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Client Relationship Management System:

Data Quality



A nonprofit had almost abandoned its CRM system due to significant data quality concerns and a potential liability to fundraising efforts.



A lack of focus on data quality over the ten-year life of the CRM solution had resulted in duplicate, stale, incomplete, and inaccurate data. 



Implement data standards via new templates and processess. Cleanse the historical data and establish data hygiene protocals.



Improved quality of prospect and donor data and implemented ongoing data quality practices to avoid recurrence.

The Whole Story

CRM data quality issues were leading to limited usage, poor segmentation, and negative brand perceptions.

A nonprofit organization, whose fundraising efforts were critically dependent on the quality of its prospect and donor data, had almost abandoned use of its CRM system due to significant data quality concerns.  End users not only considered it an unreliable source of data but often a liability to fundraising efforts. 


A lack of focus on data quality over the ten-year lifespan of the CRM solution resulted in a multi-terabyte data store of duplicate, stale, incomplete, and inaccurate data.  Fundamental industry-standard practices, such as checking if a record already existed before entering a duplicate, were not in place.  Although the nonprofit subscribed to and paid for monthly reporting that detailed the data quality issues needing to be corrected, the absence of a data quality operations team left the findings unactioned. 


Inexperienced with how to systematically assess the root cause of data issues and how to remediate them, the nonprofit hired Stanton Blackwell to develop a data quality program.

Stanton Blackwell’s Role

Conduct data quality assessment of CRM data – scope the nature of issues, identify the root cause, and design proposed remediations.

We started by creating an inventory of the organization’s online data capture points and analyzing them in detail.  Very quickly, it was clear that there were no data standards in place, and most typed content was captured in free form. This meant there was significant inconsistency and incompleteness in how data was captured.  The lack of standards made it difficult to use the data effectively and made it quite difficult to identify duplicate records. 


To remedy this, we designed a single template to be used across all website entry points to capture prospect or donor data.  We established mandatory fields that were automatically formatted to industry best practices.  Additionally, we introduced validation checks to make sure of the accuracy of the data entered. The result: significantly improved data quality, beginning with new data entered into the system. 


Having reduced the chance of new data quality issues coming into the system, we turned our attention to the records already in the CRM. We quickly identified that the system functionality was

not being utilized to its full potential for monitoring and identifying data errors, nor were they using the system’s automated correction capabilities.  Our CRM tiger team worked with the client’s technology team to adjust settings and write scripts that automated data error identification and remediation.  Over a short period of time, ten years of historical data were standardized.


To further simplify their environment, we identified and implemented recommendations for significantly reducing the volume of data stored.  Because the client had not previously trusted their data practices, they had never deleted a record. Now, having standardized and deduplicated much of their data, we were able to introduce safe deletion techniques which dramatically reduced noise in the system and cost of data storage as well as simplified the scope of data to migrate if the client ever chose to switch CRM tools. 


Among our deliverables, we detailed the data standards and cleansing procedures in a governance document for the nonprofit to be self-sufficient in maintaining its data hygiene.


Most meaningfully, our work addressed numerous issues with the potential for a significant negative impact on fundraising efforts and brand perception. 


A CRM with dramatically improved data quality critical to fundraising.

We were able to significantly improve the quality of a nonprofit’s prospect and donor data in direct support of their critical fundraising campaigns.  Through detailed analysis, we not only cleansed their historical data, but implemented preventative measures to avoid their reoccurrence, and supported them in implementing ongoing data quality practices. 

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