Intercom Merge Duplicates Overview

Duplicate data in Intercom poses serious problems for companies of any size.

Duplicate records inhibit your support teams from effectively segmenting and personalizing communications. They lack vital context, miss important information, and analysis and reporting are skewed. Ultimately, this means a worse experience for your customers.

Insycle helps you to merge duplicate leads, contacts, accounts, opportunities, and custom objects—flexibly and powerfully with the Merge Duplicates module.

Use Cases

Supported Intercom Record Types

Insycle supports the following Intercom record types for the Merge Duplicates module:

Users
Leads
Companies

You can select the record type that you would like to import at the top of the module screen.

How It Works

Insycle analyzes your database and identifies duplicates with flexible matching rules, using any field in your database, to help you identify and merge more duplicates.

Once Insycle identifies the duplicate records, you set rules for determining the master record that other duplicates will be merged into—such as the first record created, the record with the most email opens, or any other attribute that would be relevant. You can also set merging logic on a field-by-field basis.

You can merge duplicates in bulk, and Insycle provides a complete report of what was identified as a duplicate, what was merged, and what the outcome was in your master record.

Deduplicate Across Leads and Users

Deduplicating Intercom leads and users together is easy with Insycle.

First, you filter your data down to the leads that you would like to deduplicate, using rules. Then, you tell Insycle to link the records. To include both leads and users, all you have to do is check a checkbox.

To begin, follow the standard deduplication procedures. In Step 1, select "Include Leads."

To learn more, see Deduplicate Across Intercom Users and Leads.

Identify Duplicates with the Insycle Intercom Inbox App

The Insycle Inbox app, once installed, adds a widget to your Intercom inbox to quickly check for duplicates in an open conversation.

You simply open the conversation, find the "Insycle Data Management" widget on the right-hand side of the screen, and click the "Check Duplicates" button.

Then, Insycle will compare the contact in your currently opened conversation against other contacts in your database, and give you the option to merge.

To learn more, see Deduplicate in Intercom Inbox with the Insycle App.

Intercom Merge Logic

When merging Lead<>User, Insycle uses the underlying Intercom merge API.

When merging Lead<>Lead or User<>User, Insycle performs a synthetic merge:

Open conversations: Duplicate contacts will be detached from open conversations, and the master contact will be attached to those conversations.
Closed conversations: Copy all closed conversations from duplicate contacts and create a note per conversation in the master contact (Notes are searchable in Intercom).
Tags: Assigned from duplicates to master.
Companies: Assigned from duplicates to master.
Notes: Copied from the duplicates and created in the master.
Events: Copied from the duplicates and created in the master.
Fields: Use Master Selection By Field to determine what data is retained in the master record on a field-by-field basis. By default, retained from the master. When a value is empty in the master it picks a non-empty value from the most recently updated duplicate.

When merging Companies, Insycle performs a synthetic merge:

Leads: Assigned from duplicates to master.
Users: Assigned from duplicates to master.
Tags: Assigned from duplicates to master.
Fields: Use Master Selection By Field to determine what data is retained in the master record on a field-by-field basis. By default, retained from the master. When a value is empty in the master it picks a non-empty value from the most recently updated duplicate.

In addition to the default merge logic, you have two ways of controlling how your records are merged:

Master record selection – Create a series of rules to automatically select the master record for each of the duplicate groups in the Record tab. The first record that is the only one matching a rule will be selected as the master. For example, if only one record in the group has a "Contact Owner" that could be selected as the master. Or, the only record where the, "Bounced Email" value is "False."
Data retention – Values from different records in the duplicate group can be saved to the master record based on rules that you set in the Fields tab. For example, you could choose to keep your "First Name" and "Last Name" fields from the earliest created record in the duplicate group, while keeping the "Owner" from the most recently updated record.

In the event that you don't specify merge logic for a specific field—when a field value is empty in the master record, Insycle picks a non-empty value from the most recently updated duplicate automatically. When in doubt about conflicting field values, include those fields in the CSV report by adding them to the Record tab.

Customized Merge Logic

For situations where you need more granular customization for picking duplicate records to include - or exclude - from the deduplication process, or for picking the master record, and there are no common rules you can apply for all or some of the records, you can customize bulk deduplication using exclusions and pre-defined masters via a CSV file.

Automation

You can schedule your templates to run on an automated, set schedule.

Click the Review button at the bottom of the module page. Then, go through a three-step process to run the operation. In the third step, you can choose the "Automate" tab, and schedule your template.

You can also schedule deduplication automation using Recipes, which are a collection of templates run together. You can view all scheduled automations on the “Automations” page on your dashboard.

Learn More:

Automation and Manual Operations

Preview Changes Before They Go Live

You can preview the changes that you are making to your data before those changes are pushed to your live database. That way, you can check to ensure your deduplication template is working as expected.

Advanced How-Tos

Step 1: Setting Up the Fields

Pick a field that you think has some duplicate values.

Running a very simple match operation like just First and Last Name can be helpful in giving you an idea of what you have, but it is too broad to use for reliable analysis and deduplication. There may be legitimate duplicate names–different people with the same first and last name. You need additional, unique criteria to narrow it down.

Choosing Unique Identifiers

Matching duplicates requires unique identifiers—data that is unlikely to be shared by any other record unless it is a duplicate. If you don't use unique identifiers, you are likely to identify unrelated records as duplicates and may accidentally merge them.

Many CRMs match first names, last names, and email addresses. If all of those match, or are similar, you can confidently determine that the record is a duplicate.

Other unique identifying fields that are commonly used in deduplication include:

- Phone number
- Mailing address
- ID numbers

Define what kind of likeness to look for when deciding if field values should be considered a match.

It's a good idea to start with Exact Match, and begin with easy-to-find duplicates. Iterate through fields and rules you know will surface duplicates, then look for edge cases. Similar Match can be helpful for those edge cases.

Exact Match looks for values that match exactly, with no differences from one record to the next. Any unique identifying fields should use Exact Match.
Similar Match looks for values that may be close but with a one-character difference (like a typo, extra character, or missing character) 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 a Company Name of, “Acme” is found, it could include records with the Company Name values “Akme, acm, Acma,” etc., as a match.
Be careful if using Similar Match, as the looser criteria can incorrectly identify non-duplicates as duplicates. It is best to only use Similar Match with very open and generic fields, and only after trying everything else.

*Note that the ID field can only be Exact Match, never Similar Match.

Specify parts of a field value to ignore, such as specific text, whitespace, or characters. These won’t be considered as part of the matching process.

Ignore Symbols and Whitespace when comparing phone numbers.
Ignore HTTP, www, subdomain, or top-level domain (.com vs co.uk) when comparing websites or email domains is a great way to catch more advanced duplicates.
Insycle comes preloaded with terms to ignore. If you select Common Terms, click the Terms button to view and edit this list on the Common Terms tab.
If you select Text (substrings), click the Terms button, then the Ignored Text tab, and enter text to be ignored. Separate multiple substrings (or phrases) with a new line.

Note: If you’ve set up Ignored terms or strings, don’t forget to also enable them. Select the Ignored > Common Terms or Text (substrings) checkbox.

Define specific portions of the field value to compare.

Compare the entire value, the first word, any two words, just the first five letters, last nine characters, etc.

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.

To match against one field value OR another, you will need to run two different templates. For example, if you want to use fields like Phone Number OR Mobile Phone Number, you’ll run one template for Phone Number, then a second configured the same except with the Mobile Phone Number field.

The searched value must have four or more characters. For example, values of “Joe” will be ignored.

Step 1: Matching Using Two Different Fields

Sometimes, you might want to match duplicates using data in two separate fields. For example, you might want to compare your Phone Number field to a Mobile Phone Number 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 in the Advanced tab.

Common Examples of Related Field Matching

Matching Field	Related Fields
Phone Number	Mobile Phone Number, Company Phone
Email Domain	Website, Company Domain
Address	Company Address

Step 1: Allowing Empty Values When Matching

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 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: First Name, Last Name, and Phone Number. But on some of your records, the Phone Number field may be empty. Using the conditions "Empty Allowed in Any Record," or "At Least One Record with Non-Empty," all records with the same name, same phone number, and no phone number will be considered duplicates.

Step 4: Selecting Priority Match vs Absolute Match

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:

Lifecycle Stage is lead
Contact 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.

Step 4: Understanding Master Record Selection

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

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

And 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.

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

Step 4: Control What Field Data is Retained

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.

merge-duplicates-intercom-step-4-field-rules-custom-attributes.png

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

merge-duplicates-intercom-csv-collect-values-custom-attributes.png

Step 4: Customizing Merge Logic

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. You can customize bulk deduplication using exclusions and pre-defined masters via a CSV file.

Tips for Bulk Merging Duplicates

Begin with easy-to-find duplicates. Iterate through fields and rules you know will surface duplicates. Don’t expect to resolve all your duplicates by setting up and running this process once. You will need to run this process multiple times for different fields or nuanced variations.
Each time you get a Merge Duplicates process to run the way you want in your database, save it as a template. When you have a solid set of templates that reliably resolve most of your dupes, you can put them together as a Recipe that can run on a regular, automated schedule.
You may also need to look for edge cases that fall outside your standard rules. These may be templates you run manually so you can make adjustments based on what you find.
Do some experimentation. Use the Preview mode and CSV report to analyze patterns in the duplicates. You may learn what is causing the duplicates and learn how to avoid having them in the first place.

Troubleshooting

If you're not seeing the results you expect when merging duplicates, consider these issues:

Not all identified duplicates are merging into the master

You have duplicate records that have been identified by Insycle 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.

Insycle was unable to determine the master record

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

Cannot determine master record because multiple records (#) satisfy the master selection rules. In ‘Master Selection’, change/add/reorder the rules such that only one record satisfies them (if cannot determine master based on field values, use ‘ID is lowest’ as the last rule).

This error means that based on the master rules you set, Insycle could not figure out which would be the master.

Check Step 4 to ensure that you have Priority Match selected and not Absolute Match.

With Priority Match, the rules configured in the Records tab of Step 4 are processed in order and 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 meet any of the criteria on the list more than the others. In this case, you'll need to experiment with Step 4, reordering or adding additional rules for fields likely to have unique values.

Non-duplicate records are being merged together

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.

Insycle isn't finding any duplicates

Most of the time when Insycle can't find duplicates, it is due to your matching rules in Step 1. To better understand how to set up your rules, it is important to analyze the underlying data. A useful exercise can be to set up your matching filters to look for exact matches of just First Name and Last Name.

When you click the Find button, 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, click the gear button on the right side of the Record Viewer pane. Here, you can add any field in your database as a column to the Record Viewer to better understand the data inside of these records.

There are errors in the CSV Result column

If the Result column of the CSV displays an error, read the error text for help figuring out how to resolve the problem.

The most common error is:

This means that based on all the rules, Insycle could not figure out which would be the master. None of the records meet more of the rules than others. In this case, you'll need to experiment with reordering or adding additional fields likely to have unique values under Step 4.

It's taking a long time for Insycle to find duplicates

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.

merge-duplicates-linkedin-bio-step-1-match-parts-last-9-chars.png

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

merge-duplicates-linkedin-bio-step-1-ignored-text-terms-button.png

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

merge-duplicates-linkedin-bio-step-1-ignored-text-popup.png

For more help troubleshooting issues with Insycle, refer to our Troubleshooting Issues article.

Frequently Asked Questions

I already have a list of duplicates, can Insycle bulk merge them?

Yes. You can use a customized list of duplicates and use the Magical Import module to tag duplicates in your CRM, then use the Merge Duplicates module to deduplicate in bulk. Include ID numbers from your connected CRM in your CSV.

Can Insycle deduplicate across leads and users?

Yes, Insycle can deduplicate across leads and users at the same time. Please check out this article to learn more: Deduplicate Across Intercom Users and Leads.

Why can I only process 50 duplicate groups at a time?

Insycle shows 50 records on the module 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.

How do I ensure that I am not merging non-duplicate records together?

Currently, there are two ways to make sure that the records that you are merging are indeed 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 risk when merging duplicates by narrowing your filter in step 1. Use Exact Match instead of Similar Match. Make sure that you are using true 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.

Does Insycle offer an Intercom Inbox app?

Yes, Insycle does offer an intercom inbox app. To learn more, check this article: Deduplicate in Intercom Inbox with the Insycle App.

How many duplicates can I merge into one master record?

You can merge as many duplicates as you would like into one single master record. This setting is available in Step 3 of the Merge Duplicates module.

This setting is here to ensure that if you set too broad of a filter, you do not accidentally merge many non-duplicate records together on accident. You can change the setting as needed to match the size of your duplicate groups. If you are going to set this number at a high level, it is a good idea to run in Preview Mode first to make sure your deduplication template is operating as you intend.

Does the paid subscription have any limits on the number of records that can be identified and merged?

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

Can I select which data is retained in my master record on a field-by-field basis?

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 above for more detail.

I need to exclude some records from deduplication. Can I do that?

Yes. You can exclude records from deduplication by including a "Deduplication Exclude" field in your CSV, as detailed in this help article.

Insycle is having trouble determining a master record. What could be causing this issue?

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

This error means that based on the master rules you set, Insycle could not figure out which would be the master.

Check Step 4 to ensure that you have Priority Match selected and not Absolute Match.

My team needs to review and approve the master, can I accommodate that with Insycle?

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. 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, 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 detail.

Do my matching fields have to match each other exactly?

No, your field data does not need to match exactly. The Similar Match Comparison Rule found 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, “huey@coahulldu.co” is found, it could include records with the values “hueyy@coahulldu.co," or "hue.y@coahulldu.co,” as a match.

Do pay close attention when using Similar Match as the looser criteria can incorrectly identify non-duplicates as duplicates.

Review the Similar Matching best practices for more detail.

How can I find duplicates when one field is empty?