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Standard Person Account Matching Rule
The standard person account matching rule identifies duplicate person accounts using match keys, a matching equation, and matching criteria. To use the rule, first enable person accounts, and then activate rule in Setup.
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.
| Match Key Notation | Examples |
|---|---|
Email: john_doe@us.ibm.com = johndoe@ibm.com Key: johndoe@ibm.com |
|
| First_Initial (1,1) Last_Name City (1,6) | First Initial: J = j Last Name: Doe = doe = t (with double metaphone applied) City: Philadelphia = philad Key: jtphilad |
| First_Initial (1,1) Last_Name ZIP (1,3) | First Initial: J = j Last Name: Doe = doe = t (with double metaphone applied) ZIP: 10001 = 100 Key: jt100 |
Street Address |
123 Maple Avenue Key: 123maple |
| Phone (drop last four digits) | 415-555-1234 Key: 415555 555-1234-5678 Key: 5551234 |
Matching Equation
The threshold for the first three conditions in the equation is 85; the threshold for the fourth condition is 75.
(First Name AND Last Name AND Email)
OR (First Name AND Last Name AND Billing Street AND (City OR ZIP))
OR (First Name AND Last Name AND Phone )
OR (First Name AND Last Name AND Phone AND (City OR ZIP) AND Mailing Street 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 and 75 | Don’t match (ignores blank fields when Email is included in field grouping) | If the record contains a value for both 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 George and the last name is Michael. The matching rule also evaluates the first name as Michael and the last name as George. |
| Last Name | Last Name | Exact Keyboard Distance Metaphone 3 |
Maximum | 90 and 75 | Don’t match (ignores blank fields when Email is included in field grouping) | If the record contains a value for both 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 George and the last name is Michael. The matching rule also evaluates the first name as Michael and the last name as George. |
| 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 single 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. |
| Billing 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 single 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. Only 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. |
| Billing ZIP/Postal Code | ZIP/Postal Code | Exact | Weighted Average | 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 determine a single score for the field.
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| Billing City | City | Edit Distance Exact |
Maximum | 85 | Don’t match |
