Deduplicate Across Salesforce Leads and Contacts

Navigate to Data Management > Merge Duplicates, and select the Salesforce database and Contacts 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. With the box checked, Insycle will look at leads and contacts for duplicates, and allow you to merge both down into one singular record.

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

Commonly used matching fields in lead and contact deduplication include:

• First Name + Last Name
• Company Name
• Email Username
• Email Domain
• Company Website
• Phone Numbers

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

Expand Criteria for Matching Duplicates

If you'd like to look at the data in two different fields (that contain similar data) as if it were one, you can set up Related Fields under the Advanced tab. For example, you might want to look at both the Business Phone and Mobile Phone fields for duplicate values.

The Conditions tab provides rules one or more of the records in a duplicate group will need to meet.

• At Least One Record With Non-Empty - At least one record in the duplicate group must contain a value.
• Value Required in All Records - Each record must contain a value in this field to be considered a duplicate.
• Empty Allowed in Any Record - A record can still be considered a duplicate if this field is blank. Allowing empty values requires using two or more fields to identify duplicates.
• 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 have the specified value, the duplicate group will not be merged.

Records that have the same values in the fields from Step 1 are considered matches, whether they are all leads, all contacts, 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 contact 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.

Add more columns to the groups view using the columns layout gear button on the right end of the header to get more context for analyzing the records.

The most efficient and sustainable way to merge duplicates is in Bulk mode. This allows you to set rules for determining the master record automatically across all lead and contact records in your database. You'll be able to 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. The other three records would not exist anymore.

Select the matching method on the right end of the 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 detail.

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.

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 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 Create Date value can be used to determine which Contact Owner value from the duplicate group should be kept.
• 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. The example above will retain the data in the Email field that is using a professional domain rather than a free one.
• 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.
• From master record – Use the value that exists in the master record.
• 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, merging 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 the 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, meaning this excludes the value from the master record itself. 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 and keep the master. Select a destination field to copy and combine values into, then select what field the data should come from.

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 Salesforce 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 to select recipients for the email report. You can also add additional context to the email message.

On the When tab, click the Run Now tab, and select which records to apply the change to (in most cases this will be All), 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.

The Result column identifies which were picked as master, and which were identified as duplicates and merged into the master. You'll see the values:

• Duplicate – The record is part of a duplicate group.
• Master – The master record that was chosen for the duplicate group based on your rules.
• Master (After) – For each duplicate group, the Result column will show the final record's data, based on master selection and field data retention settings.
• Error – If Insycle was not able to determine which record would be the master, an error message will appear here. See the Troubleshooting section below for more detail.

When a field value in the CSV says "(Default)," the CRM will be using its default processes for dealing with the field. This is typically done for blank fields, system IDs, and other specific situations.

If everything in the Result column looks good, return to Insycle and apply 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 Salesforce 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 Salesforce.

Save Templates and Setup Automation to Maintain Formatting

After you've seen the results in Salesforce 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 contacts are merging consistently on an ongoing basis.

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

On the When tab, select Automate, and configure the frequency you'd like the template to run. When finished, click Schedule.

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.

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.

Common Examples of Related Field 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 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.

Just as an experiment you could uncheck the Include Leads checkbox in Step 1. 

You should notice a difference in the number of duplicates found.

For contacts, it's often useful to pick master records based on engagement. For example, the highest number of email clicks, or the most recent email opened. You can also use other statuses to pick a master record such as the furthest along in your sales lifecycle, or the most recently updated record. 

For companies, it's often useful to use associated records to determine the master record. For example, the highest number of associated contacts or deals. 

If you have a connected app, like Salesforce or an ERP system, pick the master record that is syncing with the other apps.

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.

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 Salesforce accounts, you may want to save all of the Account IDs from records that are merged together and deleted. You can add a new custom field, “Merged Account IDs” 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 Account IDs" field, the "Collect non-master values from other field" criteria, and "Account ID" as the other field. 

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

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

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.

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.

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. 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 Step 2: Review Duplicates pane. Here, you can add any field in your database as a column to the view to better understand the data inside of these records.

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:

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 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 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 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.

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 Business Phone field and Mobile Phone Number in case different users are using the phone number 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 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, this means 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.

Yes, Insycle allows you to select which field data is retained in the master record using the Fields tab under Step 4. See Step 4: Set Master Record and Field Data Retention Rules in this article for more details.

Yes. You can exclude records from deduplication by including a Deduplication Exclude field in your CSV, as detailed in this Customize Bulk Deduplication Using Exclusions and Pre-Defined Masters article.

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 detail.

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, “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 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.