Data quality or integrity is important for accurate reporting, efficient sales, profitable marketing and a variety of other reasons. But how do you go about identifying if you have a data quality issue? Most companies wait until they have to migrate their data to a new system or when data quality has declined so much that employees are starting to complain. So how do you identify any data quality issues prior to it impacting operations?

Begin by establishing data quality KPIs, just as you report on metrics on sales, marketing, customer service, and so on, you should report on your data quality. Here are some basic KPIs that are most commonly used, depending on your business they may or may not be applicable.

  • Bounce Rate – If your emails are being bounced at a larger rate, chances are you have an outdated CRM. Bounce rate is a measure that is most applicable to B2B businesses, as people switch jobs every couple of years.
  • Database Size – By looking at how many active accounts or contacts you have that have not bounced or declined your offer, you get an idea of your size. Monitoring the number of new records created vs. outdated records, can identify trends on how current your database is. You should at the very minimum ensure that new accounts equal the accounts that are no longer active, if you are looking to grow your database your new accounts should be greater than your outdated records.
  • “Non Active” Records and their reasons – depending on your set-up you may put a flag on inactive records and the reason for their inactivity. This is common practice, and if you currently do not have a flag and a drop down for the reason of marking a record as inactive, it should be implemented. One of the reasons could be, competitor, uses a competitor’s product, and other categories that do not have any impact on data quality. But do keep track of the data quality reasons such as “no longer there”, “wrong person”, “invalid phone #”, and so on… Your categories maybe different but the idea is to monitor when a specific reason has increased so you can fix it before, it becomes a real problem.
  • Data Completeness Score – perhaps the simplest metric to set up. Identify the mandatory fields for your company and calculate what percent of the mandatory fields have a value. This will identify your average completeness level of your CRM. Monitoring this score will help establish when you have a need for data appending services.

After you establish your KPIs, you can begin to do some spot checks on your CRM on a quarterly or semi annual basis to see if you can uncover some other common issues that companies face with their data. The data issues typically include:

  • Duplicates – Duplicate records are hard to identify on a dashboard, however, you could do a quick search to see if you can spot some duplicates or do a quick duplicate audit.
  • Consistency – you may have consistency issues within the same format. For example, you may have NY or New York as a state this will make it difficult to run reports or marketing as you have to select both. To see if you have any issues, there is a very quick way to test in plain old Excel. Just simply download a sample of your CRM fields, and run a quick Pivot table to see if the data is consistent.

Finally, having a quick meeting with members representing different data users can give you a quick assessment if they are running into any data integrity issues. You may uncover that customer service has a hard time locating the correct individual due to duplicates, the sales rep is missing a lot of phone numbers for the accounts he has to call and finance is dealing with outdated addresses that no one has verified. If you established a data quality issue, StrategicDB, a data cleansing company can help.