
Case studies
How Xerox Improved Global Data Integrity in Salesforce
Xerox's global CRM team cleaned up cross-team duplicate records in Salesforce, then added prevention so marketing targeting and client reporting stay accurate as the company scales.

Duplicates get into Salesforce from web forms, imports, and manual entry. Reps end up calling the same lead twice, automations trigger off stale records, and reports stop matching what's actually in the pipeline.
Salesforce's built-in tools can find and merge duplicates without any extra software, and the first half of this guide walks through that setup. When volume, custom objects, or ongoing prevention push past what those native tools handle, the second half covers how Plauti takes over that work inside Salesforce, without exports or scripts.
Before you start, you'll need:
Every Salesforce org ships with duplicate detection and a merge tool built in. Here's how to turn them on and put them to work.
Salesforce's built-in duplicate detection has to be switched on before it does anything.
Combining fields (email, name, and company together) catches more true duplicates than matching on any single field.
This setting controls what happens when a user tries to save a duplicate through the Salesforce UI.
Records arriving through Web-to-Lead, the Data Import Wizard, Data Loader, or the API follow a different rule. Salesforce hard-blocks a detected duplicate outright: there's no alert, no override, and no separate configuration for these channels — blocking applies even if your rule is set to Alert in the UI. That has a real cost. If someone submits your web form twice, only the first submission gets created, and whatever changed between the two submissions is lost.
Next, track down the duplicates already sitting in your org.
Consolidate the duplicates into a single record.
Salesforce can often restore a deleted record after a merge, but double-check before you confirm one. Prevention is cheaper than cleanup.

Plauti brings the same idea — find, merge, and prevent duplicates — to a scale native tools weren't built for.
Test it first: install Plauti in a sandbox, run a scan on a small sample (a Lead segment works well), and review the matches and merge scenarios before touching production.
From there:
Before:
After:

Case studies
Xerox's global CRM team cleaned up cross-team duplicate records in Salesforce, then added prevention so marketing targeting and client reporting stay accurate as the company scales.

Blog
Deduplication rules give predictable merges but can't judge context. AI Merge Recommendations suggest which field to keep; a person still approves every merge.
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