Customer Data Management

Dirty data can create a lot of time wastage and resources. It's essential that businesses perform address cleansing to organise their data.

hero-jobbies-7

Dirty data can create a lot of time wastage and resources. It's essential that businesses perform address cleansing to organise their data.

Customer data management involves collecting, storing, and using customer data to drive increased sales, customer retention, and better customer experiences.

As a business grows, they need to manage their data efficiently and effectively. Data decays by 20% per year which results in poor formatting, disordered structure and duplication.

Customer data management

The customer is the foundation of any business’ success. Accurate customer data enables a business to target specific customers and understand them. It also helps build strong relationships and faster market penetration.

Customer Data Management is important for:

  • Customer acquisition

  • Increasing retention and engagement rates

  • Knowing customers in detail and better knowledge of customer needs

  • Simplifying customer relationship management (CRM)

  • Drive higher revenue

  • Generating customer insights

  • Customer Segmentation

  • Building effective communications

  • Higher data efficiency by eliminating duplication and bad data collection

  • Compliance and data security through standardisation and centralisation of data

Ideal Postcodes Address Cleansing

Our Address Cleansing solution helps you increase database accuracy and reduce costs by ensuring all records are correctly formatted, accurate and up-to-date. It is also essential that your data is compliant with the data protection principles outlined in the GDPR Regulation. Ideal Postcodes can help.

Our address specialists verify your existing database against official data sources and return updated and accurate results. Read our Address Cleanse guide on what you can expect. Cleanse and enhance your address records with UPRNs, Rooftop Geolocations and additional authoritative datasets.