Data Quality Reporting is a way to monitor and account for your database’s data quality. You can start monitoring it today, by building a basic data quality report with a simple dashboard as your first step!
As a starting point you should have a field in your salesforce instance or any other CRM solution which calculates the percentage of your database for desired fields that are empty. To do this there are a few steps to take:
- It is important to identify the fields that are important to the business.
- Since not all fields are created equally, you can assign a weight percentage based on field’s importance.
- The score can be set –up as a simple percentage of completeness out of 100%. Alternatively, it can be a score of A, B, C, D depending on the criteria set.
Once this score is established, you can set-up reports to identify your sales reps, sources and other variables that effect your score. By monitoring the score on an ongoing basis you are able to increase completeness to a higher level by addressing gaps in your sources, marketing, and sales rep’s attention to detail.
Once it is done, you can move on to the 2nd impact of data quality in your CRM which is having current data. The way you would set-up reporting is to see what percentage of your data has been modified in the last 30 days, quarter, year, etc… Keeping in mind, that systems sometimes update/modify your records without really changing the field. However, Salesforce and other CRM sometimes will allow you to keep track of history for certain fields. You can at this point, use that to see if a field that needs modification has been updated in the last year. For example, Annual Revenue Range or Annual Revenue of a publicly traded company should be updated within the last 12-13 months, therefore, by running a history report on that field or by adding a last updated on that field you are able to see the percentage of accounts that are out of sync.
Your 3rd indication of high data quality is to have a consistent data. If you have already locked down and normalized all your fields, then you have probably placed all new values that were not on your normalization table in the “other” bucket. By having a report and reviewing all the values in the “Other” bucket you are able to continue to optimize your normalization. When that goes beyond a certain threshold you know it’s time to review and clean-up your data.
The final indication of great data quality is having correct data. This is the hardest type of data quality that is able to quantify and report on. However, you can still have flag in your fields to catch bogus accounts by looking for consecutive numbers if phone #, having zip codes which are less than 5 digits for US addresses, identifying firstname.lastname@example.org emails and other similar issues.
Another way is to identify records which do not have the phone # area code match the state or country of the record, you can also identify if states are not equal to the zip code provided.
Finally, you can also identify the number of records that are bounced and have a report based on source.
All of the above are just a few ways of to ensure your database has the highest data quality and reporting on it would keep you on track. As each business is unique, StrategicDB is more than happy to offer service which will not only help clean up your data but also help you monitor the quality going forward.