Salesforce Duplicate Management vs. Plauti Deduplicate: 2025 Enterprise Guide

The definitive, enterprise-focused comparison of native Salesforce Duplicate Management and Plauti Deduplicate

Key definitions

Matching rules

• Define which fields to compare and how: exact or fuzzy. Example: Email exact; Account Name fuzzy.

Duplicate rules

• Define what happens when a match is found: alert or block. Create duplicate items for reporting.

Duplicate jobs

• Admin-run scans that identify duplicates and allow action via Compare and Merge.

Duplicate record sets

• Native groups of suspected duplicates are used to review and merge.

What Salesforce native does well

• Prevention at the point of entry (UI, imports, API) using matching and duplicate rules.
• Customizable rules per object; supports exact and fuzzy matching.
• Manual cleanup via Duplicate Jobs and Compare and Merge for core CRM objects.

Where native tools fall short for enterprises

• Manual-heavy cleanup that becomes time-consuming for large data volumes.
• No cross-object dedupe (e.g., Lead-to-Contact-to-Account).
• No native merge for custom objects.
• Limited automation and governance (no policy-driven auto-merge, approvals, or rollback).

Plauti Deduplicate: enterprise-grade capabilities

Advanced matching

• Multi-field strategies, exact/fuzzy/phonetic, domain-aware patterns.
• Cross-object rules (Lead-to-Contact-to-Account) for holistic cleanup.

Automation

• Scheduled jobs. Policy-driven auto-merge and auto-convert.
• Works for UI/API loads and common integrations (web forms, MAPs).

Scale and performance

• Built for large data volumes with efficient indexing and batching.
• Optional local processing to accelerate large jobs.

Governance and control

• Master selection policies (completeness score, recency, source-of-truth).
• Audit logs, approval flows, and rollback safeguards.

Custom objects

• Merge across standard and custom objects; reliably reparent related records.

AI assistance

• AI Merge Recommendation suggests optimal field values during Manual Merge (available on select editions).

Enterprise use cases

• Lead hygiene at scale: Prevent duplicates from forms and MAPs; auto-convert qualified duplicates; preserve attribution and history.
• Post-merger consolidation: Unify Accounts, reparent Contacts and related objects; resolve conflicts via policy.
• Service and call centers: Reduce handle time by removing duplicate Contacts/Cases; add approvals for sensitive merges.
• Custom object scenarios: Merge custom objects and reparent related records without losing context.

Implementation best practices

1) Establish prevention first

• Configure matching (exact/fuzzy) and duplicate rules (alert or block) per object.
• Enable duplicate reporting for visibility and follow-up.

2) Segment cleanup

• Start with high-impact slices (e.g., Leads with email, Accounts by domain); expand by region/business unit.

3) Master selection policy

• Define deterministic criteria (completeness score, activity recency, source-of-truth).

4) Automate safely

• Pilot conservative auto-merge/convert policies; review results; scale incrementally.

5) Govern & audit

• Log merges; store before/after snapshots; add approvals for regulated data.

6) Iterate quarterly

• Track false positives/negatives; tune match weights and filters; review policies.

People Also Ask (Frequently Asked Questions)

Can Salesforce match on custom fields?

Yes. Matching and duplicate rules can include custom fields and apply to custom objects.

Can Salesforce merge custom objects?

No. Native merge is limited to Account, Contact, and Lead; use third-party tools for custom objects.

Does Salesforce support cross-object dedupe (Lead-to-Contact)?

No. Use a third-party solution for cross-object matching and conversion.

Why is native cleanup effort-heavy?

Duplicate Jobs are manual and object-bound; large datasets require extensive review.