Several years back, I took over a CRM system that was severely fragmented into distinct silos: the marketing department maintained its own set of contact lists, the sales team had their separate database, and the support division managed yet another independent repository. This disjointed structure led to leadership meetings devolving into contentious debates over the authenticity of each department's data, as everyone questioned whose numbers were truly accurate. The lack of cohesion resulted in overlapping outreach efforts, causing confusion and inefficiency, while critical business opportunities were frequently missed due to the lack of a unified approach. These data silos are more than just a minor inconvenience—they pose a significant threat to the organization's bottom line by directly undermining revenue generation efforts.
By following this three‑step playbook, you’ll:
And no, it’s not just about process—each step delivers measurable gains.
Why It Matters:
Without a clear and comprehensive inventory of all the data properties within your CRM system, you cannot rely on the accuracy or consistency of any report generated. This lack of clarity can lead to significant discrepancies and misalignments in data interpretation across different departments. For instance, in one particular project, the marketing department had developed 50 custom properties tailored to their specific needs. Meanwhile, the sales team had independently created 30 fields that often overlapped with those used by marketing, leading to confusion and redundancy. Additionally, the Customer Success team contributed another 10 properties focused on renewals, further complicating the data landscape. Altogether, this resulted in 90 distinct places where critical data was stored, making it nearly impossible for dashboards to align and provide a cohesive view of the business. This fragmentation not only hampers effective decision-making but also undermines the trust in data-driven strategies.
What to Do:
Navigate to Settings → Properties → Export (contacts, companies, deals) to ensure you have a complete list of all custom properties across different data categories. This step is crucial for gaining a full understanding of the current data landscape.
Once exported, organize the data in a spreadsheet with separate tabs for each department, such as Sales, Marketing, Support, and Customer Success. This organization helps in visualizing which team is responsible for which properties and facilitates easier management and analysis.
Carefully review the data to highlight fields that may have similar purposes but different names, such as Lead Source versus Original Source. Identifying these overlaps is essential for streamlining data and reducing redundancy. Additionally, take note of any fields that are rarely used or obsolete, marking them for potential archiving to clean up the data environment.
Why It Matters:
Even with a meticulously crafted property map, the potential for chaos remains high if edits are made without a structured approach. Uncontrolled modifications can lead to data inconsistencies, misinterpretations, and ultimately, a breakdown in the reliability of your CRM system. By assigning clear ownership of each data field, you establish accountability and prevent accidental or unauthorized edits that could compromise data integrity. This structured ownership ensures that each team understands their responsibilities and the importance of maintaining accurate data, which is crucial for informed decision-making and strategic planning.
What to Do:
Begin by carefully evaluating and deciding which team should have ownership over each key field within your CRM system. For instance, the Marketing team might be best suited to manage the 'Contact Source' field, given their expertise in tracking lead origins and campaign effectiveness. This decision-making process should involve cross-departmental discussions to ensure alignment and understanding of each team's role in data management.
To further safeguard data integrity, navigate to your CRM's Settings, then proceed to Users & Teams, and finally to Roles. Here, you can configure permissions to ensure that only designated owners have the ability to edit specific fields. This restriction minimizes the risk of unauthorized changes and helps maintain a consistent and reliable data environment.
Create and distribute a comprehensive Data Governance Document that outlines the definitions, ownership, and naming conventions for all data fields. This document should be easily accessible to all relevant stakeholders, perhaps shared via platforms like Confluence or Google Drive. It serves as a reference guide to ensure everyone is on the same page regarding data management practices and standards.
Tip: Enhance the document by including practical usage examples. For instance, specify that the "Lifecycle Stage" field can only be updated through a specific workflow or manually by the Sales Operations team. This clarity helps prevent misuse and ensures that data transitions are handled correctly and consistently.
Why It Matters:
Manual fixes are not sustainable in the long run, as they require constant human intervention and can lead to inconsistencies and errors. Automations, on the other hand, are designed to identify and address issues promptly, ensuring that your CRM system remains reliable and trustworthy. By implementing automated processes, you can maintain data integrity, reduce the risk of human error, and ensure that your CRM continues to function smoothly and efficiently.
What to Do:
Quarterly Property Review: Dedicate 30 minutes each quarter to thoroughly examine and manage your CRM properties. During this time, focus on identifying fields that are no longer in use or have become redundant. Take the opportunity to archive these fields or merge them with existing ones to streamline your data structure and enhance overall system efficiency. This regular maintenance ensures that your CRM remains organized and relevant, supporting effective data management and decision-making.
Monthly Data Huddle: Schedule a concise 15-minute meeting every month with key operations stakeholders to collaboratively review the latest data health reports. This brief yet focused session allows your team to discuss any emerging data issues, evaluate the effectiveness of current data management strategies, and make informed decisions on necessary adjustments. By maintaining open communication and regular check-ins, you can proactively address potential data challenges and ensure the ongoing integrity of your CRM system.
Form Templates: Leverage HubSpot's form templates to establish and enforce high standards of data quality right from the point of capture. By designing forms with predefined fields and validation rules, you can ensure that the data collected is accurate, complete, and consistent. This proactive approach to data entry minimizes errors and discrepancies, laying a solid foundation for reliable data analysis and reporting.
Are you ready to take decisive action and thoroughly clean up your HubSpot data once and for all?