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10 Best Practices to Ensure CRM Data Quality

Your customers and prospects data is a heart and soul of your CRM. Utilizing CRM effectively helps you with better targeted sales and marketing campaigns, cost saving, and an increased ROI.  CRM is as good as the data which lies in it. To get the maximum benefits out of your CRM, you should have accurate and complete data. Sadly, data can be outdated easily as business data constantly changes and duplicate data is a known problem when you rely on multiple data sources. CMS with dirty data will do more harm than good causing obvious blunders that waste your time, money and reputation. Here are 10 best practices that can help you manage CRM data and get the most out of CRM investment.

1. Ensure Data Completeness

One of the major reasons for poor data quality  is because of the incompleteness. You need to make sure your records are complete. A CRM record will have numerous fields. So, it is a must to make all the important fields mandatory. The number of such mandatory fields may depend upon your business structure while the most common ones are name, email address, phone numbers and other contact details.

2. Avoid Data Entry Mistakes

Enforcing data checking while entering them into the database can decrease the inaccuracy of data entered by 50%. There are many ways to ensure that only correct data is entered.

  • You can make use of embedded spell check features of certain CRM software.
  • For a specified set of values, you can use predefined drop down lists to enter values so that the operator does not enter the wrong values.
  • Avoid entering duplicate values by comparing them against the existing values. One best way to do this is by comparing against an email address since email address is usually a unique field.

3. Merge Duplicate Records

Merge multiple records with duplicate data to get a single complete record  is the way to clean up data. For instance, the first record may contain first name, last name and email address but missing a phone number while the second record may contain the same first name and last name with additional details on phone numbers. In this case, merging the records—rather than deleting them—will be a better solution.

4. Create Data Plan

Data plan sets data standard. It help increase your data quality by maintaining and enforcing style, format, and naming conventions of short forms, titles, designations, address, company names etc. to maintain consistency of data across the organization.

5. Provide Restricted Access

As information is coming from various sources to the CRM database, you must be able to maintain its cleanliness.

You can do this by restricting the access to your database by defining roles and allowing only authorized access to manipulate and update data.

6. Redesign Data Plan

Your CRM has to be scaled up as per the growth of your business or some new business requirements, therefore, a CRM data plan need to be redesigned as well to ensure your CRM stays clean.

7. Train End Users

Training your CRM users on the data quality practices.  This is a  logical move that should be done in order to see the maximum result of your data plan.

8. Maintain Data Formats

Data formats must be adhered to when you import data from other sources. Enforcing data compliance will reduce errors.

9. Make Use of Data Markers

Data markers are used by CRM systems to fill in missing data. The patterns give a clue on how to fill in missing data. For instance, if the email format of employees of a certain organization follows a pattern of firstname.lastname@domain, you can easily assume the email addresses of other employees whose email fields are empty.

10. Periodic Checking and Real-Time Updates

Regular data check can avoid inconsistent states and provide confidence in the system. As data is subject to change often, employing real-time update mechanism will be helpful in keeping your database complete and correct. Using cloud computing technologies and certain advanced features will help you deal with real-time updates and automated checks.


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