The importance of data quality to companies cannot be denied; but how many know how to identify high quality data from poor data? Even if companies identify a data integrity issue, do they understand the inefficiencies and wasted resources that result from it? Often times the individuals who recognize a data integrity problem are not the decision makers, resulting in a misunderstanding of how poor data quality is impacting the bottom line.
Organizations need to become aware that every customer entry point is an opportunity for bad data to enter their systems. Proactive measures should be taken to keep contact records and databases clean.
The first step a company should take to improve data integrity is to identify in real-time the areas where bad data is entering the system. Poor data quality has a downstream effect on all systems it interacts with, so the best solution is to reduce and prevent bad data directly at the source.
Common Origins of Bad Data:
- Online customers: Customers may intentionally enter incorrect information into web forms.
- Front-line employees: Customer Care representatives or support personnel are pressed for time to help as many customers as possible. This can lead to abbreviated or incorrect data being entered into the system.
- Typing errors: Fingers can get tangled on a keyboard; letters or numbers become transposed or spelled wrong.
Taking actions to improve the quality of data entering your database can lead to significant business gains and higher levels of customer satisfaction. One simple way to improve data integrity is to verify, correct and append customer contact information in real-time. This includes performing lead validation, address validation, phone number append, and email validation on contact records before it enters the database.
Failing to put proper data integrity procedures in place today can lead to significant waste down the road. Companies need to take the time to protect its most important business assets – customer data.
