At a very simple level, organisations need to understand who their customers are. This seemingly simple need is often extremely complex, because customers have a habit of moving, aging, making different purchasing decisions – basically being continually evolving data points! And that’s not even to mention those who are trying to hide some aspect of themselves for poor credit reasons, or even to evade detection for the purposes of committing crime.

Many firms therefore use a customer 360 dashboard in order to visualise a customer’s journey, from initial enquiry, through onboarding and into areas including real-time transactions. At a bare minimum, this will require many hundreds of data points covering date and place of birth, nationality, gender, financial and residential history and so on. Much of this data is considered ‘special’ or ‘‘ category data, subject to strict controls on storage and use, adding additional headaches for firms seeking to optimise customer experiences and prevent fraud.

For large institutions such as financial services firms, it’s therefore likely they will hold a vast amount of disparate data on a single customer. In order to improve their sales and marketing efforts, as well as internal reporting, it’s crucial to have complete and up to date information on their customers. Through collating and aggregating various datasets into a single source, the customer can receive a better personalised experience and organisations can increase their business intelligence, resulting in improved revenues and reduced financial penalties for non-compliance.

Customer 360 is underpinned by data quality; without reliable and accurate information on a customer, it becomes a challenge to extract valuable customer insights. Alongside the clear reduction in risk, Customer 360 offers organisational benefits, from improved downstream intelligence to more accurate planning and forecasting.

How Ä¢¹½¶ÌÊÓƵ can help:

The data matching technology at the heart of Ä¢¹½¶ÌÊÓƵ’ Self-Service Data Quality platform is fundamentally important to a Customer 360 programme. Its configurable fuzzy-matching capabilities help customers to identify close and near matches, and using AI can reduce the time spent on manual review by 45%. Read about it here.

Whilst data catalogs have been around for some time, it would have previously been a very manual task organizing an enterprise’s data. Now, however, with greater automation and data-driven technologies, it is much easier to quickly navigate and make sense of the data an organisation holds.

For departments where timeliness is key (e.g emergency services/policing), data catalogs are a valuable tool for allowing secure data discovery and accessibility. In the same way that search engines like Google can quickly categorize enormous amounts of data and present a user with the relevant results, data catalogs use metadata to organize an enterprise’s data assets into an inventory to be accessed by data stewards, analysts and scientists. The benefits of a data catalog include improved operational efficiency in terms of time and money saved, but also data stewards are empowered to self-serve in order to access the data they need, without having to rely on other departments.

Data catalogs support data governance and improve data discovery within an organisation, helping prevent wasted resources and data lakes turning into data swamps!