CRM Data Quality Solutions
What are CRM Data Quality Solutions?
CRM Data Quality Solutions are applications and plug-ins which improve the quality of CRM data. Their goal is to ensure that the data in the CRM system is of sufficiently high quality to serve the needs of the Sales, Marketing and Customer Service departments all of whom rely upon the data being fit for use.
The management of CRM data quality is a specialism for DQ Global®. Our roots can be traced back to the implementation of multiple CRM systems, as such, we understand that low quality data will undermine any CRM project.
We have a clear understanding of the data quality challenges companies face when importing, using and reporting on CRM data and have designed our CRM data quality software to specifically meet the needs of CRM system users and administrators in both ease of use and value for money.
We understand the challenges of preserving data integrity when importing, cleansing, cross-matching merging/purging and deduplicating CRM systems. We have developed our CRM Data Quality Software over the past 20 years. Our aim is to make CRM Data fit for Business use.
CRM Data Quality problems we have seen…
The greatest challenge we have seen is ownership of the data quality problem.Typically there is no sponsor or champion for the measurement and management of CRM Data Quality. There is a debate in the business as to who owns the data. I.T. state the business owns the data and the business thinks data is technical so I.T. should own the data. In practice the data falls through the cracks and that’s why it’s generally of low quality. For CRM to succeed there must be clear ownership and governance of the data, basically everyone owns the data, from recording to reporting and all steps in between. Some of the problems we have seen include:
- Consistency – without point of capture controls through technology and procedure, data will be entered inconsistently
- Uniqueness – unless duplicate detection is implemented at both point of entry and retrospectively in batch, a single customer view is not achieved
- Timeliness – reports, process flows and cash flows can be delayed when CRM data is incorrect or incomplete
- Validity – without automation and business rules to monitor data, invalid values enter and stay in the system
- Accuracy – unless technology and processes are applied to data, user trust diminishes and the CRM system falls into disrepute
- Completeness – decision making is flawed when data is missing