2025 is proving to be a challenging time for financial institutions looking to drive revenue. Organisations from the Bank of England to the IMF have been predicting a year of slow economic growth in the UK for the remainder of 2025, and now there’s uncertainty
on tariffs which could have a significant negative impact on economies globally.
In this tough macroeconomic environment those wanting to drive growth need to take the important step of ‘spring cleaning’ their customer databases. Doing so sees customer communications improved with personalisation, which in turn drives efficiencies, enhances
the customer experience, boosts revenue, while at the same time reduces churn. Additionally, a focus on cleaning ensures best practice regulatory compliance, reducing the opportunity for fraud.
With research from Gartner highlighting that 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, data cleaning should not take place once a year but on an ongoing basis.
To this end, data cleaning processes should be used not only at the onboarding stage, but to clean held data in batch.
Delivering clean customer databases
The accurate collection of customer data at the onboarding stage should commence with an address lookup or autocomplete service. These tools deliver correct address data in real-time by providing a properly formatted, correct address as the user starts to
input theirs. Via such a service the number of keystrokes required is cut by up to 81 per cent when entering an address, speeding up the onboarding process, improving the whole experience, making it much more probable that an application or purchase will be
completed. Also, very similar tools can correctly collect email addresses, telephone numbers and names at the first point of contact.
Those organisations without data quality initiatives in place commonly experience 10 – 30 per cent duplicate rates on their customer databases. This can potentially lead to customers receiving two or more of the same communications. This makes deduplication
vital, because duplicate data 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. The solution is to obtain an advanced fuzzy matching tool
to merge and purge the most challenging records to create a ‘single user record’ and source an optimum single customer view (SCV). This insight is key in improving customer communications.
To highlight people who have moved or are no longer at the address on file undertake data cleansing or suppression activity. As well as removing incorrect addresses, these services often include deceased flagging to prevent the delivery of mail and other
communications to those who have passed away, which can cause distress to their friends and relatives. The use of suppression strategies enables financial institutions to save money by not distributing inaccurate messaging, therefore protect their reputations,
while boosting their targeting efforts to overall improve the customer experience.
Delivering data quality in real-time to support wider organisational efficiencies and provide a better customer experience has never been easier. Obtain 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 need coding, integration, or training. Such 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 collected. As
well as SaaS, such a platform can also be deployed as a cloud-based API, via connector technology like Microsoft SQL Server, or on-premise.
Those serious about growth in these uncertain times must make it a priority to take the necessary steps to clean their customer data on an ongoing basis.
