Use Entity Resolution to clean your data by detecting and managing duplicate or related records across systems—ensuring a single source of truth in your entity store.
What is Entity Resolution?
Entity Resolution is the process of identifying and merging duplicate or related records across data sources based on similarity. This helps:
Maintain data accuracy and reduce redundancy.
Improve reporting fidelity and attribution precision.
Enable consistent records for downstream analytics and workflows.
Step-by-Step Guide
1. Launch Entity Resolution
Go to Config Center > Entity Resolution.
View existing configurations or click + Entity Resolution to start a new one.
2. Define the Configuration
a. Select Entity
Choose the data entity where you want to perform deduplication or linking:
Lead
Campaign
Account
Tip: Only one entity can be resolved per configuration. Each configuration will replace the corresponding table in the entity store.
b. Enter Config Name
Name your configuration clearly, e.g., Lead Dedupe - Q2 or Campaign Cleanup - LinkedIn.
c. Choose Resolution Type
Deduplication: Identify and merge duplicate records into a single master record.
Linking: Establish a relationship across similar records from multiple systems (non-destructive).
3. Set Matching Conditions
a. Select Source Systems
Pick one or more source systems (e.g., Salesforce, HubSpot, LinkedIn, Marketo).
b. Add Filters (Optional)
Refine the dataset using custom filters like:
Campaign Cost Type contains "CPC"
Status equals "Active"
Tip: Use filters to focus deduplication on a subset of high-impact records or time-bounded campaigns.
c. Define Matching Logic
Choose dimensions and matching types:
Dimensions: Fields such as Campaign Name, Email, and Account ID.
Match Type:
Exact Match: Use for stable identifiers, such as email addresses or UUIDs.
Fuzzy Match: Ideal for fields prone to human variation (e.g., names, titles).
Best Practice: Combine exact and fuzzy matches on multiple dimensions for higher accuracy and lower false positives.
4. Set Frequency
Determine when the resolution process runs:
Every data sync completion: Keeps data fresh automatically.
Specific time: For manual or scheduled resolutions.
5. Analyze and Adjust
Review proposed merges manually:
See which records are marked as duplicates.
Pick the “master record” to retain.
Preview merged data before committing.
Key Benefit: Avoids blind automation—puts you in control of the outcome.
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6. Confirm and Finalize
Final confirmation will trigger the overwrite of the respective table in the Entity Store.
The updated dataset will now be available to all downstream analytics and tools.
A success message confirms your records are clean and ready!
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Advanced Insights & Recommendations
When to Use Deduplication vs. Linking
Scenario | Choose |
|---|---|
Duplicate leads from the same source | Deduplication |
Same account from Salesforce & LinkedIn | Linking |
Repetitive campaigns across tools | Deduplication |
Suggested Match Dimensions by Entity
Entity | Recommended Dimensions |
|---|---|
Lead | Email, Phone Number, First Name |
Campaign | Campaign Name, Start Date, Campaign Type |
Account | Account Name, Domain, Industry |
FAQ
Q: Will this impact existing data models or reports?
A: Yes—since the table in the Entity Store is overwritten, ensure your resolution logic aligns with reporting needs.
Q: Can I undo a merge?
A: Yes, you can undo a merge. Changes can be undone if the config is deleted.
Q: Can I export the resolved data?
A: Resolved records become part of the underlying data warehouse; they can be accessed via integrated tools or export features.