Matching and merging Salesforce duplicates with Dedupely

Deduplication is about ensuring the right duplicates are matched, merged, or preserved in a way that supports your org's processes. A good deduplication process protects ownership, respects record types, and keeps related data connected, all while removing the noise from your database.

With Dedupely, you can define precise match logic, apply filters that protect high-value records, and merge with rules that align to Salesforce’s behavior and, at the same time, allow you to control what values win or lose during the merge.

This guide walks through how to build match and merge strategies in Dedupely for Salesforce that protect data integrity and keep your org working as expected. Every decision, from match logic to merge rules, impacts how records behave in Salesforce:

• Match logic affects ownership, automation, and reporting
• Merge rules decide which fields and relationships are kept
• Filters protect active records from being merged too soon

Free resource: Dedupely’s matching cheat sheet for Salesforce admins

Before you get started, grab this free PDF. It includes ready-to-use match and merge setups, Salesforce-specific examples, and step-by-step processes you can apply directly in your org.

What good deduplication looks like inside Salesforce

Good deduplication in Salesforce keeps records accurate, relationships between objects intact, and workflows running without disruption. Every merge should improve the data and maintain the trust of the teams who use it.

In practice, that means:

• Match logic is defined, tested, and easy to explain, with object-specific rules that account for how Leads, Contacts, and Accounts are structured in Salesforce.
• Each object has its own deduplication strategy: Leads might rely on form submission fields, Accounts on domain + name logic, and Contacts on email + phone.
• High-risk merges are excluded with filters, such as open Opportunities, active Cases, or recent Activity records.
• Relational data is preserved: Ownership, related Opportunities, Campaign history, and other dependencies remain linked after the merge.
• Deduplication happens on a schedule: Recurring scans and merges in Dedupely address issues before they affect reporting or team operations.
• Merge types are clearly defined: Safe, low-risk groups are handled with auto merges, while high-value or complex records are manually reviewed.

Common risks to avoid when deduplicating in Salesforce

Even with the right tools, deduplication in Salesforce can introduce problems if certain risks aren’t addressed. These risks often come from the platform’s interconnected data model and how different teams depend on shared records.

Key risks to avoid:

• Merging records with active sales or service activity: Such as open Opportunities, live Cases, or pending Quotes, which could disrupt deal cycles or customer support.
• Combining records across ownership boundaries: Reassigning an Account, Lead, or Contact without considering territory rules or assignment workflows can create friction between teams
• Over-reliance on single-field matching: Names and phone numbers can be inconsistent, leading to false positives or missed duplicates.
• Ignoring object-specific constraints: For example, Account merges can re-parent Contacts and Opportunities, while Lead merges follow different conversion paths.
• Merging without preserving key historical data: Campaign history, activity logs, and custom field values may be lost if merge rules aren’t configured to retain them.
• Automating merges without testing logic: Auto merging untested Search Pads can cause large-scale data changes that are difficult to reverse

Proactively managing these risks ensures deduplication strengthens data quality instead of introducing new problems.

How to build better match logic in Dedupely for Salesforce

In Dedupely, all matching happens inside Search Pads; this is where you decide what counts as a duplicate in Salesforce. The goal is to create logic that reflects how your org enters and maintains Leads, Contacts, and Accounts, so only true duplicates are matched together.

Building strong match logic inside a Search Pad

1. Pick your Salesforce object
   1. Each Salesforce object (Lead, Contact, Account) stores different types of relationships and data, so one logic set doesn’t fit all.
   2. Create separate Search Pads for Leads, Contacts, and Accounts so each can have tailored field combinations.
   3. For example, Leads might match on Email + First Name, while Accounts match on Website Domain Root + Company Name.
2. Choose your fields
   1. The fields you choose define the “fingerprint” of a duplicate. Choosing only one field can lead to false positives.
   2. Use at least two fields that, together, uniquely identify a record.
   3. For example, Email + First Name for Leads, or Company Name + Phone for Accounts.
3. Set the match type per field. Dedupely lets you decide how strict each field comparison should be:
   • Exact: Use for fields that must match perfectly to avoid errors. Example: Email on Leads, Account ID on Accounts, or CRM Owner ID when preserving record ownership.
   • Similar: Use when you expect small variations, but the base value should be mostly the same. Example: “Jonathan” vs. “Jonathon” in First Name, or “Acme Corp” vs. “Acme Corporation” in Account Name.
   • Fuzzy: Use for legacy or imported data where formatting is inconsistent. Example: catching “J Smith” vs. “John Smith” in Contact Name fields, or “123 Main St.” vs. “123 Main Street” in Address.
   • Similar Word: Use for company names or descriptions where individual word matches matter more than the whole string. Example: matching “Global Tech Solutions” with “Tech Solutions Global.”
   • Domain Root: Use for Account Websites to catch domain variations common in Salesforce data. Example: “acme.com” vs. “mail.acme.com” or “acme.co.uk” vs. “acme.com.”
4. Add filters to protect key records
   1. Filters prevent high-risk records from being matched or merged. This avoids disrupting active deals or service cases.
   2. For example, exclude Contacts with open Opportunities or Accounts with active Cases. This way, live deals aren’t accidentally merged mid-cycle.
5. Run your Search Pad
   1. Running the scan shows you how your logic behaves before merging.
   2. A good result catches obvious duplicates and avoids unrelated records, such as two companies with the same generic name but different domains.
6. Save and document the logic
   1. Clear naming and documentation mean other admins can use your Search Pads without guessing what they do.
   2. For example, name your Search Pad “Leads – Email + First Name – Similar,” and in the description, note the match types, filters, and when to run it.

By designing match logic in Search Pads this way, you can match duplicates that Salesforce’s native matching might miss, while keeping complete control over accuracy and merge safety.

How to merge in Dedupely (and when not to)

In Salesforce, a merge can affect far more than the records themselves, it can shift ownership, update related objects, and impact reporting. Dedupely’s merge process gives you the steps and controls to make sure the right record is kept, the right fields win, and nothing critical is lost.

How to merge in Dedupely:

1. Review matched duplicates first: Open your Search Pad results and scan the match groups for anything unusual. Spot-check high-value records or anything with open deals.
2. Select records to merge: Choose the duplicates you’re confident about. Keep the record with the most complete and accurate data as the primary.
3. Confirm field retention rules: Dedupely applies your merge rules (see Merging with control in Dedupely for Salesforce below) to decide which field values win. Review these before approving the merge.
4. Run the merge: Merges are pushed to Salesforce in real-time, respecting your object relationships and field mappings.
5. Audit the results: Check that merged records appear in Salesforce as expected — especially on related records like Activities, Opportunities, and Cases.

When not to merge:

• The match group contains records with conflicting high-value fields that can’t be resolved without further review
• The primary record choice isn’t clear
• The records belong to different accounts, divisions, or territories and may have different owners
• A merge could disrupt integrations, automation, or reporting tied to specific record IDs

Merge with control in Dedupely for Salesforce

Merge rules in Dedupely give you control over what happens when Salesforce records are combined. Instead of every merge being handled the same way, merge rules let you define outcomes that respect your data model and keep records reliable after the merge.

At a high level, merge rules let you:

• Decide what field values win or lose: For each field, you can apply “win” or “lose” logic. For example, you might keep the most recent Lead Owner while also keeping the oldest Created Date to preserve customer history.
• Protect related records: Activities, Campaign History, and related lists are always attached to the chosen primary record, ensuring continuity for reporting and operations.
• Control ownership: If no rule is applied, the owner of the primary record is kept. But you can override this if your process requires different assignment logic.

Good merge rules balance consistency with flexibility. They prevent unexpected data loss while making sure merged records stay aligned with Salesforce workflows.

Example scenarios where merge rules matter:

• Keeping the most recent contact details when merging multiple inbound Leads
• Preserving the full customer history by retaining the earliest Created Date
• Ensuring original record ownership is respected so team assignments remain accurate

Examples of strong match + merge strategies in Dedupely for Salesforce

Instead of treating deduplication as a one-time process, you can build repeatable strategies that align with how your Salesforce data is created, used, and reported.

Example 1: Inbound Lead processing

High-volume lead generation often means duplicates slip in through web forms or integrations. Without early deduplication, Sales ends up chasing the same prospect multiple times.

• Match: First Name + Last Name + Email: Exact match
• Filter: Created in the last 30 days
• Merge: Auto merge daily for integration-created leads

Example 2: Quarterly Account consolidation

Over time, Salesforce Accounts can become duplicated or inconsistent, especially in larger orgs. This setup allows Ops to consolidate safely without touching active deals.

• Match: Account: Similar match + Domain root match
• Filter: Last activity > 6 months
• Merge: Manual merge by the Ops team

Example 3: Contact cleanup before campaign sync

Before pushing contacts into Marketing Cloud or campaign lists, duplicates can skew counts and inflate costs. This deduplication process makes campaign targeting more reliable.

• Match: First Name + Last Name + Phone: Exact match
• Filter: Exclude contacts with recent Activity (last 30 days)
• Merge: Bulk merge with manual approval

Run your setups on repeat, keeping pipelines, accounts, and campaigns clean where it matters most.

When duplicates are handled with precision in Salesforce reports become accurate, dashboards reflect reality, and end admins stop questioning the system.

The key is to start small: test your Search Pads, run controlled merges, and validate results. Once you’re confident, scale those setups to larger datasets or run them automatically. Dedupely gives Salesforce admins a repeatable framework for high-quality merges: flexible rules, tested strategies, and filters to protect active records, so your Salesforce org stays lean, accurate, and trusted by everyone who depends on it.