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Standard Account Matching Rule
The standard account matching rule identifies duplicate accounts using match keys, a matching equation, and matching criteria. It’s 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.
| Match Key Notation | Match Key Value Examples |
|---|---|
| Company (2,6) City (_, 6) | Account: Orange Sporting Company = orangesporti City: San Francisco = sanfra Key: orangesportisanfra |
| Company (2,6) ZIP (1,3) | Account Name: salesforce.com = salesf ZIP: 94105-5188 = 941 Key: salesf941 |
| Website City (_,6) | Website: https://www.salesforce.com = salesforce.com City: San Francisco = sanfra Key: salesforce.comsanfra |
| Website ZIP (1,3) | Website: https://www.salesforce.com = salesforce.com ZIP: 94105-5188 = 941 Key: salesforce.com941 |
Matching Equation
(Account Name AND Billing Street)
OR (Account Name AND City AND State)
OR (Account Name AND ZIP)
OR (Account Name AND Phone)
OR (Website AND Phone)
OR (Website AND Billing Street)
Matching Criteria
| Field | Matching Algorithms | Scoring Method | Threshold | Blank Fields | Special Handling |
|---|---|---|---|---|---|
| Account Name | Acronym Edit Distance Exact |
Maximum | 70 | Don’t match | Removes words such as “Inc” and “Corp” before comparing fields. Company names are normalized. |
| 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 come up with one score for the field. This process works best with North American data.
For example, these two phone numbers are being compared: 1-415-555-1234 and 1-415-555-5678. All sections match exactly, except the last four digits, so the field has a score of 90, which is considered a match because it exceeds the threshold of 80. |
| Billing 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 come up with one score for the field. This process works best with North American data.
For example, 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. The field isn’t considered a match because the score is below the threshold of 80. |
| ZIP | 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 come up with one score for the field.
For example, these two ZIP codes are being compared: 94104-1001 and 94104. Because only the first five digits match, the field has a match score of 90. The field is considered a match because the score exceeds the threshold of 80. |
| City | Edit Distance Exact |
Maximum | 85 | Don’t match | |
| Website | Exact | Maximum | 100 | Don’t match | The prefix “https://” is appended to the website domain. For example, the field value www.salesforce.com becomes https://www.salesforce.com for matching purposes. Matching for an account record that has a website without the “https://” prefix identifies the record as a duplicate. |

