How to Validate Emails at Scale in Salesforce: A Step-by-Step Guide for Admins

Invalid email addresses waste marketing spend and sales time. Bounces hurt your sender reputation, inflate your contact counts, and send reps chasing prospects who don't exist. Bad email data gets into Salesforce from web forms, imports, and manual entry, constantly.

Salesforce's native tools catch some of this. For validation at scale, real-time checks, bulk processing, and ongoing hygiene, Plauti runs email verification directly inside Salesforce.

Prerequisites

Before you build anything, make sure you have:

• Salesforce admin permissions.
• Access to Leads, Contacts, and any custom object with email fields.
• A sandbox for testing validation rules, strongly recommended before you touch production.
• Optional: a sample set of records with known invalid emails, for testing.
• For real-time or bulk validation, know your email sending volume and any compliance requirements first.

4 steps to validate emails with native Salesforce tools

These steps use tools already in your org. No installation required.

Step 1: Set up basic email format validation

Create a validation rule that catches obvious format errors before a record saves.

• Go to Setup, then search for "Validation Rules".
• Select the object (Lead, Contact, or Account).
• Click New to create a rule.
• Use a formula like NOT(REGEX(Email, "^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$")).
• Add an error message: "Please enter a valid email address format."

This catches basic format issues. It won't tell you whether the address actually exists or can receive mail.

Step 2: Find problem patterns with reports

Surface the email issues already sitting in your database.

• Create a new Contact or Lead report.
• Add filters for the patterns you want to catch:
  • Email contains "test"
  • Email contains "noreply"
  • Email contains "example.com"
  • Email ends with ".con" (a common typo for .com)
• Add a filter for Email not equal to blank.
• Save the report as "Potential Invalid Emails" so you can reuse it for ongoing monitoring.

Step 3: Set up bounce handling (if you use Marketing Cloud)

Configure bounce management to identify addresses that can't receive mail.

• In Marketing Cloud, go to Email Studio > Admin > Delivery Profiles.
• Enable Bounce Management on your delivery profile.
• Set bounce categories (hard bounce, soft bounce, and so on).
• Configure automatic suppression for hard bounces.
• Build a report to track bounce rates by campaign and time period.

This only helps for mail sent through Marketing Cloud. It won't catch bad addresses that came in through an import or a web form that doesn't route through Marketing Cloud.

Step 4: Clean up manually

For data you already have, review and fix suspicious addresses by hand.

• Pull the report from Step 2 to find problem records.
• Export the data to a spreadsheet for bulk editing.
• Fix obvious typos (gmial.com to gmail.com).
• Delete or flag addresses that are clearly fake.
• Re-import the cleaned data.

Add a custom field, such as Email_Status__c, to track validation results and keep a history of your cleanup work.

Limitations of native Salesforce email validation

Salesforce's built-in tools give you basic coverage, with real gaps:

• Format-only validation: rules check if an email looks right, not whether it actually works.
• No real-time verification: you can't confirm an address exists and can receive mail while it's being entered.
• Manual cleanup required: fixing existing bad data means reviewing and correcting it by hand.
• Limited bulk processing: there's no native way to validate thousands of addresses at once.
• No ongoing hygiene: an address can go bad after it's saved, and nothing flags that automatically.
• Bounce tracking gaps: bounce management only works for mail sent through Marketing Cloud. It misses web forms, imports, and API integrations.
• No domain validation: nothing checks whether the domain exists or has mail servers configured.
• Missing advanced patterns: native regex can't catch disposable email services or more sophisticated fake addresses.

Prevent and clean up bad emails with Plauti

Plauti runs email verification inside Salesforce, without exporting records to an external tool. It checks format, domain, and mailbox status in real time or in bulk, and writes the result back to the record.

What Plauti checks

• Real-time verification: confirm an address exists and can receive mail as a user enters it.
• Bulk validation: process thousands of addresses in minutes.
• Format and syntax checks: catch typos and invalid patterns automatically.
• Domain verification: confirm the domain exists and has mail servers configured.
• Disposable email detection: flag temporary or throwaway addresses.
• Role account detection: flag generic addresses like info@, admin@, or noreply@ that may not be monitored.
• Validation date tracking: store the date and time an email was last checked in a custom Date/Time field, so you know when a record is due for a recheck.
• Works with your existing entry points: web-to-lead, imports, API integrations, and manual data entry.
• Confidence scoring: get a status code and confidence level for each result, not just a pass or fail.
• Runs inside your org: no export step, with a full audit trail.

15-minute setup: real-time and bulk validation

Setting up real-time and bulk validation takes about 15 minutes, across four steps.

Step 0: Test in a sandbox

• Install Plauti in a sandbox from AppExchange.
• Run validation on a small sample (50-100 email addresses).
• Review the validation results and confidence scores.
• Test real-time validation on a web form or through manual data entry.

Step 1: Install and configure permissions (5 minutes)

• Install Plauti from AppExchange into your production org.
• Assign the Plauti permission set to admins and any user who needs access.
• Create a custom Date/Time field on each object where you want to track the last validation date.
• Open the Plauti app from the App Launcher.
• In setup, map your email field (for example, Email) and the custom Date/Time field that will store the validation date.
• Configure validation settings, and map fields to store the status code, status message, and validation date.

Step 2: Set up real-time validation (5 minutes)

• Choose your objects (Leads, Contacts, Accounts).
• Enable real-time validation for the email field.
• Decide when validation runs: on create, on update, or both.
• Configure what happens automatically based on the status code it returns. For example:
  • Status is "Invalid": clear the email field, set a custom status field, or add the record to a "Needs new email" queue.
  • Status is "Risky": leave the email in place, but flag it for manual review.
• Decide when that automatic action runs: when batch job results come in, or as soon as each record is validated.
• Test with a sample record and confirm the status code is set as expected, the validation date is written to your custom field, and the automatic action runs correctly.

Step 3: Process existing invalid emails (5 minutes)

• Select records with email addresses, using the reports from your native cleanup.
• Choose what to validate (email, phone, address). Usually just email.
• Run the bulk validation job.
• When the results come in, use automatic actions to handle status codes at scale: clear addresses that are clearly invalid, or mark others for follow-up.
• Review a sample of the results for quality control.
• Schedule a recurring job if you want ongoing validation for a specific segment, such as key accounts or active customers.

Get started

Start in a sandbox. Run native validation rules against a sample of your Lead and Contact records, then compare the results against a real-time check to see what format-only validation misses on the same data.

From there, decide where you need coverage: catch bad addresses at the point of entry, clean up what's already in your CRM, or both.