How Data Cleansing add Value to Customer Data

1. Data Audit:

• The principal step to data cleansing, is the thorough auditing of all customer databases. The reviewing should be done using statistical and database methods to detect inconsistencies and inaccuracies. The information should be used to infer characteristics and location of inconsistencies, which can lead to root cause of the problem.

2. Merge Data:

• The process of cleansing the database should not be restricted to just the recognizing and removal of inaccurate data from client database. It should be used as a prospect to combine customer data and other information like email ids, phone numbers or additional contacts should be combined whenever possible.

3. Feedback:

• The business should launch a control mechanism where any erroneous data gets reported and gets updated into database. For instance, there should be a control and feedback mechanism for emails and any email which is undelivered owing to an incorrect address, should be reported and the invalid email address cleansed from the customer data.

4. Use Various Methods:

• The process of auditing of a database should not be restricted to analysis through statistical or database methods and further steps like buying external data and comparing it against internal data can be used. Moreover, if a business has restraints of time and employees, it can use the services of external company. However, in this approach, the business needs to be careful with respect to their brand image and the way of working of external company.

Data cleansing is a difficult yet critical process and needs devotion of dedicated time and resources. The processes stated above would certainly help in the making of a clean database which deals several benefits across functions and serves as a critical factor in the growth of business. Hence, businesses should make investment in data cleansing and data management a top priority.