Even with the best data governance processes and system limitations you may still find data integrity issues. Your issues could be brought up by your sales reps who have called the wrong person, by your analyst that has to spend extra days cleaning the data prior to running simple analysis or even the CEO who may not be able to make sense on all the data in your CRM. While those complains maybe unavoidable you can establish data quality checks to stay ahead of data integrity issues. Here are just a few examples of data monitoring for data quality by fields:
- Emails – most systems already have a check to make sure that emails have @ and . in the domain name. To go the extra mile B2B marketers may want to make sure that all emails in the same account have the same domain name, keep in mind that you can have personal emails creep in.
- Date Formats – Are consistent with clear MM – DD – YY classification, a good way to implement your system is to have the numbers convert to a 10-Nov-2017 format as oppose to having it 10/11/17 format.
- Websites – Should have a dot. and be at least 5 characters long.
Other data quality checks include:
- # of Incomplete Records – You may want to run analysis by source or sales rep to identify who creates incomplete records.
- If the percentage of “Other” in your drop-down menus are starting to exceed 10% or more, it is time to clean it up.
- Bounce Rate – if your bounce rate is starting to increase, it is time to validate your email address and check if your system is out of date and has aged.
- Last Date of Data Cleaning – Perhaps the most important date to keep in mind is the date of your last clean-up initiative. Data cleaning should be done on a yearly basis, especially in high turn-over job titles for B2B marketing. For B2C you should do data cleaning prior to any major campaign if you are doing Direct Mail.
- Data Audit – The final check is to do a data audit on your overall system. To see what % of your data is duplicated, incomplete and outdated. StrategicDB offers free data audits to help you conquer any data integrity issues you may have.
Once you have established you data quality checks, it is time to relax and focus on more important tasks at hand such as putting out fires, analyzing sales trends and planning for data growth.