Like any asset, your CRM system relies on the quality of its inputs to deliver value. Poor-quality data misguides decisions with inaccurate assumptions and flawed insights instead of streamlining operations.
The downstream costs include wasted budgets, frustrated customers, dwindling adoption, loss of competitive ground, and reputational damage.
With proper oversight and governance, your CRM data can transform from a liability to a trusted asset.
This guide shares our best practices to protect data quality without overwhelming you. You’ll learn how to align personnel, processes, and tools to ensure CRM data integrity, and give users and management confidence.
Read on to discover how to save your CRM investment from the pitfalls of poor data quality.
Recommendations to Protect CRM Data Quality
Championing CRM data quality requires continuous, concerted effort across policies, system design, automation, analytics, and education.
Here are our key areas for CRM admins to achieve success:
Formalise Data Entry Standards
Document consistent data entry guidelines aligned with your workflows, providing end-user reference details.
Establish centralised oversight for approving changes to enforce uniformity. For instance, if a new option needs to be added to a dropdown list, it should be managed centrally to avoid impromptu design changes.
Optimise System Design and Inputs
Streamline forms with mandatory fields, implement validation checks, and surface capabilities like duplicate finding on entry.
Prioritise user experience in data capture to ensure data quality and adoption. Identify improvements to form layouts to make it easier for everyone to populate records. Avoid overwhelming people with confusing layouts and irrelevant fields.
Only Import Cleansed Data
Avoid importing issues into a new CRM system if your source data is of questionable quality. As data owners, your team understands its nuances and contexts and will likely be best positioned to remediate quality gaps. While partners can provide oversight and tools to uphold governance, internal data stewards should handle the heavy lifting for information integrity.
Construct Role-Based Forms
Balance information visibility and entry burden for different teams interacting with the same records. Following the previous point, consider role-based forms that display only relevant details to guide better data discipline.
For instance, individual sales teams may want to see different information on customer account records. Enabling multiple form views will provide streamlined and personalised views for each.
Evaluate Productivity Tools
Identify plugins and integrations that can auto-populate records from other data sources to minimise manual efforts.
Sales Copilot for Dynamics 365 is one recent example, enabling sellers to easily create new CRM contacts directly from an Outlook message. This can even extract contact information from an email signature to reduce manual data entry.
Another example could be connecting CRM with lookup resources such as Loqate to ensure accurate address details.
Enforce Validation Rules
Configure platform validations on field formats, incomplete details, out-of-range inputs, and custom requirements. These safeguards will catch errors upon submission before they persist.
Activate Deduplication Safeguards
Configure CRM duplicate detection, fuzzy matching, and merge capabilities to consolidate records.
Ensure end-users receive guidance when potential duplicates are discovered and understand what to do when records should be merged.
Develop Data Quality Tracking Views
CRM admins should have access to reports and dashboard views that detect anomalies in recent records, like incomplete details or potential duplicates, for rapid remediation.
A CRM partner, such as ServerSys, can assist in creating these recurring resources to help administrators keep on top of their data management.
Formalise Data Retention Cadences
Systematically review and archive obsolete CRM records in line with your data retention policies to preserve quality and optimise storage.
While some records must be retained for regulatory and compliance purposes, older data can potentially be removed from your live CRM system. Automated processes can be configured to identify matching records in line with defined retention rules, enabling CRM admins to safely delete or archive as appropriate.
CRM Training and Support
Pursue training and use expert resources to uplift your data management capabilities. Engaging with a partner will help fill knowledge gaps and provide ongoing support to make data quality analysis and improvement a coordinated, continuous process.
Next Steps
ServerSys can help you address these issues by deploying a strategy to assess your governance gaps, prioritise fixes, and provide solutions so you can rely on the data you depend on for success. Contact us to start the conversation.
