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Cross-object duplicate detection requires analyzing shared custom identifiers across contacts, companies, and deals simultaneously. This capability is completely unavailable in HubSpot’s native duplicate detection, leaving data integrity issues hidden within individual object silos.
Here’s how to set up comprehensive cross-object duplicate detection that reveals relationship problems and ensures proper data connections across your entire HubSpot ecosystem.
Set up multi-object duplicate analysis using Coefficient
Coefficient enables comprehensive cross-object duplicate detection through multi-object imports and advanced formula capabilities, revealing data integrity issues that impact customer experience and business operations.
How to make it work
Step 1. Import comprehensive multi-object data.
Import contacts, companies, and deals from HubSpot with shared custom identifier fields. Include object-specific metadata like creation date, source, and owner for context analysis. Apply consistent filtering across all objects for relevant record subsets to focus your analysis.
Step 2. Create cross-reference analysis systems.
Compile all custom identifiers across objects using =UNIQUE() functions to create a master identifier list. Set up object mapping to track which objects contain each shared identifier. Add relationship validation to verify proper HubSpot associations exist between objects sharing identifiers.
Step 3. Build advanced cross-object formulas.
Use multi-object counting: =COUNTIF(Contacts_CustomID,A2)+COUNTIF(Companies_CustomID,A2)+COUNTIF(Deals_CustomID,A2) to see identifier distribution. Create object distribution analysis to identify identifiers appearing in unexpected object combinations. Add orphaned record detection to find objects with shared identifiers lacking proper associations.
Step 4. Identify complex duplicate scenarios.
Set up customer lifecycle tracking where the same customer ID appears as contact, company, and multiple deals. Detect account management issues where multiple contacts with the same company identifier aren’t properly associated. Find sales process gaps where deals have customer IDs not linked to corresponding contacts or companies.
Step 5. Implement cross-object validation rules.
Enforce business logic where customer IDs should appear in contacts AND companies, not deals alone. Add hierarchy validation to ensure parent-child relationships are properly reflected across object types. Include timeline consistency checks where creation dates are logical across related objects.
Step 6. Set up automated monitoring and reporting.
Configure comprehensive alerts when new cross-object duplicates are detected. Set up workflow integration to trigger HubSpot workflows based on cross-object duplicate status. Create escalation protocols with different alert levels for various cross-object scenarios.
Step 7. Create data integrity reporting and resolution.
Generate cross-object health scores showing the percentage of shared identifiers with proper object relationships. Perform gap analysis to identify missing objects in customer lifecycle representation. Use Coefficient’s association management to link related objects and consolidate data while preserving relationships.
Reveal hidden data integrity issues across your entire ecosystem
This cross-object duplicate detection provides unprecedented visibility into data relationships across your entire HubSpot ecosystem, revealing and resolving integrity issues that impact customer experience. Get started with Coefficient to uncover the hidden duplicate problems in your data.
