Enhance your data against third-party databases
Data Services / Data Services Blog / Data-Driven Marketing / Enhance your data against third-party databases
Data enhancement is the process of validating a database against third-party knowledge bases in order to check, update and complete a company’s information. There is a wide range of possible enhancements: adding postcodes to addresses, area codes to phone numbers, and many more. Common data enhancements include:
- Attaching (appending) telephone numbers and email addresses to records.
- Attaching Australia Post Delivery Point Identifiers (DPIDs) to addresses. Attaching these eight-digit numbers (unique for each address in Australia) significantly reduces ‘Return to Sender’ mail and postage costs for bulk mailings. (International equivalents and other business standards are also accommodated.)
- The automatic generation of Australia Post bar codes.
- The National Change of Address service (NCOA), which helps to find lost customers. New address details are attached to the records of any customers who have moved and registered with Australia Post’s Mail Redirection service.
- Washing data against do-not-call registers.
- Flagging socio-demographic, transactional or consumer preferences.
- Mapping – adding spatial information.
In some situations, data needs to be integrated from two or more separate sources before it can be used. During this process, multiple, diverse data records are cross-matched and assimilated into a new, consolidated data set. Data integration may be required in the following situations:
- After a merger, customers may have relationships with both organisations, and a single-customer view is needed to facilitate better decision making and corporate responsiveness.
- During direct-mail campaigns, when combining a company’s customer data with purchased third-party lists.
- When moving from a product-oriented to a customer-oriented approach.
- In applications where two separate data sources are matched for reconciliation purposes.
- When comparing different types of databases: for example, an accounting database with a marketing database.