By Barley Laing, the UK Managing Director at Melissa
Having inaccurate and duplicate data is a big issue for many organisations, with those in the retail sector being no exception. This was the key finding in our State of enterprise data quality 2025 report which highlights that 84 per cent of organisations struggle with inaccurate or duplicate data.
The research also uncovered that data quality issues are the root cause of data-related challenges. Outdated contact information was at the top, cited by 32 per cent of respondents.
In second place was compliance with evolving data regulations, raised by 25 per cent of interviewees, with incomplete customer profiles third, raised by 23 per cent of those questioned.
It’s important to recognise that each of these issues compounds when records are scattered across systems that do not synchronise in real-time.
Further data-related challenges include identity fraud or impersonation cited by 17 per cent of respondents, duplicate records by 15 per cent, and difficulty in integrating multiple data sources was raised by 12 per cent of those questioned. While these three areas receive slightly lower scores their aggregate cost can surpass more visible pain points.
Also, recognition that fraud losses tend to spike in isolation is important, while manual deduplication efforts often accumulate without warning or budget allocation.
Focusing on the root causes of data problems and switching from ad hoc firefighting into a continuous, rules-driven process, can help.
Consider address verification
Putting processes in place that deliver address verification is a good starting point in delivering contact data accuracy on an ongoing basis. Then, with clean and verified addresses, providing a fast and frictionless shopping experience that consumers expect is achievable.
Additionally, clean customer data can be effectively analysed to acquire valuable customer insight that can be used to keep them happy, with personalised communications and offers. And don’t forget that by having up-to-date and standardised customer addresses it’s much easier to match and verify identities across multiple sources.
This makes verifying the accuracy and legitimacy of an individual’s address an important part of any identity related process, with any discrepancies between a claimed address and official records acting as red flags for fraud or compliance failures.
Investigate address lookup technology
A good way to collect accurate customer contact data at the onboarding stage is via an address lookup or autocomplete service. Such tools provide a properly formatted, correct address when the user starts to input theirs.
This reduces the number of keystrokes required by up to 81 per cent when entering an address, speeding up the onboarding process, enhancing the entire experience, and making it much more likely that a purchase will be completed.
Furthermore, similar tools can correctly collect email addresses, telephone numbers and names at the first point of contact.
Data deduplication
Retailers without data quality initiatives in place commonly experience 10 – 30 per cent duplicate rates on their customer databases.
This adds cost in terms of time and money, particularly with printed communications and online outreach campaigns with customers receiving two or more of the same communication. It’s an approach that also delivers a negative impact on the sender’s reputation.
One option to prevent this 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 essential in improving customer communications, along with reducing the opportunity for fraud.
Embark on data cleansing
Undertaking data cleansing or suppression activity to highlight people who have moved or are no longer at the address on file is a smart choice. 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 anguish to their friends and relatives.
Using suppression strategies enables retailers to save money by not distributing inaccurate messaging, and therefore protect their reputation, while at the same time improving their targeting to overall improve the customer experience.
Source a SaaS data quality platform
Delivering data quality in real-time to support wider organisational efficiencies and provide a better customer experience has never been easier.
It’s possible to access a scalable data cleaning software-as-a-service (SaaS) platform in a matter of hours, without the need for coding, integration, or training. Such technology can cleanse and correct names, addresses, email addresses and telephone numbers worldwide from official data sources – government agency, credit agency, and utility companies.
It can do so with held data in batch and as new data is being collected. Outside of SaaS such a platform can additionally be deployed as a cloud-based API, via connector technology like Microsoft SQL Server, or on-premise.
In summary
Data quality can no longer be an afterthought. It needs to be a strategic business priority. Retailers that embrace real-time, automated contact data verification and deduplication services are better positioned to unlock long-term growth by helping to reduce risk, prevent fraud, and accelerate onboarding, while improving the customer experience.
Published 10/11/25
