Module Overview: Merge Duplicates

When records are merged using Insycle, the properties are consolidated and follow similar logic across all record types on all CRMs:

• Fields/Property values: 
  • By default, the value is retained from the master. When a value is empty in the master, it picks a non-empty value from the most recently updated duplicate. All other values are available in the history.
  • To customize how field data is retained in the master record on a field-by-field basis, use the Field tab under Step 3.
• Associated items: Reassigned from the duplicates to the master.
• Activities (notes, emails, tasks, etc.): Reassigned from the duplicates to the master.
• Attachments: Reassigned from the duplicates to the master. (Note that there may be a short delay before the attachment appears in the merged record.)

See the CRM-specific articles for any further details:

• HubSpot Merge Duplicates Overview
• Salesforce Merge Duplicates Overview
• Pipedrive Merge Duplicates Overview
• Intercom Merge Duplicates Overview
• Mailchimp Merge Duplicates Overview

When merging duplicates, Insycle goes through the following steps for all record types and database types:

1. Select the master record according to the rules set in Step 3 on the Master tab.
2. Determine field values to retain in the master record based on rules configured in Step 3: Merge Logic, Fields tab.
3. For fields without specific rules, identify non-empty values using a "fill in the blanks" method:
   • Check whether the master record has any empty fields.
   • If empty, copy values from the most recently updated record in the duplicate group.
4. Update the master record by:
   • Applying the field values chosen in #2 (from Field rules).
   • Adding the non-empty values identified in #3 (using "fill in the blanks").
   • Preserving all other existing values in the master record.
5. Merge the duplicate records and reassign all related objects to the master record.
6. Store an audit trail report accessible from the Activity Tracker and send an email notification to the designated recipients.

Though you can create custom data retention rules for any record fields using the Fields tab under Step 3, it is not required. There is no need to create rules for every field in your CRM - Insycle automatically handles fields without specific rules with a "fill in the blanks" approach. 

When the master record has empty fields, Insycle copies values from the most recently updated record in the duplicate group where that data exists. For example, if the master record's Industry field is empty but another record in the duplicate group has an Industry value, that value will automatically be copied to the master record. 

This means you only need to create custom retention rules for the fields that require special handling, rather than setting up rules for all your fields.

Step 1 is where you define which fields Insycle should examine to find duplicate records, and set the rules for how those fields are compared. Each field you add is cumulative — records must match all of the criteria you specify to be flagged as potential duplicates. For example, matching on First Name AND Last Name AND Phone Number returns only results where all three values are the same.

Step 1 operates through three tabs:

• The Simple tab is where you add matching fields and configure comparison rules, ignored elements, match parts, and conditions.
• The Advanced tab is where you configure Related Fields for any field already added on the Simple tab.
• The Conditions tab is where you set conditions for any field already added on the Simple tab.

A field must be added on the Simple tab before it can be configured on the Advanced or Conditions tabs.

See the Duplicate Identification Rules Reference below for a complete breakdown of every option.

Additionally, Step 1 includes a CSV tab that lets you upload a file of known duplicate record ID pairs directly — bypassing field-based matching entirely. See the CSV Tab Reference below for details.

Step 2 displays all duplicate groups identified in Step 1, allowing you to review and verify the matches before proceeding. Records that match your Step 1 criteria are automatically clustered into duplicate groups — each group represents a single entity and shows how many duplicate records it contains. For example, four records for the same person would appear as a single duplicate group containing four records.

Click the chevron  at the right end of a duplicate group row to expand it and examine the individual records within that group. You can also add more fields as columns to give yourself further context when evaluating the matches.

To exclude a duplicate group from all future deduplication analysis, click the X on the group row. Excluded groups will not appear as duplicates or be included in merges, even when using different duplicate detection templates. To review and manage excluded groups, click the Exclusions button in the Step 2 header.

Step 3 is where you configure how duplicate groups are consolidated—from choosing your operation mode to defining master selection rules and field retention logic. This step combines operation selection with the merge logic configuration through multiple tabs.

At the top of Step 3, choose between Bulk and Manual modes in the header:

Bulk mode (recommended) automatically merges all duplicate groups according to the master record selection rules you define in the Master tab. This is the right choice for most deduplication processes, and the only mode that supports templates, Recipes, and automation.

Manual mode lets you review and select specific records to merge individually from the Record Viewer. Reserve this for high-value records or complex scenarios where you want hands-on control over each merge.

Step 3 operates through three tabs that work together:

Master tab — This is where you set the rules that determine which record in each duplicate group becomes the master. Insycle evaluates your rules in order from top to bottom, and the first record that uniquely matches a rule becomes the master. If no record matches any rule, master selection fails for that group. See the Master Record Selection reference below for a full breakdown of all rules and options.

At the bottom of the Master tab, you'll also configure:

• Processing method — Choose between By Priority (evaluates rules in sequence, stops at first unique match) or Absolute (master must match all rules). Most operations should use By Priority.
• Exclusions — By default, Insycle skips any duplicate group containing more than 5 records—this prevents overly broad matching criteria from accidentally merging unrelated records. You can adjust this threshold up to 100 records per group.

Fields tab — This is where you control which field values end up in the master record after the merge. By default, Insycle keeps the master record's values and fills any empty fields with values from the most recently updated duplicate. You can override this on a field-by-field basis for any fields that need special handling. See the Field Data Retention Reference below for all available criteria and conditions.

Method tab (HubSpot & Salesforce only) — This tab lets you choose between Native and Synthetic merge logic, and control whether empty master fields are automatically filled. See the Method Tab Reference below for details.

Step 4 is where you preview and apply your merge changes. It operates in two modes.

Preview Mode generates a CSV report that shows exactly how your records would be merged based on your current configuration — which records become masters, which field values end up where, and whether any errors occur. No changes are made to your CRM. Always run Preview Mode before Update Mode to verify everything is working as expected.

Update Mode applies the merge to your live CRM. Once you've confirmed your Preview results look correct, Update Mode executes the actual merge operations.

When the Merge API is set to Synthetic on the Module tab in Step 3, running in Update Mode displays a Please confirm dialog before the operation begins. This dialog shows an estimated time for the merge based on the number of associations and engagements that need to be reassigned. 

Click Yes to proceed. 

Processing time for Synthetic merges depends on the volume of associated records and will be longer than Native merges — avoid running multiple operations in parallel on the same database. You can monitor progress in the Activity Tracker.

Step 1 controls which records Insycle flags as potential duplicates. Each matching field you configure acts as a filter — records must match all of your specified criteria to be grouped together. For example, matching on First Name AND Last Name AND Email returns only results where all three values are the same.

Core Matching Parameters

Field SelectionComparison RuleIgnoredMatch Parts

Field Selection

Choose fields that, in combination, provide strong evidence that matched records represent the same entity. The goal is to select fields that are unlikely to be identical across unrelated records.

Choosing Unique Identifiers

Matching duplicates requires unique identifiers — data that is unlikely to be shared by any other record unless it is truly a duplicate. If you only use fields that could legitimately have the same values across different entities, you risk identifying unrelated records as duplicates and accidentally merging them.

Common Unique Identifiers by Object Type

For contacts:

• Email address
• Phone number
• Full name (first + last) combined with another identifier
• LinkedIn URL or other social profile
• Customer ID or external system ID

For companies:

• Company domain
• Company name combined with location or industry
• Tax ID or registration number
• External system ID (Salesforce ID, ERP system ID, etc.)
• Phone number or main office address

For other object types:

• Transaction ID
• Deal name combined with associated company
• Ticket number
• Any system-generated or externally synced ID

  Field Length Requirement

Values must be at least 4 characters long to be considered for matching. Standalone values such as "Joe," "Ace," or "Inc" will be ignored during the matching process.

Comparison Rule

The Comparison Rule determines how strictly field values must align to be considered a match.

• Exact Match looks for values that are identical with no differences between records. Use Exact Match for fields that should never vary if they represent the same entity — email addresses, domain names, ID numbers, and phone numbers (when formatted consistently) are all good candidates.

• Similar Match searches for values that are close but differ by one character, such as a typo, an extra character, or a missing character. This is often called "fuzzy matching" and helps find records with minor differences. The behavior is similar to how Google suggests alternative spellings when you search.

  For example, if a Company Name of "Acme" is found, it could match records with values like "Akme," "Acm," or "Acma."

  Similar Match uses looser criteria, casting a wider net for what constitutes a duplicate. Use it carefully, and always review the results to ensure the identified duplicates are what you expect. Start with Exact Match for reliable duplicates, then layer in Similar Match for edge cases.

  Note: ID fields only work with Exact Match, not Similar Match.

Ignored Elements

The Ignored parameter lets you exclude specific parts of a field value from the matching process — such as text, whitespace, or characters. These elements will not be considered when comparing records.

Available Ignore Options:

• Symbols — Ignore punctuation and special characters. Useful when comparing phone numbers where formatting varies (e.g., (555) 123-4567 vs 5551234567).
• Whitespace — Ignore spaces, tabs, and line breaks. Useful when comparing phone numbers or formatted text with inconsistent spacing.
• Subdomain — Ignore the subdomain portion of URLs or email domains (www., app., mail., etc.). For example, www.acme.com and acme.com would match.
• Top-level domain — Ignore the domain extension (.com, .co.uk, .org, etc.). For example, acme.com and acme.net would match.
• URL path — Ignore everything after the domain in a URL (/about, /contact, /us/western-region, etc.). For example, acme.com/about and acme.com/contact would match.
• Common Terms — Ignore business entity suffixes and common words that appear in company names. Insycle comes preloaded with terms like Inc, LLC, Corporation, and Company. Click the Terms button to view and edit the full list on the Common Terms tab.
  
• Text (substrings) — Ignore specific text strings you define. Click the Terms button, select the Ignored Text tab, and enter the text to ignore. Separate multiple strings with a new line. For example, you might ignore "Customer -" or "Account #" if these prefixes are inconsistently applied.

Enabling Ignored Elements

After configuring which elements to ignore, remember to enable the setting by checking the corresponding box under Ignored (for example, Ignored > Common Terms or Ignored > Text (substrings)). The ignore rules won't apply unless this checkbox is selected.

Match Parts

Match Parts lets you compare only a specific portion of the field value rather than the entire value. This is useful when records contain the same core data but differ in formatting, prefixes, or suffixes.

Available Options

Entire Value — Compare the full field value (default behavior).

Word-based matching:

• First Word, Last Word
• First 2-5 Words, Last 2-5 Words
• Any 2-4 Words (matches if any consecutive words match)

Character-based matching:

• First 3-12 Characters
• Last 3-12 Characters

When to use Match Parts

Use Match Parts when you know that a specific portion of the field value is consistent across duplicates, but the full value varies. Common scenarios include:

• Phone numbers with inconsistent country codes — Use Last 10 Characters to match the core phone number while ignoring whether a country code is present (+1 555-123-4567 vs 555-123-4567)
• URLs with varying subdomains or paths — Use First 10-15 Characters to match based on the core domain
• Names with inconsistent prefixes or suffixes — Use First Word or Last Word to match on the primary name component
• IDs with prefixes — Use Last 8-12 Characters to match the core ID while ignoring a prefix that may vary
• Long field values that slow processing — When matching on fields with very long values (such as long ID numbers, LinkedIn profile URLs, or other URLs with query strings), Insycle takes longer to process the comparison. If the unique portion of the value is at the beginning or end, use Match Parts to limit the comparison to just the first or last several characters. For example, use Last 9 Characters to match LinkedIn profiles like https://www.linkedin.com/in/svadinir-nemec-1234b31a3/ based only on the unique identifier portion. Alternatively, use the Ignored Text (substrings) option to exclude the common URL prefix (https://www.linkedin.com/in/) from the comparison entirely.

Related Fields

Related Fields lets you compare data across up to three different fields as if they were a single field. This helps catch duplicates where the same information appears in different field locations across records.

For example, you might want to check both the Email field and the Additional Email field for matching values. Or compare Phone, Business Phone, and Mobile Phone to find duplicates where the same number appears in different fields.

To configure Related Fields:

1. On the Simple tab of Step 1, select the primary field you want to match on.
2. Click the Advanced tab.
3. Under Related Fields, select up to two fields that contain similar data. Insycle will treat values from any of these fields as potential matches.

This is particularly useful when dealing with inconsistent data entry practices or records imported from different sources that map the same information to different fields.

Conditions

Conditions add requirements that one or more records in a duplicate group must meet. These let you control whether fields can be empty, require specific values, or set time-based parameters. 

To set a condition on a field:

1. On the Simple tab of Step 1, select the primary field you want to match on.
2. Click the Conditions tab.
3. Select the Condition option to configure for the field

Available Conditions

• At Least One Record With Non-Empty — At least one record in the duplicate group must contain a value in this field. The other records can have empty values.
• Value Required in All Records — Every record in the duplicate group must contain a value in this field to be considered a duplicate.
• At Least One Record Match — At least one record in the duplicate group must match the specified value, and the other records cannot be blank. If none of the records contain the specified value, the duplicate group will not be merged.
• Empty Allowed in Any Record — Duplicate group identified even if this field is blank in one, many, or all of the records. Useful when a field is a secondary identifier. Requires using at least two fields to identify duplicates.
• Only One Record Match — If more than one record in the duplicate group contains the specified field value, the entire duplicate group is skipped and will not be merged. Use this to ensure uniqueness constraints.
• Within Timeframe — Limit duplicate detection to records created or modified within a specific time window (minutes, hours, or days). For example, find duplicates created within the last 20 minutes. This is useful for catching duplicates created during high-volume import processes or live form submissions.
• Values Don't Match — All records in the duplicate group must have a value in this field, but the values cannot be identical across records. Use this to exclude previously processed duplicates from subsequent deduplication runs.

The CSV tab in Step 1 lets you import a list of known duplicate record pairs directly into the Merge Duplicates module, bypassing field-based duplicate detection entirely. This is useful when you already know which records are duplicates — for example, from an external audit, a data migration, or a report from another system — and want to use Insycle's merge logic to handle the consolidation.

This approach works with any supported CRM, including HubSpot and Salesforce. No custom CRM fields are required.

CSV Format Requirements

The CSV must include a header row with exactly these two column names: ID_1 and ID_2. Each subsequent row should contain the record IDs of one duplicate pair. Any additional columns in the file will be ignored — Insycle only processes the ID_1 and ID_2 columns.

Uploading the CSV

Navigate to Data Management > Merge Duplicates and select your database and record type. In Step 1, click the CSV tab, then click Upload and select your file.

Once uploaded, Insycle validates that the record IDs in the file exist in your CRM. Rows with invalid or missing record IDs will be skipped and will not appear in Step 2.

Completing the Merge

After uploading, continue through Steps 2–4 to review the duplicate groups, configure master selection rules and field retention settings, and run the operation.

The Master tab controls which record in each duplicate group becomes the master — the record that will remain after the merge. Insycle evaluates your rules sequentially from top to bottom. As soon as one record uniquely meets a rule, it becomes the master, and no further rules are evaluated for that group. If no records match any rule, automatic master selection fails for that group.

Core Configuration Options

Processing MethodField SelectionConditions

Choose Your Processing Method

Before adding rules, select how Insycle should process your master selection criteria. This is found at the bottom of the Master tab.

• By Priority (recommended) — Evaluates rules sequentially from top to bottom. As soon as one record uniquely meets a rule, it becomes the master, and remaining rules are skipped. This is the recommended method for most deduplication processes as it provides flexible, fallback-based master selection.
• Absolute — Requires the master record to simultaneously match every rule on your list. For example, if you need the master to be both a customer AND assigned to an active representative, Absolute ensures that only records meeting both criteria are selected. However, Absolute frequently results in no master being identified since records must satisfy all conditions simultaneously. By Priority is typically the better choice for most use cases.

Select Fields to Base Master Record Choice On

You can select any field from your CRM — whether writable or read-only — to base your master selection decision on. For each field, you'll set a condition that determines which record becomes the master.

Insycle reads rules in order from top to bottom. The first record that is the only one matching a rule becomes the master, and subsequent rules are ignored.

How Rule Ordering Works

Rule order matters. If your first rule is "Lifecycle Stage is Customer" and multiple records in the group are customers, Insycle moves to the next rule. If your second rule is "Email is work domain" and only one of those customer records has a work domain email, that record becomes the master — even if there are additional rules below.

Field Types You Can Use

• Writable fields — Any field you can edit in your CRM (Owner, Lifecycle Stage, Industry, etc.)
• Read-only fields — System fields like Create Date, Last Modified Date, Record ID, engagement metrics
• Calculated fields — Number of associated records, email engagement counts, deal amounts
• System sync fields — External system IDs (Salesforce ID, ERP ID, etc.)

You can layer multiple rules for the same field to create fallback logic. For example, "Lifecycle Stage is Customer" followed by "Lifecycle Stage is Opportunity" — if no records are customers, Insycle looks for opportunities.

Preventing Master Selection Failures

If none of your rules produce a unique match, Insycle cannot select a master, and the duplicate group will be skipped. To prevent this, add a catchall rule at the bottom of your list that applies to all records, such as "Create Date is earliest" or "Record ID is lowest." This ensures every duplicate group has a fallback option when more specific rules don't identify a clear winner.

Apply Conditions

Conditions define the logical criteria used to evaluate each record in a duplicate group to determine which one should become the master. When you define a condition, Insycle checks each record against your criteria (such as "Lifecycle Stage = Customer" or "Create Date is earliest") and selects the record that meets that condition. The available conditions vary based on the field type you've selected.

Standard conditions (text fields)

• Is / Is not — Match or exclude an exact value
• Contains / Does not contain — Match or exclude based on partial text
• Regex — Use a regular expression pattern for complex matching
• Exists / Doesn't exist — Filter based on whether the field has any value

Date field conditions

• Earliest / Latest — Select the record with the oldest or most recent date

Number field conditions

• Highest / Lowest — Select the record with the largest or smallest numeric value

Owner field conditions

• Active user — Select the record where the owner is currently an active user in your CRM
• Exists / Doesn't exist — Filter based on whether an owner is assigned

Email field conditions

• Not role-based (info@, etc.) — Exclude generic email addresses like info@, admin@, sales@
• Work domain (non-Gmail, etc.) — Select work email addresses, excluding common personal email providers
• Personal domain (Gmail, etc.) — Select personal email addresses from providers like Gmail, Yahoo, Outlook
• Exists / Doesn't exist — Filter based on whether an email address is present

Picklist and lookup field conditions

• Any of / Not any of — Select or exclude from multiple dropdown values at once

Most field types also support the Exists and Doesn't exist conditions to check whether the field contains any value.

Layering Conditions for the Same Field

You can create multiple rules for the same field to establish fallback logic. Insycle evaluates them in order and stops at the first one where a single record uniquely matches.

For example:

1. Lifecycle Stage is Customer
2. Lifecycle Stage is Opportunity
3. Lifecycle Stage is Lead

If no records in the group are Customers, Insycle checks for Opportunities. If no Opportunities exist, it checks for Leads. This ensures you select the most qualified record available within each duplicate group.

This fallback pattern also works for other scenarios:

• Check for synced records first (Salesforce ID exists), then fall back to records with owners, then fall back to oldest record
• Prioritize work email addresses, then personal email addresses, then any record with an email
• Select the most engaged contact (highest email clicks), then most recently updated, then earliest created

Example: Prioritizing Synced Records

A common master selection strategy is to preserve records that sync with external systems like Salesforce or ERP platforms. Here's how you might structure the rules:

1. Salesforce Contact ID exists — If a record syncs with Salesforce, it becomes the master
2. Contact Owner exists — If no Salesforce sync exists, pick a record that has an owner assigned
3. Create Date is earliest — If no records have a Salesforce ID or owner, merge into the oldest record

This ensures the record that integrates with your other systems is always preserved, with clear fallback logic when that sync doesn't exist.

Considerations When Picking a Master Record

The best master selection strategy depends on your record type and business priorities.

For Contacts:

Select master records based on engagement metrics when available — highest number of email clicks, most recent email opened, or highest engagement score. You can also prioritize by lifecycle stage (customers over leads) or by assignment (records with active owners).

Common contact strategies:

• Most engaged contact (email clicks, opens, form submissions)
• Furthest along in lifecycle (Customer > Opportunity > Lead)
• Most recently updated or contacted
• Record with active owner assigned

For Companies:

Prioritize records with the most associated data — the highest number of associated contacts, deals, or activities. This ensures you preserve the record with the richest relationship history.

Common company strategies:

• Most associated contacts or deals
• Highest annual revenue or employee count
• Record synced with external systems (Salesforce, ERP)
• Record with active owner assigned

For records synced with external systems:

If you integrate with Salesforce, an ERP system, or other platforms, prioritize the record that syncs with those systems to prevent breaking your integration. Use an "exists" condition on the sync ID field as your first master rule. See the example in the Conditions section above for how to structure this with fallback logic.

The Fields tab controls how data in each field is handled when duplicate records are merged. After selecting a master record, you can pull specific field values from other records in the group to ensure the most valuable data is retained.

By default, Insycle keeps all field values from the master record. If a master field is blank, the value from the most recently updated duplicate is used. You can create rules to override this behavior on a field-by-field basis — you only need to configure rules for fields requiring special handling, not for every field in your CRM.

Core Configuration Options

Field SelectionCriteriaConditionsGroup Fields

Field Name

Choose which fields you want to control data retention for. You can only add writable fields to the Fields tab — read-only fields, like Record ID, cannot have retention rules configured.

Available criteria and condition options vary by field type. For example, number fields support rollup calculations (sum, average, max, min), while text fields support conditions like "contains" or "is."

You don't need to create a rule for every field. Fields without specific rules are handled automatically using the default "fill in the blanks" behavior — Insycle keeps the master record's value, or copies from the most recently updated duplicate if the master field is empty.

Criteria

The Criteria dropdown determines where the field value comes from and how it's handled during the merge. Select from the following options for choosing the data to keep: 

Criteria marked with an asterisk (*) support the Group Fields feature. See the Group Fields tab for details.

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From master record* — Use the value that exists in the master record. If the master field is blank, the value from the most recently updated duplicate will be used automatically. For example, you may want to keep the Owner or LinkedIn URL from the selected master. 

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From master record (even empty)* — If the field on the selected master record is blank, keep it blank. Don't automatically fill it in with a value from the most recently updated record.

This prevents unwanted data from being copied into the master when you specifically want the field to remain empty. This option also supports the Group Fields feature.

Example: If you're merging test records into production records and the test records have invalid data, use this to preserve the master's empty state rather than copying bad data forward.

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Most frequent value — If the same value appears in multiple records within the duplicate group, use the one that appears most frequently.

Example: If three records have "Industry = Software" and one has "Industry = Technology," the master will be set to "Software."

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From record where value* — Select data from one of the records in the duplicate group based on the field's value. The available options vary by field type.

• For number fields: highest, lowest 
• For date fields: earliest, latest
• For text fields: exists, doesn't exist, specific value matches

Example: Keep the Employees count from the record with the highest number of employees.

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From record based on other field value*— Look at a different field's value to decide which record's data to keep for this field. This lets you use one field as the decision criteria for selecting another field's value.

Example 1: Keep the Owner from the record where Industry contains "Software" or "Technology." 

Example 2: Select the Company Name from the record with the earliest (oldest) Created Date.

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Combine and append all values — Merge the values from the selected field across all records in the group. Values are concatenated, preserving data from each duplicate.

Example: If there is a Notes field, consolidate the notes from all duplicates into the master so no historical context is lost.

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Rollup numbers— Aggregate numeric values from all records in the duplicate group. Available rollup types:

• Sum — Add all values together
• Average — Calculate the mean value
• Max — Keep only the largest value
• Min — Keep only the smallest value

Example: If duplicate contact records each have an "Amount Donated" field showing donations from different time periods, sum them and save the total to the master record.

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Collect all values from other field — Select a destination field to copy and combine values into, then select what field the data should come from. This preserves data by moving it from one field location to another during the merge.

Example: Preserve the Owner values from all duplicates by collecting them into a custom "Previous Owners" field. Or collect Record IDs from all duplicates into a "Merged Record IDs" field for tracking purposes.

Select the destination field under "Field Name," then select which field the data should come from under "Other Field." 

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Collect non-master values from other field — Aggregate values from all duplicates except the master, excluding any values that match the master's value. This ensures you only collect unique values that differ from what's already in the master.

Example: If you want a record of the Record IDs that were removed during the merge (excluding the master's ID), create a custom "Merged Record IDs" field in your CRM, then use this criteria to collect only the non-master IDs. This is helpful when you need to track which records were merged for cross-system cleanup or audit purposes.

Select the destination field under "Field Name," then select which field the data should come from under "Other Field." 

Apply Condition

Conditions define the logical criteria that determine which values are retained during the merge. When you add a condition to a field, Insycle evaluates each record's value against your rule (such as "Country = United States" or "Email is work domain") and only retains the value if the condition is true. Not all Criteria options support conditions—when available, the Condition dropdown appears next to the Criteria you've selected.

Standard conditions

These are available across most field types:

• Is / Is not — Match or exclude an exact value. For example, retain the Country field only when it is "United States."
• Contains / Does not contain — Match or exclude based on whether the value includes specific text. For example, retain the Website field only when it contains "acme."
• Exists / Does not exist — Filter based on whether the field has any value at all. For example, retain the Phone field only from a record where a phone number exists.
• Regex — Use a regular expression pattern for more precise matching. Useful for values that follow a known format, like ID numbers or postal codes.

Picklist and lookup conditions

For fields that use a dropdown or reference another record (such as owner fields):

• Any of / Not any of — Select or exclude multiple values at once without needing pipe separators. For example, retain the Lifecycle Stage only when it is one of the following: Customer, Opportunity, or Lead.

Field-type-specific conditions

Certain field types unlock additional condition options:

• Owner fields — Active user. Retains the value only from a record where the owner is currently an active user in your CRM. For example, use this with the "From record where value" Criteria to ensure the merged record ends up with a functioning owner assignment.
• Email fields — Not role-based (info@, etc.), Work domain (non-Gmail, etc.), Personal domain (Gmail, etc.). Filters based on the type of email address. For example, only keep the Secondary Email value if it uses a personal domain like 'outlook.com' or 'gmail.com' to ensure non-work contact information is preserved.
• Number fields — Available when using the Rollup numbers Criteria. Choose how to aggregate: sum, average, max, or min.

Using Conditions With Multiple Values

Several conditions support combining multiple values in a single rule using pipe-separated syntax.

To match against more than one value with Is, Is not, Contains, or Does not contain, separate each value with a pipe character ( | ). 

Example: To retain the Country field when it contains either "United States" or "Canada," enter: "United States|Canada"

For picklist fields, use any of or not any of instead — these let you select multiple options from a list without needing pipe separators.

 Be Careful with Multiple "Is Not" Rules on the Same Field

If you create two separate negative rules for the same field — for example, "Country is not UK" followed by "Country is not US" — they can work against each other. The second rule can unintentionally match values that the first rule was meant to exclude. A record with Country = UK will fail the first rule but pass the second ("is not US"), so UK could still end up being selected.

To avoid this, combine your exclusions into a single rule: Country is not any of UK|US

Keep Multiple Values Based on One Rule 

The Group Fields option lets you keep values of multiple fields from the same record based on a single rule. When you select a field value based on a condition, you can also preserve other related fields — even if those other fields are empty.

Group Fields is available when using the following Criteria:

• From record where value
• From record based on other field value
• From master record
• From master record (even empty)
   

How It Works

Configure your primary field rule as normal, then click Group Fields and select additional fields to preserve from the same record. If the record that meets your primary condition has values in the grouped fields, those values are copied to the master. If the grouped fields are empty in that record, the blank values overwrite whatever was in the master.

  Important: Group Fields will overwrite existing master values with blank values if the selected record has empty grouped fields. Use Group Fields only when you want to keep data from the same source record together, regardless of whether all fields are populated.

Example 1: Address fields
If a record has a Country value, you can group it with City, State, Street Address, and Postal Code to preserve the complete address from the same record. If any of the grouped address fields on that record are blank, those blank values will overwrite the master's existing address data.

Example 2: Record owner fields
Select the Contact Owner from the record with the earliest Create Date, then also save the Success Owner from the same record. If the Success Owner field on that record is blank, the master's Success Owner field will be blanked out as well.

The Method tab appears in Step 3 when working with HubSpot or Salesforce and provides additional merge configuration options. These settings control which merge API Insycle uses and whether empty master fields are automatically filled with values from duplicates.

Merge API

The Merge API setting determines which merge logic Insycle uses to combine your records.

Native uses your CRM's built-in merge logic. In HubSpot, this uses HubSpot's native merge behavior. In Salesforce, this uses Salesforce's Apex API merge logic. Native merge follows your CRM's standard rules for consolidating fields, associations, and activities during a merge.

Synthetic uses Insycle's custom merge logic. This gives you more control over field retention and master selection than your CRM's native merge provides, and is the only option available for object types that don't have native merge support in your CRM.

Default Merge API by Platform and Object Type

Learn more about CRM-specific merge behavior:

• Native Merge vs. Synthetic Merge behavior in HubSpot
• Native Merge vs. Synthetic Merge behavior in Salesforce

Blank Fields

The Blank Fields toggle controls whether Insycle automatically fills empty fields in the master record with values from duplicates — the "fill in the blanks" behavior described in the Understanding Insycle's Merge Logic section.

Enabled (toggled yellow) — Insycle automatically fills empty master record fields with values from the most recently updated duplicate where that data exists. This is the default setting and is recommended for most use cases.

Disabled (toggled grey) — Empty fields in the master record remain empty. No automatic filling occurs. Use this when you specifically want to preserve the master's empty state and prevent any data from duplicates being copied forward.

After you've seen the results in the CRM and you are satisfied with how the operation runs, you can save your configuration as a template and set up automation so this merge operation runs on a set schedule. If you have several templates you'd like to run together automatically, you can create a Recipe. 

Additionally, HubSpot users can integrate Insycle Recipes into HubSpot Workflows, and Salesforce users can use Recipes with Salesforce Flows. This enables event-based triggers, such as new-record creation or attribute changes, to ensure deduplication occurs in real time.

Return to the Template menu at the top of the page and click Copy to save your configurations as a new version of whatever template you started with. Then click the pencil to edit your new template name.

Under Step 5, click the Review button, and select Update mode.

On the Notify tab, select the send option appropriate for your automation: Always send, Send when errors, or Do not email.

Add any additional recipients who should receive the CSV (and make sure to hit Enter after each address). You can also provide additional context in the message subject or body.

On the When tab, under Automate, configure the frequency you'd like the template to run: Hourly, Daily, Weekly, or Monthly. 

When finished, click Schedule.

You can view all your scheduled automations at any time on the Operations > Automations page.

Scheduled Automation Run Times

With the Activity Tracker, you have a complete audit trail and history of changes made through Insycle, including processes run in Preview mode or data syncs. At any time, you can download a CSV report that shows all the changes made in a given operation run.

Navigate to Operations > Activity Tracker, search by module, app, or template name, then click the Run ID for the operation.

If you've configured the Insycle Run ID property in your CRM, you can cross-reference these operations in your CRM records.

In HubSpot, the master record always determines which primary email is kept after a merge. If you want to control which primary email address is kept, set up a rule to select the appropriate master record.

Review the email values in Step 2 to identify the criteria, then set up a Master rule in Step 3 to choose the record for each duplicate group based on that criteria. 

For example, to select the master based on corporate email addresses over personal ones (like choose the record with john.smith@acmecorp.com over john.smith@gmail.com), configure a master rule:

• Field Name: Email
• Condition: Work domain (non-Gmail, etc.)

Other Example Master Rule Configurations:

• Field Name: Email
• Condition: Select from the following options based on your business rules:
  • Personal domain (Gmail, etc.) — Prioritize personal email addresses; useful when merging consumer contacts or individual leads.
  • Not role-based (info@, etc.) — Exclude generic email addresses like info@company.com or sales@company.com to keep only personal contact emails.
  • Is / Is not — Match or exclude an exact value. For example, use "Is not" with "noreply@company.com" to avoid selecting automated email addresses as master records.
  • Contains / Does not contain — Match or exclude based on partial text. For example, use "Contains" with "@acmecorp.com" to prioritize all company domain emails, or "Does not contain" with "+test" to exclude test email addresses.
  • Regex — Use a regular expression pattern for complex matching. For example, use a regular expression (regex) pattern to match emails from multiple specific domains or to identify specific naming patterns.
  • Exists / Doesn't exist — Filter based on whether the field has any value. For example, use "Exists" to prioritize records with an email address over those without one.

Retaining Other Email Data

Though you cannot use the Fields rules to control what HubSpot primary email field data is retained, you can set retention rules to copy non-master email values to a different field, such as Additional Email or a custom field.

For example, to preserve non-master email values as backup contact information, configure a field rule:

• Field Name: Additional email addresses
• Criteria: Collect non-master values from
• Other Field: Email

Let's say we have four records that represent the same person—Marta Vaskovitch. The Merge Duplicates module will identify this as a single duplicate group of four records.

Here is the data that we have for this duplicate group:

Here are the master selection rules we have set up:

We haven't sent any emails to Marta yet, so when Insycle processes the first three rules—Marketing emails clicked, emails bounced, and emails opened—Insycle cannot eliminate any record because they all have the same value of zero.

None of the record email addresses are "role-based," so there isn't a single choice for the master using the Email rule either.

In the next rule about contact owner, records 61301, 61201, and 61251 are eliminated since no contact owner exists for those records. Now, only one record remains, 61351, therefore that's the master record.

Most of the time, when Insycle can't find duplicates, it is due to your matching rules in Step 1. It is important to analyze the underlying data to better understand how to set up your rules. A helpful exercise for contacts is to set up your matching filters to find exact matches on only First Name and Last Name. For companies, you can use Company Name.

When you click Find, these rules can show you a broad overview of what duplicates are potentially in your database and what fields might be useful to include in your matching fields. These settings are just for discovery and should not be used for a final merge operation; many people can have the same first and last names and are not duplicates. 

To get further context, on Step 2, click the layout gear button on the right side of the title bar. Here, you can add any field from your database as a column in the duplicate group review to better understand the data in these records. These will also appear in your CSV report. 

If the Result is "Failed" and the Message column of the CSV report displays this text:

Change rules in Step 3 'Master Selection'. Failed to pick master record because multiple records (X) meet the selection criteria. In 'Master Selection', change, add, or reorder the rules such that only one record matches (if cannot determine master based on field values, use 'Record ID is lowest' as the last rule).

This means Insycle could not determine which record in the duplicate group should become the master — none of the records meet more of the rules than the others.

There are a few things you can try to resolve this:

1. Under Step 3, on the Master tab, experiment with reordering or adding rules based on fields that are likely to have unique values across your records. Think about what matters most to your business — the fields that would make one record clearly more valuable or authoritative than another. For example:

   • A field that stores an ID linked to an external system, such as an ERP, data warehouse, or proprietary internal tool — the record with that ID populated is likely the one your other systems depend on
   • The record with the highest number of associated records (contacts, deals, activities) — indicating it has accumulated more history and relationships
   • A field indicating CRM ownership or account status — for example, a record marked as "Customer" vs. "Lead," or one with an active owner assigned
   • A field that tracks revenue, subscription tier, or engagement level — the record with higher values may represent the more complete or current entry
   • A custom field your team uses to flag record quality or data source reliability

   The goal is to surface the fields that reflect record importance for your specific operations, not just default system fields.

2. Also on the Step 3 Master tab, confirm that By Priority is selected rather than Absolute.

   With By Priority, a record only needs to match one rule to be selected as master. With Absolute, a record must meet all rule criteria, which makes it much harder for any single record to qualify.

   In most cases, By Priority is the right choice. If By Priority is already selected and the error persists, none of the records in the group meet any of the criteria more than the others. Return to the Master tab and continue adding or reordering rules, focusing on the business-critical fields described in #1 above.

   

3. As a last resort, add a rule on the Master tab that uses Record ID is lowest, or Create Date is earliest. These rules will always produce a unique winner, ensuring master selection can complete even when other field-based rules cannot differentiate the records.

There are a couple of things to look at that may be causing records to be misidentified as duplicates.

First, you may need a better unique identifier. Under Step 1, if you use only fields that can correctly contain the same values across multiple records, they aren't unique identifiers. In this case, you are likely to identify unrelated records as duplicates and may accidentally merge them.

Unique identifiers are data unlikely to be shared by any other record unless they represent the same underlying entity. Common fields used for deduplication include phone numbers, email addresses, mailing addresses, and ID numbers.

Second, this may indicate the Comparison Rule under Step 1 is too broad. Try using the Exact Match comparison rule instead of the Similar Match rule. Similar Match looks for values that may be close, even with a one-character difference (e.g., a typo), broadening the search. 

Remember to always run your deduplication in Preview Mode to confirm it's working as expected before running it in Update Mode and applying the changes to your CRM records.

You have duplicate records identified by Insycle, but not all are merging into the master. Check how many duplicates are in the affected groups. If you have duplicate groups with more than 5 records, you may want to change the Exclusions value at the bottom of Step 3 on the Master tab: Skip duplicate groups with more than 5 records per group to ensure you can get them all.

This setting is intended to prevent overly broad matching criteria from accidentally merging unrelated records. You can adjust this threshold up to 100 records per group.

It can take Insycle a while to find and match duplicates when the fields used to identify them have very long values. The longer the values, the longer it takes Insycle to process the data and generate the results. This might come up when looking for matches based on long ID numbers, LinkedIn bio links, or other URLs with long strings attached (ex, https://www.linkedin.com/in/svadin%C3%ADr-n%C4%9Bmec-1234b31a3/).

You can speed this up by limiting how much of the value Insycle looks at.

If the beginning or ending portion of the values are all unique, you can limit the comparison to the first or last several characters using the Match Parts parameter under Step 1. 

Or use the Ignore Text (Substrings) parameter, then click the Terms button.

On the Ignored Text tab of the popup, add the common portion of the URL or text string.

Field rules in Step 3 can only update writable fields. Read-only fields are not shown in the Fields tab dropdown because the CRM prevents these properties from being written back. Insycle excludes them from the field selection options to prevent errors.

While you cannot create field rules for read-only properties in the Fields tab, you can use them in the Master tab. Read-only fields, such as "Last Activity Date," can be used to make merge decisions without attempting to modify those properties.

You can also use read-only properties for filtering and matching in Step 1. Read-only fields are also available when reviewing data in Step 2 or in the CSV report.

To identify which fields are read-only, use the Cleanse Data module. Navigate to Data Management > Cleanse Data, then select a database and record type from the top menu. You can search for a specific field by name or click the Writable heading in the table to sort and review all writable or non-writable fields. A checked box in the Writable column indicates the field is writable.

If you are running a bulk merge operation on custom objects for the first time, you may see the message "Please contact support@insycle.com to enable bulk merge for type: [Custom Object Name]."

By default, you can manually merge custom objects that have been synced with Insycle, but before you can bulk merge duplicate custom objects, they must be enabled for your account. This message indicates the step has not been completed yet. 

To enable bulk custom object merging for your account, please contact Insycle support by email or via the live chat at the bottom of every page on the Insycle website or in the app.

Learn more about using custom objects and fields in Insycle.

Currently, neither HubSpot nor Salesforce provides an automated way to prioritize active owners during the merge process. You'd need to verify owner status manually for each merge operation.

However, Insycle's Merge Duplicates module includes an option to prioritize an active owner. 

First, you could add a Master rule under Step 3 to tell Insycle to select the record from each group with an active owner as the master record.

Add a rule with the following parameters:

• Field: Record owner
• Condition: active user

Second, you could create a Field rule to retain the owner who is an active user.

Add a rule with the following parameters:

• Field: Owner
• Criteria: From record where value
• Condition: active user

There are two ways to ensure the records you are merging are indeed duplicates.

First, always run your deduplication templates in Preview Mode before running them in Update Mode. This produces a CSV file showing how your records would have been merged. Then you can ensure that your Merge Duplicates template is working as expected and not merging non-duplicate records together.

Additionally, to ensure a smooth merge, consider narrowing the matching settings in Step 1. Try the Exact Match Comparison Rule instead of Similar Match. Then make sure that you are using actual, uniquely identifying fields—first name, last name, email, and phone number are popular choices. The more tightly defined your filter is, the less likely you are to merge non-duplicate records.

No, matching fields do not need to match exactly. The Similar Match Comparison Rule in Step 1 acts as a fuzzy match, looking for values that may be close but differ by only one character (e.g., a typo), and broadens the search.

This search behaves like when Google shows results for a slightly different term or says, “Did you mean...” For example, if an Email of “huey@coahulldu.co” is found, it could include records with the values “hueyy@coahulldu.co" or "hue.y@coahulldu.co” as a match.

You should be careful when using Similar Match as the looser criteria can incorrectly identify non-duplicates as duplicates. 

Review the Understanding Similar Matching best practices for more details.

Yes, Insycle allows you to select which field data to retain in the master record using the Fields tab in Step 3. See the Merge Duplicates module field data retention rules reference for more details.

If the Message column of the CSV report displays this error:

Change rules in Step 3 'Master Selection'. Failed to pick master record because multiple records (X) meet the selection criteria. In 'Master Selection', change, add, or reorder the rules such that only one record matches (if cannot determine master based on field values, use 'Record ID is lowest' as the last rule).

None of the records meet more of the rules than the others do.

There are a couple of things you can try to resolve this:

1. On the Master tab in Step 3, experiment with reordering or adding additional fields that are likely to have unique values.
2. At the bottom of the Master tab in Step 3, ensure By Priority is selected, not Absolute.
   With By Priority, your master record only has to match one rule. Using Absolute, your master record would have to meet all of the rule criteria. In most cases, it is best to select By Priority.
   If By Priority was used, then none of the records in the duplicate group meet any of the criteria on the list more than the others. In this case, you'll need to experiment, reordering or adding additional rules for fields likely to have unique values.
3. As a last resort, you can add a rule on the Master tab in Step 3 that says Record ID is lowest, or Create Date is earliest.

By default, merged records retain the value from the master record. If you want to keep a specific value from a read-only field that's not in the master, you have two options:

1. Copy to a writable custom property: In your CRM, create a custom field to copy the read-only field value into. Then run a Copy operation in the Transform Data module before performing the merge. Finally, set up Merge Duplicates rules on the Fields tab of Step 3 to retain the value of that custom property that meets your criteria.

2. Use master selection rules: Set the master selection rules on the Master tab of Step 3 to retain the record with the read-only value you want to keep. This guarantees the correct record becomes the master without trying to change the read-only property itself.

You can merge up to 100 duplicate records into a single master record.

By default, Insycle skips any duplicate group containing more than 5 records. If you have duplicate groups with more than 5 records, you may want to adjust the Exclusions setting at the bottom of the Master tab in Step 3. The Skip duplicate groups with more than X records per group setting can be increased up to 100 records per group to ensure all duplicates in large groups are processed.

This default limit is a precaution to prevent duplicate matching criteria that are too broad in Step 1 from accidentally merging many non-duplicate records. If you plan to set this number higher, it is a good idea to run Preview Mode first to ensure your deduplication template is operating as you intend.

Yes. You can use an existing list of duplicates with Insycle to deduplicate it in bulk, following these steps:

1. Prepare a CSV file with columns for the record IDs and a "Merge Master" column. In the "Merge Master" column, mark which record should be kept after merging.
2. Create a custom field called "Merge Master" in your CRM.
3. Use the Magical Import module to import your CSV file into the CRM, updating the "Merge Master" field for the relevant records.
4. Go to the Merge Duplicates module and set up a filter to select records based on the "Merge Master" field.

Learn more about deduplicate records using a CSV.

Yes, there are several ways to share details and get approval before merging duplicates.

You can manually approve master records and mark them in a CSV file, then use Insycle to bulk deduplicate into those master records. See the Customize Bulk Deduplication Using Exclusions and Pre-Defined Masters article to learn more.

Or, you can run the Merge Duplicates module in Preview Mode and then deliver the preview CSV that Insycle generates. The CSV report includes your entire merge operation down to individual duplicate groups, but does not update your live data. Then your team can approve the merge based on this report, before running Merge Duplicates in Update Mode.

Additionally, team members can review duplicates and manually select the master for each record under Step 3 by selecting Manual mode. Review the Manually Merge Duplicates article for more details.

Insycle displays 50 records on the module screen as a preview; this is not the full list. Insycle can process thousands of duplicate groups in a single operation. You could potentially deduplicate your entire database in a single step. 

When using the Preview in Step 4, select the "All" option under When > Run Now to view all records in the Preview CSV report. When you run the operation in Update mode, all records will automatically be included.