By Barley Laing, the UK Managing Director at Melissa
Competition is growing in the financial services sector as more fintechs compete with the legacy banks. At the same time, it is becoming harder for financial institutions to stand out in a crowded, increasingly online marketplace. This makes it vital to create a point of differentiation via the delivery of a positive customer experience.
Also, customer acquisition requires more investment than retention, with it costing on average five times more to source a new customer than to keep an existing one. This makes it critical to put time and resource into delivering a great customer experience to drive loyalty and long-term revenue.
What does clean data offer?
Customer data is one of the most valuable assets financial institutions have. If maintained and used correctly it can help to prevent customer churn and drive revenue. Clean and updated data can be analysed to gain valuable customer insight that can be used to deliver personalised communications, which can help to up and cross-sell products and services, and aid new product development.
Data decay is a problem
Unfortunately, data decays quickly – on average two per cent a month and roughly 25 per cent a year – as people move home, divorce or pass away. This makes it vital to have data cleaning processes in place at the point of data capture, and when cleaning held data in batch. The good news is the delivery of such practices usually involves simple and cost-effective changes to the data quality regime.
Use an address lookup / autocomplete service
To collect accurate contact data at the customer onboarding stage use an address lookup or autocomplete service. It provides accurate address data in real-time by providing a properly formatted, correct address when the user starts to input theirs. It also cuts the number of keystrokes required, by up to 81 per cent, when entering an address. This speeds up the onboarding process and diminishes the probability of the user not completing an application or purchase.
This approach is important with 20 per cent of addresses inputted online containing errors; these include spelling mistakes, wrong house numbers, and incorrect postcodes, mainly due to errors when typing contact information.
The good news is that first point of contact verification can be extended to email, phone and name, so this valuable contact data can also be verified in real-time.
Deduplicate data
Data duplication is a significant issue, with the average database containing 8-10 per cent duplicate records. This occurs for a variety of reasons, for example when two departments merge their data and mistakes in contact data collection occur at different touchpoints. It adds cost in terms of time and money, particularly with printed communications and online outreach campaigns, and it negatively impacts on the sender’s reputation.
Using an advanced fuzzy matching tool is the best approach to merge and purge the most challenging records to create a ‘single user record’ and obtain an optimum single customer view (SCV), with the insight used to improve communications. Also, organising contact data in this way will maximise efficiency and reduce costs, because multiple outreach efforts will not be made to the same person. An additional benefit is that the potential for fraud is lessened because a unified record will be established for each customer.
Data cleaning
Data suppression, or cleaning, using the appropriate technology that highlights people who have moved or are no longer at the address on file, is a crucial part of the data cleansing process, and therefore in supporting efforts with improving the customer experience. 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 distress to their friends and relatives. By applying suppression strategies organisations can save money, protect their reputations, avoid fraud and improve their targeting efforts.
Source a data cleaning platform
Evolving technology, such as artificial intelligence (AI), means it’s never been easier or more cost-effective to deliver data quality in real-time to support the delivery of a better customer experience and wider business efficiencies. It’s possible to source a scalable data cleaning software-as-a-service (SaaS) platform that doesn’t require coding, integration, or training. This technology cleanses and corrects names, addresses, email addresses, and telephone numbers worldwide. Also, records are matched, ensuring no duplication, and data profiling is provided to help identify issues for further action. A single, intuitive interface provides the opportunity for data standardisation, validation, and enrichment, resulting in high-quality contact information across multiple databases. It can deliver this with held data in batch and as new data is being gathered. Also, such a platform can be deployed on-premise, if required.
Identity verification
As part of adhering to know your customer (KYC) and anti-money laundering (AML) regulations at the customer onboarding stage, undertaking ID verification checks in real-time using a SaaS electronic identity verification (eIDV) tool or web API, is just as important in delivering a good customer experience.
In summary
Implementing best practice data quality procedures is a must for those serious about improving their competitive edge and driving growth in 2024. Doing so makes it possible to deliver a consistent, positive customer experience online, and therefore build stronger, more resilient long-term engagement and revenue.
