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How to Audit Your Marketing Data for Accuracy and Insight
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Data integrity across systems Do your integrations send correct values into HubSpot or your CRM without overwriting accurate fields? Together, these ensure your reports reflect reality and your operations run smoothly. Step 1: Map Your Data Sources Begin your audit by identifying every system that sends data into your CRM. Common sources include: Website forms Landing pages Email marketing tools Sales engagement platforms Event platforms Webinar systems Lead generation partners Paid ads integrations Manual uploads from sales Create a list of all these sources and note what data each sends. This prevents accidental overwrites and helps you identify inconsistencies such as different naming conventions or conflicting lifecycle values. Step 2: Review Your Data Properties Your property structure influences how your CRM functions. Check for property duplication Often, the same field exists twice due to past imports or integrations. For example: Job title vs role Industry vs sector Lifecycle vs lead stage Duplicate fields cause confusion and inaccurate reporting. Check for incomplete or unused properties Any property that is rarely used or contains outdated values should be deleted or merged. Standardise property naming Ensure names are clear, descriptive, and consistent across teams. Step 3: Analyse Record Quality This is the core of your audit. Review all contact and company data for accuracy and consistency. 1. Duplicate records Use HubSpot duplicate management tools to identify and merge duplicates. 2. Missing mandatory fields Define minimum requirements such as: First name Last name Email Company Lifecycle stage Lead source Industry Check how many records fail this requirement. 3. Incorrect lifecycle stages Check whether contacts progress through stages correctly or remain stuck in early stages. 4. Missing associations Many CRMs contain contacts with no linked company. This breaks attribution and segmentation. 5. “Sales engagement platforms or lead providers may overwrite lifecycle stages or owner fields.” Consolidate overlapping lists Too many segments can introduce complexity and errors. Step 8: Audit Reporting Dashboards Your dashboards reflect the quality of your data. Identify reports showing incorrect numbers Common issues include: Mismatched lifecycle stages Double counting contacts Incorrect first touch attribution Inflated lead numbers due to duplicates Outline which reports need correction, then link fixes to the earlier steps of your audit. Step 9: Fix Data with a Structured Cleanup Plan Once issues are identified, create a structured plan to fix them. 1. Standardise property formats Align dropdowns, date formats, and naming rules. 2. Merge or delete unnecessary fields This reduces clutter and improves performance. 3. Clean duplicate contacts and companies Use automated tools and manual review for accuracy. 4. Reassign lifecycle stages Move contacts into the correct stage based on real behaviour. 5. Update inaccurate values Correct job titles, industries, and lead sources to improve segmentation. A cleanup plan turns audit findings into measurable improvements. Step 10: Build an Ongoing Data Quality Framework Data quality is not a one time project. It requires ongoing governance. Create a data owner role Assign responsibility for ongoing maintenance. Set quarterly audits Review properties, integrations, and reporting every quarter. Document data rules Document property definitions, naming rules, and lifecycle logic for cross team alignment. This ensures long term accuracy across marketing, sales, and operations. Bringing It All Together Marketing data is the foundation of every growth decision. A thorough audit uncovers gaps, inconsistencies, and blind spots that prevent accurate reporting and forecasting. When your CRM is clean and structured, your revenue insights become sharper, attribution improves, and sales follow up becomes more reliable.