Data Quality
Data Quality refers to the accuracy, consistency and completeness of that data.

Organizations rely on clean, accurate customer data to run their day-to-day operations and gain insight to make informed business decisions. Data quality refers to the accuracy, consistency and completeness of that data. Since data is often collected from many different sources, businesses need an effective way to manage it to ensure it remains useful.

Why is Data Quality Important?

Bad data is costly for organizations. Inaccurate information, outdated contacts, incomplete and duplicate records result in everything from undeliverable shipments to returned mail and lost customers. Data quality creates a foundation for businesses to work more effectively with their customers. By addressing data quality issues, businesses can leverage their data for analysis and better decision-making to improve the efficiency of their operations. In the long run, it ends up being more costly for businesses not to have a solid, comprehensive data quality approach or solution in place that will guarantee their customer contact information is valid. Solutions that correct and verify data at the point of entry go a step further by making sure bad data never gets into an organization’s systems in the first place - preventing data quality issues down the road.

What Steps Can Be Taken to Improve Data Quality?

The CRM database is an important and valuable asset for many companies. But if the data isn’t accurate, it’s useless. The following four steps can be taken to improve data quality:

  1. Check data before it enters your system - Verifying contact data at the point of entry saves time & money
  2. Fill in the gaps - Data enrichment adds missing contact information for more complete customer records
  3. Remove duplicate records - Identify and merge multiple records into one “Golden Record” for each customer
  4. Keep your records current - Continuously update your database with change-of-address information

Taking the steps to improve customer data leads to better response rates, greater customer satisfaction and, ultimately, ROI. Learn more about data quality here, how it’s measured and the lifecycle that organizations go through to implement their DQ strategy.

Why Melissa?

Melissa has been helping businesses improve their data quality for over 35 years with smart solutions that correct, verify, update and enrich customer data. Our full spectrum of data quality solutions give businesses the tools they need to maintain clean, current and consistent data for more efficient operations and improved marketing and sales efforts. Melissa’s Data Quality Suite instantly verifies contact data at the point of entry for over 240 countries and territories, with flexible tools that are available as on-premise APIs or Web services to meet your specific needs.

250+ Countries & Territories
1,000,555,787+ Addresses Verified
35+ Years
10,000+ Customers Worldwide