Deduplicate Across Intercom Leads and Users

Navigate to Data Management > Merge Duplicates, and select the Intercom database and Users record type from the top menu. Then explore the templates for an existing solution that may be close to what you need.

Step 1 looks through the records in your database examining the fields that you specify for a match. 

Add a row for each field you want to compare to find a matching value. Choose fields that, in combination, give a high degree of certainty that the matched records are duplicate records.

Check the Include Leads checkbox so that Insycle will look at leads and users for duplicates and allow you to merge them into a single record.

Click the Find button and Insycle will generate a list of duplicates for you to review.

Commonly used matching fields in lead and user deduplication include:

• Name
• Companies
• Email
• Email domain
• Phone
• ID

For details on configuring the find duplicates rules, see the Bulk Merge Duplicate People, Companies article.

Records that have the same values in the fields from Step 1 are considered matches, whether they are all leads, all users, or a mix. When two or more records represent the same person based on your matching rules, they are clustered together into duplicate groups.

Under Step 2, each duplicate group shows the total number of records that were identified as duplicates based on your settings. For example, if you had four records for the same person, it would count as one duplicate group with four duplicate records.

In this view, each row represents a duplicate group. When you click a row, it expands and shows the records that belong to that group. The Type column indicates whether the duplicate record is a user or lead.

Explore the record data in the duplicate groups. Double-check to ensure that the fields you set up in Step 1 show what you expected.

Looking at the record details in several duplicate groups, decide the best way to determine which is the master record the other records will be merged into. Learn common practices for picking a master record.

To get more context for analyzing the records, add more columns to the groups view using the columns layout gear button at the right end of the header.

The most efficient and sustainable way to merge duplicates is in Bulk mode. This allows you to set rules for automatically determining the master record across all lead and user records in your database. You can then use saved templates and recipes to repeat the process.

Under Step 3: Choose Operation, the Bulk operation tab is automatically selected. Leave this as is.

If you have duplicate groups that contain more than five records, you may want to change the value in Skip duplicate groups with more than 5 records per group to make sure you can get them all.

Note: When merging in bulk, Insycle limits the duplicate group size to 5 records and skips groups that contain more. You can adjust the value as needed, up to 100 per duplicate group. This is a precaution to ensure that if you use a duplicate matching filter that is too broad in Step 1, you do not accidentally merge many non-duplicate records together.

In Manual mode, you have complete control over which records are merged together by selecting them from the Record Viewer. Manual mode should be reserved only for cases needing a careful, controlled process. Learn more about manually merging duplicates.

Configure Rules to Automatically Select the Master Record

On the Record tab of Step 4, define how all of the duplicate groups should be merged at scale. To do this you need to create a series of rules that specify which record from each group should become the master.

The master is the record that will remain after the merge. For example, if you had four records representing the same person in one duplicate group, all four would be merged into one master record, and the three non-master records would no longer exist.

Select the matching method on the right end of the Step 4 header. The vast majority of duplicate processes should use Priority Match. When a record meets one of the criteria, Insycle makes the master selection and skips the rest of the rules on the list.

For each duplicate group, Insycle will look at each Record rule to see which of the records in the group meet the criteria. Rules are read in order, from top to bottom and as soon as a record is the only one to meet a rule, it is selected as the master record. The subsequent rules are ignored. 

If none of the records in the duplicate group match any of the rules, the automatic master selection for the group fails. See the Troubleshooting section below for more details.

With Absolute Match, the master record must meet all of the listed rules in the Record tab. This is appropriate for less flexible master selection. 

Learn more about Priority Match vs. Absolute Match in the Advanced How-Tos section below.

Configure Rules That Determine Values to Keep

After Insycle has identified the master record, it will use the Field selection rules to automatically pick which values from a duplicate group will be used in the master record.

Under Step 4, click the Fields tab. For each field you want to control the data retention for, you need to tell it where the data should be taken from. This is merged into the master. Any data that is not in the master or not copied to the master is deleted.

The Criteria dropdown gives you various options for choosing the data to keep:

• From master record – Use the value that exists in the master record.
• From master record (even empty) – If the field on the selected master record is blank, keep it that way. Don’t automatically fill it in with a value from the most recently updated record.
• Most frequent value – If the same value appears in multiple records, use the one that appears most frequently.
• From record where value – Select data from one of the records in the duplicate group based on the values. These options vary depending on the field type. For example, retain the Tag value in the record where the value is not, "CSV Import -2023 0531," or "CSV Import - 2023 0515."
• From record based on other field value – Look at the value in a different field to decide which value from the duplicate group should be kept. The example above highlights how a Last Opened Email value can be used to determine which Email value should be kept. 
• Combine and append all values – You can merge the values from the selected field for all records in the group. For example, if there is some type of Notes field, you could keep the notes from all the records in the duplicate group and merge them into the master record.
• 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. For example, this could be used to keep the record Owner values of all duplicates and combine them into a custom field.
• Collect non-master values from other field – Aggregate the values of all the duplicates that are not the master and not the same as the master, meaning all instances of that value are excluded from collection. This can be especially helpful if you want a record of the object IDs that were removed, so you can also remove them from another system. Select a destination field to copy and combine values into, then select what field the data should come from.

  When one or more fields are added to the Fields tab, a special row –Master (After)– will appear in the CSV report. For each duplicate group, the Master (After) row shows the values the final record will contain based on your Field rules and the default behavior.

Preview Merge Changes in CSV Report

Now with the filters and master record set up, you can preview how the merging would be applied. That way, you can check to ensure your configuration works as expected before the changes are pushed to your live Intercom database. The CSV report that Insycle generates includes records from all the duplicate groups.

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

Click the Next button to go to the Notify screen, where you can select recipients for the email report and add additional context.

On the When tab, click the Run Now tab, select which records to apply the change to, and then click the Run Now button.

Insycle will generate a preview CSV and send it to your email. Open the CSV file from your email in a spreadsheet application.

There's a row for each record, which includes:

• The Result of the action
• A Message with details
• The Duplicate Group ID which indicates which records will be merged together
• A record Status that identifies which were picked as master and which were identified as duplicates and merged into the master. See below for more details
• All fields used to identify the duplicates in Step 1
• The Record ID, record name or email, and Deeplink to the CRM record
• The Type, indicating whether the record is a User or Lead
• All fields selected for the Record and Fields rules in Step 4. Note that if a field is used on both tabs, it will only appear once in the CSV. 

The Status column indicates:

• Duplicate – The record is part of a duplicate group.
• Master – The master record chosen for the duplicate group based on default behavior and your Record rules. Review the selections in this row to determine whether the appropriate records are being chosen.
• Master (After) – This appears only if at least one or more fields have been specified in Step 4 on the Fields tab. For each duplicate group, the Master (After) row shows the values the final record will contain based on your Field rules and the default behavior. 
• Error – If Insycle is not able to determine which record would be the master, an error message will appear here. See the Troubleshooting section below for more details.

If everything looks good, return to Insycle and move forward with applying the changes.

Apply Changes to Your CRM Records

If everything in your CSV preview looks good, return to Insycle and move forward with applying the changes to your live Intercom data.

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

On the When tab, you should use Run Now the first time you apply these changes to Intercom.

After you've seen the results in Intercom and 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 automatically run together, you can create a recipe.

By automating with a template, you'll save time and ensure that your leads and users are merging consistently on an ongoing basis.

Return to the Template menu at the top of the page and click Copy to save your configurations as a new version of the 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, select Automate, and configure the frequency you'd like the template to run. When finished, click Schedule.

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

Learn More:

• Automation and Manual Operations
• Recipes

Each row in your matching fields setup is cumulative, so records must meet all of the criteria. For example, looking for records that have the same First Name and Last Name and Phone Number returns only results where all three values are the same.

  The minimum required length for the matching values is four characters or more. Values such as "Joe" or "Ace" will be disregarded.

Use the filter to work with a segment or smaller pool of records. Then Insycle will only analyze the remaining records for duplicates. To add filters, click the Filter button, then choose the field to look at, select the condition, and set the value to look for. The filter is applied before the matching step runs. 

Most of the options in the Field dropdown match the fields that are found in your CRM, and for Contact records, there are three additional options related to the Email value: 

• Email Username: The portion of the email address before the “@.” For example, if the email address were “maria@acmewidgets.com,” the username value would be “maria.” 
• Free Email Provider Domain: Choose True to filter out records where the email domain is Gmail, Hotmail, Yahoo, and about 10,000 other free email providers. This filter helps ensure these are real clients, or can determine which record is the legitimate one because it’s most likely customer companies aren't using free Gmail accounts (though a contact may have accidentally emailed us from it at some point). 
• Email Top-Level Domain: The top-level domain (TLD) is everything that follows the final dot of a domain name. For example, in the domain name acmewidgets.com', '.com' is the TLD. Some other popular TLDs include '.org', '.uk', and '.edu'. 

Sometimes, you might want to match duplicates using data in two separate fields. For example, you might want to compare the Business Phone field to a Mobile Phone field to identify duplicates.

Using the Related Fields feature, you can use two different fields (that contain similar data) as matching fields to catch more duplicates.

You can set up Related Fields on the Advanced tab of Step 1.

When using two or more fields to identify duplicates, records can still be considered matches even if one of the field values is blank. You just need to specify which field(s) allow a blank value.

Under Step 1, configure your matching rules in the Simple tab, then click the Conditions tab.

All the matching fields you included will automatically appear with the default Value Required in All Records condition selected. Change the condition to Empty Allowed in Any Record to allow empty values for certain fields. You can also use the At Least One Record with Non-Empty condition to help you determine which is the master record. Make sure at least one field remains required and is a reliable unique identifier to ensure the records are really duplicates.

For example, on the Simple tab, you may have the matching fields: Email, Name, and Phone. But on some of your records, the Phone field may be empty. Using the Empty Allowed in Any Record or At Least One Record with Non-Empty, all records with the same email, same name, and no phone number will be considered duplicates.

 

Priority Match: Looks through the master selection rules in order, one by one. As soon as a record meets one of the criteria, Insycle makes the master selection and skips the rest of the rules on the list. The vast majority of duplicate templates should use Priority Match.

Absolute Match: The master record must meet all of the listed rules in the Record tab in Step 4. If a record does not match every rule listed, no master record will be identified. Absolute Match is appropriate for less flexible master selection.

For example, if a company wanted to ensure the chosen master record is in their sales pipeline and already has a sales rep working the record, they can choose Absolute Match and set the Record rules:

• Email has hard bounced is False
• Owner exists

Choosing Absolute Match can often result in no master record being identified since the record has to match every rule listed, so in most cases, you should select Priority Match.

Though it's possible that duplicate records may be exactly the same, often there is only partial data overlap between them. When data is split between two different records, both records may contain unique and important information about the customer you'd like to keep.

The Merge Duplicates module allows you to control the values saved in the master record after the merge, regardless of the default merge behavior. By adding each field you want to control the data retention for and selecting a Condition, you can tell Insycle where the data for the field should be taken from and how to handle it.

For example, if merging Intercom users, you may want to save all of the Owners from records that are merged together and deleted. You can add a new custom attribute, “Merged Owners” to your CRM.

Then in the Merge Duplicates module under the Fields tab of Step 4, add a rule to override the default merge behavior. Select the "Merged Owners" field, the "Collect non-master values from other field" criteria, and "Owner" as the other field. 

You can use the Preview to see how this will preserve the Owner values of all the duplicates in each duplicate group.

For situations where there are no common rules you can apply for identifying duplicates for all or some of the records, you may need more granular control for picking records to include or exclude from the process. In these cases, you can use CSV files to customize your bulk merging, designate master records, and exclude records from deduplication. Then you can import the CSV from the Magical Import, and use the Merge Duplicates module for complete control over the final merge operation. Learn how to customize merging duplicates in bulk using a CSV.

You have duplicate records that Insycle has identified, but not all of them are merging into the master. Check to see how many duplicates are in the affected duplicate groups. If you have duplicate groups that contain more than five records, you may want to change the value in Skip duplicate groups with more than 5 records per group to make sure you can get them all.

This setting is intended to protect against the accidental merging of non-duplicate records if the filter in Step 1 is too broad.

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

Change rules in Step 4 '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 that based on all the rules, Insycle could not figure out which record in the duplicate group would be the master. None of the records meet more of the rules than others.

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

1. Under Step 4, on the Record tab, experiment with reordering or adding additional fields that are likely to have unique values.
2. In the Step 4 heading, check to ensure that you have Priority Match selected and not Absolute Match.

   
   With Priority Match, your master record only has to match one rule. Using Absolute Match, your master record would have to meet all of the rule criteria. The majority of the time, it is best to select Priority Match.

   If Priority Match 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 with the Record tab, reordering or adding additional rules for fields likely to have unique values.

3. As a last resort, you can add a rule on the Record tab of Step 4 that says Record ID is lowest, or Create Date is earliest.
   

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

First, you may need a better unique identifier. Under Step 1, if you only use fields that could correctly contain the same values in multiple records, these 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 that is unlikely to be shared by any other record unless it represents the same underlying entity. Fields that are commonly used in deduplication include phone numbers, email, mailing addresses, or ID numbers.

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

Remember, always run your deduplication in Preview Mode to confirm things are working as expected before running them in Update Mode and applying the changes to your CRM records.

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 useful exercise can be to set up your matching filters to look for exact matches of just 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 in your database as a column to the duplicate group review to better understand the data inside these records.

It can take a while for Insycle to find and match duplicates if the fields being 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.

Yes. You can use an existing CSV with duplicate record details. The file needs to include the record IDs and a "Deduplication Master" column, specifying which records should be the master, kept after the merge. Next, create a custom field "Deduplication Master" in your CRM to facilitate the merging. Use the Magical Import module to import the edited CSV file into the CRM, populating the new custom field. Finally, utilize this custom field to merge the duplicate records in the Merge Duplicates module.

Learn more about customizing bulk deduplication from a CSV.

Insycle shows up to 50 records on the Merge Duplicates screen as a preview, this isn't the entire list of records. View the Preview CSV report to see the results for all records.

Insycle can process thousands of duplicate groups in one operation. Potentially, you could deduplicate your entire database in one operation. 

Yes. Sometimes, you may want to look at the data in two separate but related fields to identify duplicates. For example, you might want to look in both the Email Domain field and Email in case different team members are using the fields differently. 

Using the Related Fields feature, you can use two different fields that contain similar data as matching fields to catch more duplicates. You can set up Related Fields in the Advanced tab of Step 1.

Currently, there are two ways to ensure that the records you are merging are duplicate records.

First, always run your deduplication templates in Preview Mode before running them in Update Mode. This produces a CSV that shows you 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, you can reduce the risk when merging duplicates by narrowing your duplicate 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.

You can merge up to 100 duplicates into one single master record. 

If you have duplicate groups that contain more than five records, you may want to change the value in Skip duplicate groups with more than 5 records per group under Step 3 to make sure you can get them all.

This is a precaution to ensure that if you use a duplicate matching filter that is too broad in Step 1, you do not accidentally merge many non-duplicate records together. If you are going to set this number at a high level, it is a good idea to run Preview Mode first to make sure your deduplication template is operating as you intend.

All plans include unlimited usage, unlimited users, and unlimited operations. See Insycle's pricing page for more details. During the free trial, there is a cap of 500 records updated, cleansed, or merged.

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

Change rules in Step 4 '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 that based on all the rules, Insycle could not figure out which record in the duplicate group would be the master. None of the records meet more of the rules than others.

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

1. Under Step 4, experiment with reordering or adding additional fields that are likely to have unique values.
2. In the Step 4 heading, check to ensure that you have Priority Match selected and not Absolute Match.
   
   With Priority Match, your master record only has to match one rule. Using Absolute Match, your master record would have to meet all of the rule criteria. The majority of the time it is best to select Priority Match.
   If Priority Match 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 Record tab of Step 4 that says Record ID is lowest, or Create Date is earliest.
   

Yes, Insycle allows you to select which field data is retained in the master record using the Fields tab under Step 4. See the Advanced How-To, Step 4: Control What Field Data is Retained in this article for more details.

Yes. You can exclude records from deduplication by creating a CSV with a "Deduplication Exclude" field.

First you'll export a Preview CSV from the Merge Duplicates module, add an exclude column, and specify which records should be excluded from the merge process. Next, create a custom field in your CRM to facilitate the merging. Use the Magical Import module to import the edited CSV file into the CRM, populating the new custom field. Finally, utilize this custom field to merge the remaining duplicate records in the Merge Duplicates module.

Learn how to customize bulk deduplication using exclusions.

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, then use Insycle to bulk deduplicate down to those master records. Consult with this Customize Bulk Deduplication Using Exclusions and Pre-Defined Masters article to learn more.

Or, you can run the Merge Duplicates module in Preview Mode, then deliver the preview CSV that Insycle generates. The CSV report that Insycle generates 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 4. Review the Manually Merge Duplicates article for more details.

No, your field data does not need to match exactly. The Similar Match comparison rule in Step 1 looks for values that may be close but with a one-character difference (maybe 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, “myla.h@cington.co” is found, it could include records with the values “myla.h@cington.com," or "myla@cington.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 Deduplication Best Practices article for more detail.

When using two or more fields to identify duplicates, records can still be considered duplicates even if one of the matching field values is blank. You just need to specify which field(s) allow a blank value.

See the Advanced How-To, Step 1: Allowing Empty Values When Matching above for full details.