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Standard Contact Matching Rule and Standard Lead Matching Rule
The standard contact matching rule and standard lead matching rule identify duplicate contacts and leads using match keys, a matching equation, and matching criteria. They’re activated by default.
Match Keys
Match keys speed up matching by narrowing the potential matches to the most likely duplicates before the rule applies the comprehensive matching equation.
| Contact Match Key Notation | Contact Examples |
|---|---|
Email: john_doe@us.ibm.com = johndoe@ibm.com Key: johndoe@ibm.com |
|
| First_Name (1,1) Last_Name Email | First Name: John = j Last Name: Doe = doe = t (with double metaphone applied) Email: john_doe@us.salesforce.com = johndoe@salesforce.com Key: jt@salesforce.com |
| First_Name (1,1) Last_Name Company (2,5) | First Name: Marc = m Last Name: Benioff = pnf (with double metaphone applied) Company: salesforce.com = sales Key: mpnfsales |
| First_Name (1,1) Last_Name Phone (drop leading 1 and last four digits) | First Name: Marc = m Last Name: Benioff = pnf (with double metaphone applied) Phone: 1-415-555-1234 = 415555 Key: mpnf415555 |
| Lead Match Key Notation | Lead Examples |
|---|---|
Email: john_doe@us.ibm.com = johndoe@ibm.com Key: johndoe@ibm.com |
|
| First_Name (1,1) Last_Name Email | First Name: John = j Last Name: Doe = doe = t (with double metaphone applied) Email: john_doe@us.salesforce.com = johndoe@salesforce.com Key: jt@salesforce.com |
| First_Name (1,1) Last_Name Company (2,5) | First Name: Marc = m Last Name: Benioff = pnf (with double metaphone applied) Company: salesforce.com = sales Key: mpnfsales |
| First_Name (1,1) Last_Name Phone (drop leading 1 and last four digits) | First Name: Marc = m Last Name: Benioff = pnf (with double metaphone applied) Phone: 1-415-555-1234 = 415555 Key: mpnf415555 |
Matching Equations
The standard contact matching rule uses the following matching equation.
(First Name AND Last Name AND Title AND Account Name)
OR (First Name AND Last Name AND Email)
OR (First Name AND Last Name AND Phone AND Account 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 Email)
OR (First Name AND Last Name AND Phone)
The standard lead matching rule uses the following matching equation.
(First Name AND Last Name AND Title AND Company)
OR (First Name AND Last Name AND Email)
OR (First Name AND Last Name AND Phone AND Company)
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 Email)
OR (First Name AND Last Name AND Phone)
Matching Criteria
| Fields on Contacts | Fields on Leads | Matching Algorithms | Scoring Method | Threshold | Blank Fields | Special Handling |
|---|---|---|---|---|---|---|
| First Name | First Name | Exact Initials Jaro-Winkler Distance Metaphone 3 Name Variant |
Maximum | 85 | Don’t match (ignores blank fields when Email is included in field grouping) | If record contains a value for the First Name and Last Name fields, the values are transposed to account for possible data entry mistakes. For example, suppose that the first name is Felix and the last name is Michael. The matching rule also evaluates the first name as Michael and the last name as Felix. |
| Last Name | Last Name | Exact Keyboard Distance Metaphone 3 |
Maximum | 90 | Don’t match (ignores blank fields when Email is included in field grouping) | If record contains a value for the First Name and Last Name fields, those values are transposed to account for possible data entry mistakes. For example, suppose that the first name is Felix and the last name is Michael. The matching rule also evaluates the first name as Michael and the last name as Felix. |
| Title | Title | Acronym Exact Kullback-Liebler Distance |
Maximum | 50 | Don’t match | |
| Account Name | Company | Acronym Edit Distance Exact |
Maximum | 70 | Don’t match | |
| Exact | Maximum | 100 | Don’t match | |||
| Phone | Phone | Exact | Weighted Average | 80 | Don’t match on all sections except 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 determine a score for the field. This process works best with North American data.
For example, these phone numbers are being compared: 1-415-555-1234 and 1-415-555-5678. All sections match exactly except the last four digits. The field has a match score of 90, which is considered a match because it exceeds the threshold of 80. |
| Mailing Street | Street | Edit Distance Exact |
Weighted Average` | 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 determine a score for the field. This process works best with North American data.
For example, these addresses are being compared: 123 Market Street, Suite 100, and 123 Market Drive, Suite 300. The street number and street name match. The field has a match score of 70, which isn’t considered a match because it’s less than the threshold of 80. |
| Mailing ZIP/Postal Code | ZIP/Postal Code | Exact | Weighted Average | 80 | Don’t match | 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 determine a score for the field.
|
| Mailing City | City | Edit Distance Exact |
Maximum | 85 | Don’t match |
