Definition:
Companies and organizations of every kind understand that without accurate, high-quality data, they will waste a significant amount of time and effort trying to reach clients. They will unsuccessfully develop outreach and marketing campaigns that are ineffective, as well as create extra labor for in-house staff working with competing data sets. That is why these entities constantly strive to make sure that only the most accurate and relevant data possible enters into databases.
Unfortunately, even the most vigilant efforts to prevent errors from creeping into the client data cannot keep all mistakes and inaccuracies from finding their way into the contact records.
A successful data management plan cannot focus only on preventing incorrect data from entering the system. It must also periodically revisit database information to fix outdated information, as well as repair mistakes introduced in the transmission and storage of data.
In short, a comprehensive data management plan must include regular data cleansing. But what is data cleansing, and how does it benefit companies or other organizations in the long-run?
The basics of data cleansing
A succinct data cleansing definition can be derived from the phrase data cleansing itself. Simply put, data cleansing consists of the discovery of errors in a data record and the removal or correction of these mistakes.
Remove incorrect, incomplete, duplicate and improperly formatted data
Industry experts recognize that data cleansing is the most important aspect of data quality management. It is impossible to prevent absolutely every error from entering client databases, and the expanding number of ways that customers can interact with companies and organizations means that there will likely never be a system that catches every error at the point of entry every time. This is not to deny the need to be proactive in regard to helping to keep customers, clients, and even company and organizational staff from entering errors. However, it is to recognize the reality of human error, the complexities of our digital age, and the problems that go along with the opportunities afforded by vast quantities of customer and client data.
Data cleansing is necessary for all forms of customer data. Back-end address verification, for example, reviews customer mailing addresses and makes sure that they are updated with correct ZIP codes, new addresses when clients move, and so forth.
Email verification does the same kind of thing with email addresses, eliminating incorrect email addresses from the systems of companies and organizations, processing email changes, and much more.
In the long-run, regular cleansing of data keeps contact information accurate, enabling you to stay in touch with clients and to market to them effectively.
Cleanse your data today
What is data cleansing and why is it necessary? Data cleansing is necessary to maintain data accuracy, as well as to ensure that you can always reach your clientele effectively. When the key parts of the data cleansing definition are understood, it is obvious that every data quality management effort will be successful only when cleansing of data is included. Experian Data Quality can help you with its large variety of data cleansing and data quality products.
Related links:
Learn more about address verification solutions.
Learn more about email verification solutions.