The Data Quality Audit: Assessing Your HubSpot Health

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The Complete Guide to Auditing Your HubSpot CRM for Better Performance

Before you can fix data quality problems, you need to know where they are. Today's guide walks you through a comprehensive audit of your HubSpot CRM—creating the baseline metrics that will measure your progress toward AI readiness.

Why Conduct a Data Quality Audit?

A data quality audit isn't just about finding problems—it's about understanding your data's current state so you can:

1. Prioritize efforts – Focus on high-impact issues first
2. Measure progress – Track improvement over time
3. Justify investment – Demonstrate ROI of data quality initiatives
4. Enable AI – Understand readiness for AI feature adoption

The Bottom Line: You can't manage what you don't measure. This audit creates your data quality baseline.

What Should a Data Quality Audit Include?

The Five Dimensions of Data Quality

Your audit should evaluate data across five dimensions:

How to Conduct a HubSpot Data Quality Audit

Phase 1: Dashboard Review (15 minutes)

Step 1: Access the Data Quality Dashboard

1. Navigate to Data Management > Data Quality
2. Set date range to Last 90 days for initial review
3. Note the summary metrics:
   • Total duplicate issues
   • Total formatting issues
   • Property insights summary

Step 2: Document Your Current State

Create a simple tracking document with these baseline metrics:

DATA QUALITY AUDIT - [DATE]============================DUPLICATES- Contact duplicates detected: ____- Company duplicates detected: ____FORMATTING ISSUES- Total formatting issues: ____- Top issue type: ____PROPERTY HEALTH- Total active properties: ____- Properties with issues: ____- Unused properties: ____

Phase 2: Duplicate Analysis (30 minutes)

Step 1: Review Duplicate Volume

1. Click the Manage Duplicates tab
2. Note total Contact duplicates
3. Note total Company duplicates
4. Calculate duplicate percentage: Duplicate % = (Duplicates / Total Records) × 100
5. Target: Less than 2%

Step 2: Analyze Duplicate Patterns

Review a sample of 20-30 duplicates to identify patterns:

• Are duplicates from specific sources (forms, imports, integrations)?
• Are duplicates caused by name variations or email variations?
• Are there systematic issues (e.g., every integration import creates duplicates)?

Document findings:

DUPLICATE PATTERNS- Primary cause: ____- Secondary cause: ____- Integration-related: Yes/No- Preventable going forward: Yes/No

Step 3: Assess Merge Complexity

For financial services, some duplicates are complex:

• Household members with same last name and address (not duplicates)
• Business contacts at same company (not duplicates)
• Former employees now at different companies (may be duplicates)

Identify how many duplicates require manual review vs. can be auto-merged.

Phase 3: Formatting Issues Analysis (30 minutes)

Step 1: Review Formatting Issues by Object

1. Click the Formatting Issues tab
2. Review Contact issues
3. Review Company issues
4. Review Deal issues (if applicable)

Step 2: Categorize Issue Types

Common formatting issues for financial services:

Document findings:

TOP FORMATTING ISSUES1. Property: ____ | Count: ____ | Auto-fixable: Yes/No2. Property: ____ | Count: ____ | Auto-fixable: Yes/No3. Property: ____ | Count: ____ | Auto-fixable: Yes/No

Phase 4: Completeness Analysis (45 minutes)

Step 1: Identify Critical Properties

For financial services, these properties are typically critical:

Contact Properties:

• Email (required for marketing)
• Phone (required for sales)
• First Name, Last Name (personalization)
• Company (account association)
• Job Title (segmentation)
• Lifecycle Stage (funnel management)

Company Properties:

• Company Name
• Industry
• Annual Revenue / AUM
• Number of Employees
• Website

Step 2: Check Fill Rates

For each critical property:

1. Navigate to Reports > Reports
2. Create a simple report or use existing analytics
3. Calculate fill rate: (Records with value / Total records) × 100

Alternative method using lists:

1. Create a list with criteria: [Property] is unknown
2. Note the count
3. Calculate fill rate: ((Total - Unknown) / Total) × 100

Document findings:

PROPERTY FILL RATESContact Properties:- Email: ____%- Phone: ____%- First Name: ____%- Last Name: ____%- Company: ____%- Job Title: ____%Company Properties:- Industry: ____%- Revenue/AUM: ____%- Website: ____%

Target fill rates for financial services:

• Email: 95%+
• Phone: 70%+
• Name fields: 98%+
• Company: 80%+
• Job Title: 60%+

Phase 5: Property Insights Review (30 minutes)

Step 1: Review Properties to Review

1. Click the Property Insights tab
2. Review the Properties to review table
3. Sort by issue count (highest first)

Step 2: Identify Property Problems

For each problematic property, determine:

• Is this property needed?
• Is the issue data quality or property configuration?
• Should this property be archived?

Step 3: Identify Unused Properties

Unused properties create confusion and clutter. Review:

• Properties with 0% fill rate
• Properties not used in any forms, workflows, or reports
• Properties created for one-time purposes

Document findings:

PROPERTY HEALTH- Properties needing attention: ____- Candidates for archival: ____- Redundant properties: ____

Phase 6: Integration Health Check (30 minutes)

Step 1: List Active Integrations

Document all integrations syncing data to/from HubSpot:

• CRM integrations
• Email integrations
• Form/landing page tools
• Custodian feeds (financial services specific)
• Financial planning software
• Marketing tools

Step 2: Assess Integration Quality

For each integration, evaluate:

Step 3: Identify Integration Issues

Common integration-related data quality problems:

• Integrations creating duplicate records on every sync
• Integrations overwriting manually cleaned data
• Integrations syncing outdated information
• Missing field mappings causing data loss

How to Score Your Data Quality

The Data Quality Scorecard

Compile your findings into a scorecard:

Duplicate Score (25 points)

• < 1% duplicates: 25 points
• 1-2% duplicates: 20 points
• 2-5% duplicates: 10 points
• > 5% duplicates: 0 points

Formatting Score (25 points)

• < 50 formatting issues: 25 points
• 50-200 issues: 20 points
• 200-500 issues: 10 points
• > 500 issues: 0 points

Completeness Score (25 points)

• Average fill rate > 85%: 25 points
• Fill rate 70-85%: 20 points
• Fill rate 50-70%: 10 points
• Fill rate < 50%: 0 points

Property Health Score (25 points)

• < 5 properties needing attention: 25 points
• 5-15 properties: 20 points
• 15-30 properties: 10 points
• > 30 properties: 0 points

Total Score Interpretation:

• 90-100: Excellent – AI Ready
• 75-89: Good – Minor improvements needed
• 50-74: Fair – Moderate work required
• Below 50: Needs Attention – Significant investment required

What to Do With Audit Results

Create a Priority Matrix

Plot issues on an Impact vs. Effort matrix:

High Impact, Low Effort (Do First)

• Automated formatting fixes
• Obvious duplicate merges
• Quick property archival

High Impact, High Effort (Plan Carefully)

• Integration reconfiguration
• Large-scale deduplication
• Data enrichment projects

Low Impact, Low Effort (Quick Wins)

• Minor formatting standardization
• Individual record cleanup

Low Impact, High Effort (Deprioritize)

• Perfect historical data
• Rarely-used property cleanup

Set Improvement Targets

Based on your audit, set 90-day improvement targets:

90-DAY DATA QUALITY TARGETSCurrent Score: ____Target Score: ____Specific Targets:- Reduce duplicates from ____% to ____%- Resolve ____ formatting issues- Improve average fill rate from ____% to ____%- Archive ____ unused properties

Frequently Asked Questions

How often should I conduct a full data quality audit?

• Full audit: Quarterly
• Dashboard review: Weekly
• Spot checks: After major imports or integration changes

Can I automate the audit process?

Partially. HubSpot's Data Quality dashboard automates much of the detection. However, interpretation and prioritization require human judgment, especially for financial services compliance considerations.

What if my data quality score is very low?

Don't panic. Most organizations have data quality issues—the audit simply makes them visible. Focus on high-impact, low-effort improvements first. A low score is your starting point, not your ending point.

Should I pause marketing while cleaning data?

Generally no. Instead:

• Clean the data you use for current campaigns first
• Exclude obviously problematic segments
• Improve quality incrementally alongside normal operations

Your Day 3 Action Items

1. Block 2-3 hours for your initial audit
2. Complete all six phases of the audit
3. Document your baseline using the templates provided
4. Calculate your Data Quality Score
5. Create your Priority Matrix for improvements

What's Next?

Tomorrow (Day 4): We tackle the duplicate problem head-on. You'll learn advanced strategies for HubSpot duplicate management, including AI-powered detection, merge best practices, and prevention strategies for financial services.

Want Expert Help With Your Audit?

Vantage Point offers comprehensive HubSpot Data Quality Assessments for financial services firms. Our certified specialists:

• Conduct thorough multi-system audits
• Identify integration issues
• Create prioritized remediation roadmaps
• Implement sustainable governance frameworks

About Vantage Point

Vantage Point specializes in helping financial institutions design and implement client experience transformation programs using Salesforce Financial Services Cloud. Our team combines deep Salesforce expertise with financial services industry knowledge to deliver measurable improvements in client satisfaction, operational efficiency, and business results.

About the Author

David Cockrum founded Vantage Point after serving as Chief Operating Officer in the financial services industry. His unique blend of operational leadership and technology expertise has enabled Vantage Point's distinctive business-process-first implementation methodology, delivering successful transformations for 150+ financial services firms across 400+ engagements with a 4.71/5.0 client satisfaction rating and 95%+ client retention rate.

• Email: david@vantagepoint.io
• Phone: (469) 499-3400
• Website: vantagepoint.io