way to drive growth is by ‘spring cleaning’ customer databases. This way personalisation is improved with customer communications, which drives efficiencies, enhances the customer experience, boosting revenue, while at the same time reducing churn. Also, additional attention on cleaning ensures best practice regulatory compliance, reducing the opportunity for fraud. 

Data cleaning should take place on an ongoing basis. Not once a year. Particularly, as according to Gartner, data decays on average at three per cent a month and roughly 25 per cent a year, as people move home, divorce or pass away. With data continually degrading it’s essential to have data cleaning processes in place, not only at the onboarding stage, but to clean held data in batch. 

How to effectively clean customer databases

To collect accurate customer data at the onboarding stage it’s best to use an address lookup or autocomplete service. Such tools deliver correct address data in real-time by providing a properly formatted, correct address when the user starts to input theirs. This approach also cuts the number of keystrokes required by up to 81 per cent when entering an address, speeding up the onboarding process, improving the whole experience, making it significantly more likely that the user will complete a purchase or application. Similar tools can accurately collect email addresses, telephone numbers and names at the first point of contact. 

Deduplicate data because data duplication is a common and significant issue, with 10 - 30 per cent duplicate rates not uncommon for those organisations without data quality initiatives in place. Data duplication adds cost in terms of time and money, particularly with printed communications and online outreach campaigns, and it can have a negative impact on the sender’s reputation. Obtaining an advanced fuzzy matching tool to merge and purge the most challenging records is the ideal solution to generate a ‘single user record’ and source an optimum single customer view (SCV). The insight from which can be used to improve communications. 

Embark on data cleansing or suppression activity to highlight people who have moved or are no longer at the address on file. Along with removing incorrect addresses, these services can include deceased flagging to stop the distribution of mail and other communications to those who have passed away, which can cause anguish to their friends and relatives. By implementing suppression strategies financial institutions can save money by not distributing inaccurate messaging, protecting their reputations, while boosting their targeting efforts to overall improve the customer experience.

Today, it’s never been easier to deliver data quality in real-time to support wider organisational efficiencies and provide a better customer experience. Access services such as a scalable data cleaning software-as-a-service (SaaS) platform that can be accessed in a matter of hours and doesn’t require coding, integration, or training. This technology can cleanse and correct names, addresses, email addresses, and telephone numbers worldwide. It can do so with held data in batch and as new data is being gathered. As well as SaaS, such a platform can additionally be deployed as a cloud-based API, via connector technology like Microsoft SQL Server, or on-premise.

For those serious about growth make it a priority to take the necessary steps to clean you customer data on an ongoing basis.