Manage Duplicate Records. salesforce Salesforce Organization
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Pubblicità
Set Up and Maintain Your Salesforce Organization Manage Duplicate Records
Manage Duplicate Records
Duplicate Management
Maintaining clean and accurate data is one of the most important things you can do to help your organization get the most out of Salesforce. Use Data.com Duplicate Management to control whether and when users can create duplicate records in Salesforce; customize the logic that’s used to identify duplicates; and create reports on the duplicates that users save.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Note: Duplicate Management uses Data.com technology, but does not require a Data.com
license.
Available in:
After Duplicate Management is set up, here’s how it works.
•
When a user attempts to save a new record, the record is first compared with existing Salesforce records to identify possible duplicates (1). The criteria used to compare records and identify the possible duplicates are defined by a matching rule. Next, a list of possible duplicates is returned (2). What happens when the record being saved is identified as a possible duplicate
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer depends on what’s defined in the duplicate rule (3). For example, the duplicate rule could block users from saving the possible duplicate record or allow them to save it anyway. Both the Block and Allow options include an alert, which tells users why they can’t save the record and what they need to do. The Allow option includes the ability to report on the duplicate records.
•
When a user attempts to save an edited record, the record is first checked to see if the user has changed the value of a matching rule field. If so, the duplicate management process works as described for new records. If not, no further action is taken and duplicates are not detected.
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Set Up and Maintain Your Salesforce Organization Duplicate Management Concepts
For a list of limits, see Duplicate Management Limits.
SEE ALSO:
Set Up Duplicate Management in Salesforce
Duplicate Management Concepts
To configure Data.com Duplicate Management more effectively, it’s important to understand some key concepts.
IN THIS SECTION:
Duplicate rules are used to control whether and when users can save duplicate records within
Salesforce.
Matching rules are used to identify duplicate records within Salesforce.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
408
Set Up and Maintain Your Salesforce Organization Duplicate Management Concepts
Quickly see a list of duplicate records, grouped into duplicate sets, by clicking the Duplicate Record Sets tab. To do so, your organization needs to use the report action with its duplicate rules.
If your organization uses Data.com Duplicate Management, you can view any system errors that prevent the duplicate rules or matching rules from running successfully.
How Duplicate Management Affects Your Users
When you’ve created and activated duplicate rules and your users try to save a record that’s identified as a possible duplicate, users will be given guidance on how to proceed. This is what they’ll see.
Duplicate Rules
Duplicate rules are used to control whether and when users can save duplicate records within
Salesforce.
Duplicate rules tell Salesforce what action to take when a user attempts to create a duplicate record.
Each duplicate rule needs to include at least one matching rule to identify which existing records are possible duplicates.
You can configure your duplicate rule to perform an action when a new record is created and when an existing record is edited. However, the rule will only run for edited records if the fields being edited are included in the associated matching rule.
Example: The duplicate rule can block users from saving records that have been identified as possible duplicates or allow them to save them anyway. Both the Block and Allow options include an alert, which tells users why they can’t save the record and what they need to do.
The Allow option includes the ability to report on the duplicate records.
SEE ALSO:
Create or Edit Duplicate Rules
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
Matching Rules
Matching rules are used to identify duplicate records within Salesforce.
Watch a video: Understanding Matching Rules (4:32)
A matching rule is made up of individual fields that are assembled into an equation. Each field contains matching criteria that tell the rule how to compare the fields and what conditions need to be met for the specific field to be considered a match.
After a matching rule is activated, one or more match keys are automatically created and applied to existing records. (Also known as indexing, this process improves performance and returns a better set of match candidates because the matching rule is only looking for duplicates among records with the same match key.)
When the matching rule is run, it compares each field against the corresponding field in existing records that share the same match keys, and uses the matching criteria to determine how closely the fields, and ultimately the records, match.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
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Set Up and Maintain Your Salesforce Organization Duplicate Management Concepts
Example: A simple matching rule might specify that if two records’
and
Phone
values match exactly, they are possible duplicates. Or you can use a variety of “fuzzy” matching methods to compare the fields.
Use matching rules with duplicate rules to manage whether and when users are allowed to create duplicate records within Salesforce.
You can use the standard matching rules or create your own custom matching rule. We recommend you use the standard matching rules because they’ve been carefully designed to return the best possible set of match candidates.
SEE ALSO:
Create or Edit Custom Matching Rules
Duplicate Record Sets
Quickly see a list of duplicate records, grouped into duplicate sets, by clicking the Duplicate Record
Sets tab. To do so, your organization needs to use the report action with its duplicate rules.
When a user saves a record that’s identified as a duplicate by a duplicate rule with the report action:
•
The saved record and all its duplicates, up to 100, will be assigned to a new or existing duplicate record set.
•
The saved record and each of its duplicates will be listed as a duplicate record item within the duplicate record set.
•
If the duplicate rule is configured to find duplicates across objects, all cross-object duplicates will be listed as duplicate record items within the duplicate record set.
Duplicate record sets and duplicate record items can be used to do the following.
•
•
Create custom fields
•
Write validation rules, triggers, and workflow rules
•
Modify the fields that can appear on the respective page layouts
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
When using duplicate record sets, keep a few things in mind.
•
By default, duplicate record sets are visible to only administrators, but the administrator can grant visibility to other users.
•
If a lead is identified as a duplicate but converted before the duplicate record set is created, the converted lead won’t be included in a duplicate set.
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Set Up and Maintain Your Salesforce Organization Duplicate Management Concepts
Duplicate Error Logs
If your organization uses Data.com Duplicate Management, you can view any system errors that prevent the duplicate rules or matching rules from running successfully.
From Setup, enter
Duplicate Error Logs
in the
Quick Find
box, then select Duplicate
Error Logs. There, you can see which, if any, errors occured. Error logs are deleted after 90 days.
Example: Here are some scenarios that could produce an error on the log.
•
The match engine used for fuzzy matching is temporarily unavailable. Therefore, any matching rules that include fuzzy matching methods will not run.
•
The Report action on duplicate rules fails because the system is unable to create a duplicate record set.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
How Duplicate Management Affects Your Users
When you’ve created and activated duplicate rules and your users try to save a record that’s identified as a possible duplicate, users will be given guidance on how to proceed. This is what they’ll see.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
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Set Up and Maintain Your Salesforce Organization Duplicate Management Concepts
•
All duplicate rules include a system-generated message (1) that tells the user how many possible duplicates were found. The number of possible duplicates includes only the records the user has access to, even if the duplicate rule’s record-level security was set to
Bypass sharing rules
. (The
Bypass sharing rule
option tells the associated matching rule to compare all records, regardless of the user’s access.) If the user doesn’t have access to any of the records that are identified as possible duplicates, then this message just says there are duplicates detected and the number of duplicates isn’t included. The possible duplicates displayed in the list only includes records the user has access to.
•
If your duplicate rule includes an alert, it will appear beneath the system-generated message (2).
•
If your duplicate rule allows users to save a record even though it might be a possible duplicate, the Save (Ignore Alert) button is present (3). If your duplicate rule blocks users from saving a record that is a possible duplicate, the Save button is present but the record cannot be saved successfully until the user makes the necessary changes to the record so it’s no longer flagged as a possible duplicate.
•
The list of possible duplicates (4) includes only records the user has access to. The fields shown in the list include only fields the user has access to (up to the first 7 fields that were compared by the associated matching rule). A maximum of 5 records are displayed in this list, but if more than 5 duplicates are found, users can click Show All >> to see full list of records, up to 100. Records are listed in the order they were last modified. Users can go directly to one of the records in the list by clicking on its link.
•
The highlighted fields (5) are the fields that were compared by the associated matching rule and determined to match.
SEE ALSO:
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Set Up and Maintain Your Salesforce Organization Set Up Duplicate Management in Salesforce
Set Up Duplicate Management in Salesforce
To use Data.com Duplicate Management in your organization, you need two separate rules: a duplicate rule and a matching rule. The duplicate rule tells Salesforce what action to take when duplicates are identified. The matching rule defines how records are compared to one another to identify possible duplicates.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
IN THIS SECTION:
Create or Edit Duplicate Rules
Use duplicate rules to define what happens when a user tries to save a duplicate record.
Create or Edit Custom Matching Rules
Use matching rules to determine how two records are compared and identified as duplicates.
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
Create Custom Report Types for Duplicate Record Reports
If your organization uses the Report action with its duplicate rules, you can run reports to analyze the quality of your data and to see how well your duplicate rules are working. That way, you can fine tune your duplicate rules if needed. First, you’ll need to set up the appropriate custom report types.
Create or Edit Duplicate Rules
Use duplicate rules to define what happens when a user tries to save a duplicate record.
Watch a demo: Managing Duplicate Records in Salesforce with Duplicate Rules (3:12)
In order for users to see the list of possible duplicates detected by the duplicate rule, they must have read access to the object defined in the rule.
1. From Setup, enter
Duplicate Rules
in the
Quick Find
box, then select Duplicate
Rules.
2. To edit an existing rule, click the rule name, then click Edit. To create a new rule, click New
Rule , then select the object you want the rule to apply to.
3. Enter the rule details, including the rule’s name, description, and record-level security settings.
4. Select which action will occur when a user tries to save a duplicate record.
If the action includes an alert to users, we’ll provide default alert text that you can customize.
Only the Allow action includes the report option.
5. In the Matching Rules section, first select the object that records will be compared with. Then select which matching rule will determine how records are identified as duplicates.
The list includes all available matching rules for the selected object. If none of the matching rules in the list are what you want, select
Create New Matching Rule
.
Tip: We recommend you use the standard matching rules because they’ve been carefully designed to return the best possible set of match candidates. Just be sure you’ve activated them.
If, however, you decide to create a new matching rule, we recommend you first finish creating your duplicate rule. Then create and activate the new matching rule. When you come back to the duplicate rule, it will automatically have the newly created matching rule associated it, as long as it didn’t already have an associated matching rule.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
USER PERMISSIONS
To create, edit, or delete duplicate rules:
•
“Customize Application”
To activate and deactivate duplicate rules:
•
“Customize Application”
To view duplicate rules:
•
“View Setup and
Configuration”
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Set Up and Maintain Your Salesforce Organization Set Up Duplicate Management in Salesforce
6. Make sure you’ve selected the field mapping for each matching rule, if needed.
If the matching rule is comparing records from two different objects or uses custom fields:
•
You’ll need to decide how you want the fields from the first object to be compared to the fields from the second object. For example, you might map a custom field called
Work Email
to the standard
field.
•
Some data may be truncated prior to matching two text fields with different maximum lengths.
7. If you want your duplicate rule to run only if specific conditions are met, specify the conditions.
For example, you could add a condition that tells the rule to run only if the record was entered by a user with a certain profile or role, or if the record includes a specific country or state.
8. Save the rule.
9. Activate the rule.
For the activation to succeed, all associated matching rules must be active.
10. If you have more than one active duplicate rule for a particular object, you may want to adjust the order in which the rules are processed. You can reorder rules by clicking Reorder from any rule’s detail page.
Tip: If the first duplicate rule finds a match for a particular record, that record will not be evaluated by subsequent duplicate rules. Therefore, you should order your duplicate rule so that rules with the Block action are run before rules with the Allow action.
SEE ALSO:
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Set Up and Maintain Your Salesforce Organization Set Up Duplicate Management in Salesforce
Create or Edit Custom Matching Rules
Use matching rules to determine how two records are compared and identified as duplicates.
Watch a Demo (3:39)
1. From Setup, enter
Matching Rules
in the
Quick Find
box, then select Matching
Rules.
2. If editing an existing matching rule, make sure the rule is inactive.
3. Click New Rule or Edit next to the existing rule you want to edit.
4. Select which object this matching rule will apply to.
5. Enter a name and description for the rule.
6. Enter the
.
The matching criteria is where you define which fields to compare and how. To add additional fields (up to 10 total) click Add Filter Logic... and then Add Row.
7. If you need to adjust the matching equation, click Add Filter Logic.... Here you can, for example, manually change an AND expression to an OR expression.
8. Save the rule.
9. Activate the rule.
The activation process may take some time, so we’ll send you an email when the process is complete and your matching rule is ready to use.
After the matching rule is active, it’s available to use with other Data.com Duplicate Management
tools. For example, using a matching rule with a duplicate rule
tells Salesforce to take certain actions when users try to save a record the matching rule has identified as a duplicate.
SEE ALSO:
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
USER PERMISSIONS
To create, edit, or delete matching rules:
•
“Customize Application”
To activate and deactivate matching rules:
•
“Customize Application”
To view matching rules:
•
“View Setup and
Configuration”
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Set Up and Maintain Your Salesforce Organization Set Up Duplicate Management in Salesforce
Create Custom Report Types for Duplicate Record Reports
If your organization uses the Report action with its duplicate rules, you can run reports to analyze the quality of your data and to see how well your duplicate rules are working. That way, you can fine tune your duplicate rules if needed. First, you’ll need to set up the appropriate custom report types.
The only records that will appear in these reports are:
•
Records identified as duplicates by duplicates rules that include the report action.
•
Records that were manually added to the Duplicate Record Set object.
1. Make sure you’re familiar with custom report types and the general steps for creating and maintaining them.
2. Create custom report types with the appropriate object relationships and configure them as necessary.
Here are some examples of custom report types to get you started.
Report Type
Account
Duplicates
Contact
Duplicates
Create reports on the duplicate contacts that were found by your duplicate rules.
Contacts
Lead Duplicates Create reports on the duplicate leads that were found by your duplicate rules.
Leads
All Duplicates
Possible Use A (Primary
Object)
Create reports on the duplicate accounts that were found by your duplicate rules.
Accounts
B
Duplicate Record
Items
Duplicate Record
Items
Duplicate Record
Items
Additional
Steps
Create reports to see how well your duplicate rules are performing.
Duplicate Record
Set
Duplicate Record
Items
Add the
Duplicate
Rule Name lookup field to the Duplicate
Record Set page layout.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
USER PERMISSIONS
To create or update custom report types:
•
“Manage Custom Report
Types”
To delete custom report types:
•
“Modify All Data”
3. Deploy the report types you want to make available to users.
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
4. Let users know that they can create reports using these custom report types.
SEE ALSO:
Matching Rule Reference
Here’s some additional information that will help you understand how matching rules work and how to use them.
EDITIONS
IN THIS SECTION:
We’ve provided several standard matching rules that you can use with Data.com Duplicate
Management tools, such as duplicate rules. Each standard matching rule has been carefully designed to return the best possible set of match candidates for accounts, contacts, or leads.
Matching Criteria for Matching Rules
Matching rules use criteria to determine how closely a field on a new or edited record matches the same field on an existing record, and, ultimately, whether the two records match. When you create a custom matching rule, you need to define certain criteria. Standard matching rules include additional criteria, all of which are defined for you.
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
Matching Methods Used with Matching Rules
The matching method is the part of the matching rule’s matching criteria that determines how a specific field in one record is compared to the same field in another record. We’ve provided an exact matching method and a variety of fuzzy matching methods.
Matching Algorithms Used with Matching Methods
The matching method and matching algorithm are part of the matching rule’s matching criteria. Together, they determine how a specific field in one record is compared to the same field in another record and whether the fields are considered matches.
Match keys are used to increase the effectiveness of matching rules. By understanding how match keys are created, you’ll get a better sense of how matching rules work.
Match Keys Used by Standard Matching Rules
Match keys are used to increase the effectiveness of matching rules. Review the match key information for a better understanding of how standard matching rules work.
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Standard Matching Rules
We’ve provided several standard matching rules that you can use with Data.com Duplicate
Management tools, such as duplicate rules. Each standard matching rule has been carefully designed to return the best possible set of match candidates for accounts, contacts, or leads.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
IN THIS SECTION:
Standard Account Matching Rule
Like all matching rules, the standard matching rule used for account records is made up of fields that are arranged into an equation. Each field contains matching criteria that the rule uses to determine how closely the field matches the same field in an existing record, and ultimately whether the record is a match.
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
Standard Contact and Lead Matching Rule
Like all matching rules, the standard matching rule used for contact and lead records is made up of fields that are arranged into an equation. Each field also contains matching criteria that the rule uses to determine how closely the field matches the same field in an existing record, and ultimately whether the record is a match.
Standard Account Matching Rule
Like all matching rules, the standard matching rule used for account records is made up of fields that are arranged into an equation.
Each field contains matching criteria that the rule uses to determine how closely the field matches the same field in an existing record, and ultimately whether the record is a match.
Matching Equation
Important: In order for the Standard Account Matching Rule to return matches accurately, the new or edited record must include a value in the
Account Name and either the
City
or
ZIP
fields.
Rule Name
Standard Account Matching Rule
Matching Equation
(
Account Name
AND
Billing Street
)
OR (
Account Name
AND
City
)
OR (
Account Name
AND
ZIP
)
OR (
Account Name
AND
Phone
)
OR (
Website
AND
Phone)
OR (
Website
AND
Billing Street
)
Matching Criteria
For a definition of each matching criterion, see Matching Criteria for Matching Rules on page 423.
Special Handling Field Matching
Algorithms
Scoring
Method
Account
Name
Acronym
Edit Distance
Maximum
Threshold Blank
Fields
70 Don’t match
Removes words such as
Inc
and
Corp
before comparing fields. Also, company names are normalized. For example,
1st
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Field
Phone
ZIP
Matching
Algorithms
Exact
Exact
Exact
Scoring
Method
Weighted
Average
Billing
Street
Edit Distance
Exact
Weighted
Average
Weighted
Average
Threshold Blank
Fields
80
Special Handling
National Bank
is normalized to
First National
Bank
.
Don’t match on all sections expect
Area Code, which ignores blank fields
Phone numbers are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field. This process works best with North American data.
•
•
International code (Exact, 10% of field’s match score)
Area code (Exact, 50% of field’s match score)
•
Next 3 digits (Exact, 30% of field’s match score
•
Last 4 digits (Exact, 10% of field’s match score)
For example, suppose these two phone numbers are being compared:
1-415-555-1234
and
1-415-555-5678
.
All sections match exactly except the last 4 digits, so the field has a match score of 90, which is considered a match because it exceeds the threshold of 80.
80 Don’t match
80 Don’t match
Addresses are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field. This process works best with North American data.
•
Street Number (Exact, 20% of field’s match score)
•
Street Name (Edit Distance, 50% of field’s match score)
•
Street Suffix (Exact, 15% of field’s match score)
•
Suite Number (Exact, 15% of field’s match score)
For example, suppose these two billing streets are being compared:
123 Market Street, Suite 100
and
123 Market Drive, Suite 300
.
Because only the street number and street name match, the field has a match score of 70, which is not considered a match because it’s less than the threshold of 80.
ZIP codes are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field.
•
First 5 digits (Exact, 90% of field’s match score)
•
Next 4 digits(Exact, 10% of field’s match score)
For example, suppose these two ZIP codes are being compared:
94104–1001
and
94104
.
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Field Matching
Algorithms
Scoring
Method
City
Edit Distance
Exact
Maximum
Website
Exact Maximum
85
100
Threshold Blank
Fields
Special Handling
Because only the first 5 digits match, the field has a match score of 90, which is considered a match because it exceeds the threshold of 80.
Don’t match
Don’t match
Only the website domain is compared. For example, a field value http://www.salesforce.com
salesforce.com
.
becomes
SEE ALSO:
Standard Contact and Lead Matching Rule
Like all matching rules, the standard matching rule used for contact and lead records is made up of fields that are arranged into an equation. Each field also contains matching criteria that the rule uses to determine how closely the field matches the same field in an existing record, and ultimately whether the record is a match.
Matching Equation
Rule Name
Standard Contact Matching Rule
Standard Lead Matching Rule
Matching Equation
(
First Name
AND
Last Name
AND
Title
AND
Company Name
)
OR (
First Name
AND
Last Name
AND
)
OR (
First Name
AND
Last Name
AND
Phone
AND
Company Name
)
OR (
First Name
AND
Last Name
AND
Mailing
Street
AND (
City
OR
ZIP
OR
Phone
)
OR (
First Name
AND
Last Name
AND
Mailing
Street
AND
Title
)
OR (
First Name
AND
Last Name
AND
Title
AND
)
OR (
First Name
AND
Last Name
AND
Phone
)
Matching Criteria
For a definition of each matching critetia, see Matching Criteria for Matching Rules on page 423.
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Fields on
Contacts
Fields on
Leads
First Name First
Name
Last Name Last
Name
Matching
Algorithms
Exact
Initials
Jaro-Winkler
Distance
Metaphone 3
Name Variant
Exact
Keyboard
Distance
Metaphone 3
Scoring
Method
Threshold
Maximum 85
Maximum 90
Title Title Acronym
Exact
Kullback-Liebler
Distance
Maximum 50
Maximum 70 Account
Name
Company Acronym
Edit Distance
Exact
Phone
Phone
Exact
Exact
Maximum
Weighted
Average
100
80
Blank Fields
Don’t match
(Ignores blank fields when
Email is included in field grouping)
Don’t match
Special Handling
Don’t match
(Ignores blank fields when
Email is included in field grouping)
If record contains a value for the both
First
Name
and
Last Name
fields, those values will be transposed to account for possible data entry mistakes.
For example, if the first name is
George
and the last name is
Michael
, the matching rule will also evaluate first name as
Michael
and the last name as
George
.
Don’t match
If record contains a value for the both
First
Name
and
Last Name
fields, those values will be transposed to account for possible data entry mistakes.
For example, if the first name is
George
and the last name is
Michael
, the matching rule will also evaluate first name as
Michael
and the last name as
George
.
Don’t match
Don’t match on all sections expect Area
Code, which ignores blank fields
Phone numbers are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field. This process works best with
North American data.
•
International code (Exact, 10% of field’s match score)
•
Area code (Exact, 50% of field’s match score)
•
Next 3 digits (Exact, 30% of field’s match score
•
Last 4 digits (Exact, 10% of field’s match score)
For example, suppose these two phone numbers are being compared:
1-415-555-1234
and
1-415-555-5678
.
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Fields on
Contacts
Fields on
Leads
Matching
Algorithms
Scoring
Method
Threshold Blank Fields Special Handling
Mailing
Street
Mailing
ZIP/Postal
Code
Mailing
City
Street
ZIP/Postal
Code
City
Exact
Exact
Edit Distance
Exact
Weighted
Average`
Weighted
Average
Maximum
80
80
85
Don’t match
All sections match exactly except the last 4 digits, so the field has a match score of 90, which is considered a match because it exceeds the threshold of 80.
Addresses are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field. This process works best with North
American data.
•
Street Name (Edit Distance, 50% of field’s match score)
•
Street Number (Exact, 20% of field’s match score)
•
Street Suffix (Exact, 15% of field’s match score)
•
Suite Number (Exact, 15% of field’s match score)
For example, suppose these two adresses are being compared:
123 Market Street,
Suite 100
and
123 Market Drive,
Suite 300
.
Because only the street number and street name match, the field has a match score of 70, which is not considered a match because it’s less than the threshold of 80.
ZIP codes are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field.
•
First 5 digits (Exact, 90% of field’s match score)
•
Next 4 digits(Exact, 10% of field’s match score)
Don’t match
SEE ALSO:
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Matching Criteria for Matching Rules
Matching rules use criteria to determine how closely a field on a new or edited record matches the same field on an existing record, and, ultimately, whether the two records match. When you create a custom matching rule, you need to define certain criteria. Standard matching rules include additional criteria, all of which are defined for you.
Note: This release contains a beta version of Data.com Duplicate Management that is production quality but has known limitations. You can provide feedback and suggestions on the Salesforce Success Community . For information on enabling this feature for your organization, contact Salesforce.
Criterion Definition Automatically
Defined for
Custom
Matching
Rules
Field Indicates which field to compare. When selecting fields, keep in mind that:
•
The available fields depend on which object the matching rule applies to and include both standard and custom fields.
•
The supported input field types are email, lookup relationship, number, phone, standard picklists, custom picklists (single-select only), text, and URL.
•
An auto-numbered lookup relationship field cannot be used in a matching rule.
•
If you enable
State
and
Country
picklists for your organization, we recommend using State/Province Code and Country Code in your matching rules. These fields yield better duplicate detection results than the state and country text fields.
Matching
Method
Defines how the fields are compared. We’ve provided an exact matching method and various fuzzy matching methods. Each matching method is further defined by matching algorithms and other criteria.
For more information about matching methods, see Matching Methods
Used with Matching Rules on page 426.
Matching
Algorithm
Defines the logic that determines whether 2 fields match. For the Exact matching method, the Exact matching algorithm is automatically used.
For the Fuzzy matching method, various fuzzy matching algorithms can be used. Each matching algorithm used is automatically given a match score based on how closely it’s able to match the two fields. For example, if you select Exact matching and the two fields match, the match score is 100. If the 2 fields don’t match, the match score is 0.
For more information about matching algorithms, see
Algorithms Used with Matching Methods on page 428.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Criterion Definition
Match Blank
Fields
Specifies how blank fields affect whether the 2 fields being compared are considered matches. If you select the
Match Blank Fields
checkbox for any field, and that field is blank in both records being compared, the fields are considered matches. If, however, you select the
Match
Blank Fields
checkbox for any field, and that field is blank in only one of the records being compared, the fields are not considered matches.
If you don’t select the
Match Blank Fields
checkbox for any field, and that field is blank in both records being compared, the fields are not considered matches.
Scoring
Method
Determines how the matching algorithms’ match scores are calculated to come up with one match score for the field. Each matching algorithm used is automatically given a match score based on how closely it’s able to match the two fields. Scoring method is used only by the standard matching rules.
Average
: Uses the average match score.
Maximum
: Uses the highest match score.
Minimum:
Uses the lowest match score.
Weighted Average
Uses the weight of each matching method to determine the average match score.
Threshold
Match Key
Determines the minimum match score needed for the field to be considered a match. The field is automatically given a match score based on how closely it matches the same field in an existing record.
A code that allows the matching rule to quickly return a list of possible duplicates. Once the matching rule is activated, the match key is automatically applied to all existing records so that when the matching rule runs, it’s only looking for duplicates among records with the same match key. This process improves performance and returns a better set of match candidates.
For more information about match keys, including examples, see Match Keys and Matching Rules
on page 429.
Automatically
Defined for
Custom
Matching
Rules
Example
Example: Assuming your custom contact matching rule includes the following criteria, here’s how records are compared and matched.
•
Matching equation is
AND (
Phone
OR
City
).
•
All fields use the Exact matching method.
•
The
Match Blanks Fields
checkbox is selected for
Phone
and
City
.
New Record A
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Phone
415-555-1234
City
San Francisco
Existing Records Compared with New Record A
Phone
3
4
1
2
5
Record Email
0 none 0 [email protected]
100
Match
Score
100
100
415-555-1234 none
415-555-1234
415-555-1234
415–555-7777
100
100
0
Phone
Match
Score
100
0
City
none
San Francisco
San Francisco
Oakland
San Jose
New Record B
Phone
none
City
none
Existing Records Compared with New Record B
Phone
1
2
3
Record
4
5
0 none 0
Match
Score
100
100
100
415-555-1234 none none
415-555-1234
415-555-1234
0
0
Phone
Match
Score
0
100
100
City
none
San Francisco none
San Francisco
Oakland
100
0
0
City
Match
Score
0
100
Record
Matches?
Yes
Yes
No
No
No
0
0
City
Match
Score
100
0
100
Record
Matches?
Yes
Yes
Yes
No
No
SEE ALSO:
425
Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Matching Methods Used with Matching Rules
The matching method is the part of the matching rule’s matching criteria that determines how a specific field in one record is compared to the same field in another record. We’ve provided an exact matching method and a variety of fuzzy matching methods.
Matching Method
Exact
Fuzzy
Description
This method looks for strings that match a pattern exactly. If you’re using international data, we recommend you use the Exact matching method with your matching rules.
This method looks for strings that match a pattern approximately. We’ve provided the logic for a variety of fuzzy matching methods.
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
For a definition of each matching criteron, see Matching Criteria for Matching Rules on page 423.
Special Handling Fuzzy Matching Method Matching
Algorithms
Fuzzy: First Name Exact
Initials
Jaro-Winkler
Name Variant
Fuzzy: Last Name Exact
Keyboard
Distance
Metaphone 3
Fuzzy: Company Name
Fuzzy: Phone
Acronym
Exact
Syllable
Alignment
Exact
Scoring
Method
Maximum
Threshold
85
Maximum
Maximum
Weighted
Average
90
70
80
The
Middle Name
field, if used in your matching rule, is compared by the Fuzzy: First
Name matching method.
Removes words such as
Inc normalized. For example,
and
IBM
Corp
before comparing fields. Also, company names are
is normalized to
International Business Machines
Phone numbers are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field. This process works best with
North American data.
•
International code (Exact, 10% of field’s match score)
•
Area code (Exact, 50% of field’s match score)
•
Next 3 digits (Exact, 30% of field’s match score
.
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Fuzzy Matching Method Matching
Algorithms
Scoring
Method
Threshold Special Handling
•
Last 4 digits (Exact, 10% of field’s match score)
For example, suppose these two phone numbers are being compared:
1-415-555-1234
and
1-415-555-5678
.
All sections match exactly except the last 4 digits, so the field has a match score of 90, which is considered a match because it exceeds the threshold of 80.
Fuzzy: City
Fuzzy: Street
Edit Distance
Exact
Exact
Maximum 85
Weighted
Average
80
Fuzzy: ZIP Exact Weighted
Average
80
Addresses are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field. This process works best with North
American data.
•
Street Name (Edit Distance, 50% of field’s match score)
•
Street Number (Exact, 20% of field’s match score)
•
Street Suffix (Exact, 15% of field’s match score)
•
Suite Number (Exact, 15% of field’s match score)
For example, suppose these two billing streets are being compared:
123 Market Street,
Suite 100
and
123 Market Drive,
Suite 300
.
Because only the street number and street name match, the field has a match score of 70, which is not considered a match because it’s less than the threshold of 80.
ZIP codes are broken into sections and compared by those sections. Each section has its own matching method and match score. The section scores are weighted to come up with one score for the field.
•
First 5 digits (Exact, 90% of field’s match score)
427
Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Fuzzy Matching Method Matching
Algorithms
Scoring
Method
Threshold Special Handling
•
Next 4 digits(Exact, 10% of field’s match score)
For example, suppose these two ZIP codes are being compared:
94104–1001
and
94104
.
Because only the first 5 digits match, the field has a match score of 90, which is considered a match because it exceeds the threshold of 80.
Fuzzy: Title Acronym
Exact
Kullback-Liebler
Distance
Maximum 50
Matching Algorithms Used with Matching Methods
The matching method and matching algorithm are part of the matching rule’s matching criteria.
Together, they determine how a specific field in one record is compared to the same field in another record and whether the fields are considered matches.
We’ve provided an exact matching method and a variety of fuzzy matching methods. If the exact matching method is selected, then the exact matching algorithm is automatically used to compare the fields. If one of the fuzzy matching method is selected, then a variety of fuzzy matching algorithms is used to compare the fields. A field can be compared using more than one matching algorithm, and a matching score is given to each matching algorithm based on how closely it’s able to match the fields. The fields being compared by the matching algorithms are not case sensitive.
For more information about the matching methods, see Matching Methods Used with Matching
on page 426.
Matching Algorithms Available with Exact Matching Method
Matching Algorithm
Exact
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
Description
Determines whether two strings are the same. For example, salesforce.com and Salesforce are not considered a match because they’re not exactly the same, and return a match score of 0.
Matching Algorithms Available with Fuzzy Matching Methods
Matching Algorithm
Acronym
Description
Determines whether a business name matches its acronym. For example, Advanced Micro
Devices and its acronym AMD are considered a match and return a match score of 100.
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Matching Algorithm
Edit Distance
Initials
Jaro-Winkler Distance
Keyboard Distance
Kullback Liebler Distance
Metaphone 3
Name Variant
Description
Determines the similarity between two strings based on the number of deletions, insertions, and character replacements needed to transform one string into the other. For example, VP
Sales matches VP of Sales with match score of 73.
Determines the similarity of two sets of initials in personal names. For example, the first name
Jonathan and its initial J match and return a match score of 100.
Determines the similarity between two strings based on the number of character replacements needed to transform one string into the other. This method is best for short strings, such as personal names. For example, Johnny matches Johny with a match score of 97.
Determines the similarity between two strings based on the number of deletions, insertions, and character replacements needed to transform one string into the other, weighted by the position of the keys on the keyboard.
Determines the similarity between two strings based on the percentage of words in common.
For example Director of Engineering matches Engineering Director with a match score of 65.
Determines the similarity between two strings based on their sounds. This algorithm attempts to account for the irregularities among languages and works well for first and last names. For example, Joseph matches Josef with a match score of 100.
Determines whether two names are variation of each other. For example, Bob is a variation of
Robert and returns a match score of 100. Bob is not a variation of Bill and returns a match score of 0.
SEE ALSO:
Match Keys and Matching Rules
Match keys are used to increase the effectiveness of matching rules. By understanding how match keys are created, you’ll get a better sense of how matching rules work.
EDITIONS
A match key is a code that allows a matching rule to quickly return a list of possible duplicates. After the matching rule is activated, the match key is automatically applied to all existing records so that when the matching rule runs, it’s only looking for duplicates among records with the same match key. Also known as indexing, this process improves performance and returns a better set of match candidates.
The match keys for both standard and custom matching rules are automatically created based on the fields in the matching rule. Because each custom matching rule can have only 10 match keys, you’re prevented from saving a matching rule that would require more than 10 match keys.
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
The process of creating match keys includes several steps.
1. The matching rule equation (that is, the arrangement of fields) is rewritten into a standardized format that translates OR statements into AND statements.
2. The fields are normalized using the same methods as standard matching rules. For details, see
Match Keys Used by Standard Matching
3. The standardized field format and the normalized field values are combined to create the match keys.
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Note: We currently don’t create match keys for the
Title
and
Address
fields. Therefore, if those fields are included in your matching rule, they won’t generate match keys.
Example:
Example
Field Name
First Name
Last Name
Company
Field Value
John [email protected]
O’Reilly
Intel Corp.
j
Normalized Field Value
joreilly@intelcom arl intel
Matching Rule Equation
(First Name OR Email) AND
(Last Name OR Company
Standardized Format Match Keys (Field
Combinations)
(First Name AND Last Name)
OR
First Name Last Name
(First Name AND Company)
OR
First Name Company
(Email AND Last Name) OR
(Email AND Company) OR
Email Last Name
Email Company
Match Keys ( with Normalized
Field Values)
jarl jintel joreilly@intelcomarl joreilly@intelcomintel
Match Keys Used by Standard Matching Rules
Match keys are used to increase the effectiveness of matching rules. Review the match key information for a better understanding of how standard matching rules work.
What is a Match Key?
A match key is a code that allows a matching rule to quickly return a list of possible duplicates. After the matching rule is activated, the match key is automatically applied to all existing records so that when the matching rule runs, it’s only looking for duplicates among records with the same match key. Also known as indexing, this process improves performance and returns a better set of match candidates.
How to Read a Match Key
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
430
Set Up and Maintain Your Salesforce Organization Matching Rule Reference
•
The field used in the match key (1)
•
Number of tokens (or character string sets) in the field value to include in match key (2). If no number is present, then all tokens are included.
•
Number of characters per token to include in the match key (3). If no number is present, then all characters are included.
•
Additonal field used in the match key (4)
Normalization of Fields
Before the match keys are applied to any records, the field values of those records are normalized.
Field
Company
First Name
Last Name
Phone
Website
Normalization Details Examples
Expands acronyms. Lowercases first letter of each word. Removes suffixes, such as
Corporation
,
Incorporated
,
Inc
,
Limited
,
Ltd
.
Removes stopwords and
, the
, of
.
IBM = international business machines
Intel Corp. = intel
Removes salutations and all but first letter of first word. Lowercases first letter. Replaces first name with alias, if applicable.
Dr. Jane = j
Mr. Bob= robert = r
Removes special characters and suffixes. Replaces consecutive identical consanants with single consanant. Lowercases first letter. After normalization, the double metaphone algorithm is applied so that misspellings and spelling variants are accounted for.
O’Reilly, Jr. = oreily (without double metaphone)
O’Reilly, Jr. = oreily = arl (with double metaphone)
Removes special characters, such as underscores and periods, from both parts of the email address.
john_doe @salesforce.com = jdoe@salesforcecom [email protected] = jdoe@salesforcecom
Removes all non-digit and non-alpha characters. For all U.S. phone numbers, converts alpha characters to numeric characters and removes leading international code. Removes last four digits.
1-800-555-1234 = 800555
44 20 0540 0202 = 44200540
Removes protocol (http), subdomain (www), and any file path. Then takes only the last two or three tokens, depending on if there are international designations.
http://www.us.salesforce.com/product = salesforce.com
http://www.ox.ac.uk/ = ox.ac.uk
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Set Up and Maintain Your Salesforce Organization Matching Rule Reference
Pre-defined Match Keys
After fields are normalized, the following match keys are applied to all existing records. Also known as indexing, this process occurs when a matching rule is activated.
Match Key
Company (2,6) City (_, 6)
Company (2,6) ZIP (1,3)
First_Name (1,1) Last_Name Email
First_Name (1,1) Last_Name Company (2,5)
First_Name (1,1) Last_Name Phone
First_name (1,1) Last_Name Email (domain)
Website City (_,6)
Objects Applied
To
Account
Example
Account: salesforce.com = salesf
City: San Francisco = sanfra
Key: salesfsanfra
Account
Contact
Lead
Contact
Lead
Account Name: salesforce.com = salesf
ZIP: 94105-5188 = 941
Key: salesf941
Email: [email protected] = [email protected]
Key: [email protected]
First Name: John = j
Last: Doe = doe = t (with double metaphone applied)
Email: [email protected] = [email protected]
Key: [email protected]
Contact
Lead
Contact
Lead
Contact
Lead
Account
First Name: Marc = m
Last Name: Benioff = pnf (with double metaphone applied)
Company: salesforce.com = sales
Key: mpnfsales
First Name: Marc = m
Last Name: Benioff = pnf (with double metaphone applied)
Phone: 1-415-555-1234 = 415555
Key: mpnf415555
First Name: Marc = m
Last Name: Benioff = pnf (with double metaphone applied)
Email: [email protected] = salesforce.com
Key: mpnfsalesforce.com
Website: https://www.salesforce.com = salesforce.com
City: San Francisco = sanfra
Key: salesforce.comsanfra
432
Set Up and Maintain Your Salesforce Organization
Match Key
Website ZIP (1,3)
Duplicate Management FAQs
Objects Applied
To
Account
Example
Website: https://www.salesforce.com = salesforce.com
ZIP: 94105-5188 = 941
Key: salesforce.com941
Duplicate Management FAQs
Answers to common questions about Data.com Duplicate Management.
IN THIS SECTION:
How does duplicate prevention work with Data.com Prospector and Data.com Clean?
Why am I getting an error saying my matching rule uses too many OR operators within groupings?
EDITIONS
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
How does duplicate prevention work with Data.com Prospector and Data.com Clean?
EDITIONS
Adding Records with Data.com Prospector
It depends on what your organization’s Data.com duplicate preferences are.
If your organization does not allow duplicate records to be added to Salesforce from Data.com, then Data.com will block duplicate records from being added to Salesforce and the duplicate rule won’t need to run. The user trying to add records from Data.com will receive an error log detailing which records couldn’t be added because they are duplicates.
If your organization allows duplicate records to be added to Salesforce from Data.com, then the duplicate rules will run. The duplicate rule will determine if the duplicate record is allowed or blocked. Records that are blocked by the duplicate rule will appear in the error log.
Available in: both Salesforce
Classic and Lightning
Experience
Available in:
•
Professional
•
Enterprise
•
Performance
•
Unlimited
•
Developer
Updating Records with Data.com Clean
It depends on what your organization’s duplicate rules are. If your duplicate rule is set to block duplicates on edit, then a record can’t be cleaned if cleaning creates a duplicate.
For Clean jobs, if your duplicate rule is set to block or alert, then a record can’t be cleaned if the cleaning creates a duplicate. An entity error appears in the Clean Jobs History table for any record that can’t be cleaned during a job.
If your duplicate rule is set to allow duplicates on edit, then a record can be cleaned even if it creates a duplicate. In addition, no alert displays when manually cleaning records even if your duplicate rule is set to alert.
433
Set Up and Maintain Your Salesforce Organization Duplicate Management FAQs
Why am I getting an error saying my matching rule uses too many OR operators within groupings?
A matching rule has a limit of 10 fields that are arranged into an equation. When a matching rule is saved, we rewrite the equation into a standardized format that translates the OR statements to AND statements. The standardized format has a limit of 10 rows.
Example: If your matching rule includes the following equation...
(Field 1 OR Field 2) AND
(Field 3 OR Field 4) AND
(Field 5 OR Field 6) AND
(Field 7 OR Field 8)
...it would be rewritten as
(Field 1 AND Field 3 AND Field 5 Field AND 7) OR
(Field 1 AND Field 3 AND Field 5 AND Field 8) OR
(Field 1 AND Field 3 AND Field 6 AND Field 7) OR
(Field 1 AND Field 3 AND Field 6 AND Field 8) OR
(Field 1 AND Field 4 AND Field 5 AND Field 7) OR
(Field 1 AND Field 4 AND Field 5 AND Field 8) OR
(Field 1 AND Field 4 AND Field 6 AND Field 7) OR
(Field 1 AND Field 4 AND Field 6 AND Field 8) OR
(Field 2 AND Field 3 AND Field 5 AND Field 7) OR
(Field 2 AND Field 3 AND Field 5 AND Field 8) OR
(Field 2 AND Field 3 AND Field 6 AND Field 7) OR
(Field 2 AND Field 3 AND Field 6 AND Field 8)OR
(Field 2 AND Field 4 AND Field 5 AND Field 7) OR
(Field 2 AND Field 4 AND Field 5 AND Field 8) OR
(Field 2 AND Field 4 AND Field 6 AND Field 7) OR
(Field 2 AND Field 4 AND Field 6 AND Field 8)
Although this matching rule is within the field limit, it exceeds the row limit of 10 when written in the standardized format, and therefore can’t be saved. You need to refine the matching rule so it uses fewer OR operators within groupings.
SEE ALSO:
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