--- schema_version: "1" id: ddf399b747795c77eb891e279ee536f8cd4212b1ecb5558be9868ceb95292541 title: Matching Methods Used in Matching Rules collection: admin version: current locale: en-us portal_url: https://docs.salesforce.com/admin/current/en-us/sales/264-0-0/matching_rules_matching_methods.md canonical_url: https://help.salesforce.com/s/articleView?id=sales.matching_rules_matching_methods.htm&release=264.0.0&type=5 source_site: help.salesforce.com content_type: documentation content_hash: 3cc730a3665843830564dfda48b7a09f9917bca1f7d5e9c64252d6e396d33fee description: The matching method determines how a specific field in a record is compared to the same field in another record. Each matching method is defined by normalization criteria, match key definitions, and matching algorithms. products: - Sales - Sales Enablement release: "264" --- # Matching Methods Used in Matching Rules The matching method determines how a specific field in a record is compared to the same field in another record. Each matching method is defined by normalization criteria, match key definitions, and matching algorithms. ### Required Editions
Available in: Lightning Experience and Salesforce Classic
Available in: Essentials, Professional, Enterprise, Performance, Unlimited, and Developer Editions
The exact matching method looks for strings that exactly match a pattern. If you’re using international data, we recommend using the exact matching method with your matching rules. You can use the exact matching method for almost any field, including custom fields. The fuzzy matching methods look for strings that approximately match a pattern. Some fuzzy matching methods, such as Acronym and Name Variant, identify similarities using hard-coded dictionaries. Because the dictionaries aren’t comprehensive, results can include unexpected or missing matches. Specific fuzzy matching methods are available for commonly used standard fields on accounts, contacts, and leads.
Matching Method Matching Algorithms Scoring Method Threshold Special Handling
Exact Exact      
Fuzzy: First Name

Exact

Initials

Jaro-Winkler

Name Variant

 Maximum 85 If the Middle Name field is used in your matching rule, it’s compared using the Fuzzy: First Name matching method.
Fuzzy: Last Name

Exact

Keyboard Distance

Metaphone 3

 Maximum 90  
Fuzzy: Company Name

Acronym

Exact

Syllable Alignment

 Maximum 70

Removes words such as “Inc” and “Corp” before comparing fields. Also, company names are normalized. For example, “IBM” is normalized to “International Business Machines”.

When generating a match key for a company name with more than two words, the system evaluates only the first two words. As a result, legal designators, such as Corporation or LLC, outside the first two words aren't included in special handling.
Fuzzy: Phone Exact Weighted Average 80

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, these 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 match score of 90. This score is considered a match because it exceeds the threshold of 80.
Fuzzy: City

Edit Distance

Exact

 Maximum 85  
Fuzzy: Street 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, these billing streets are being compared: 123 Market Street, Suite 100, and 123 Market Drive, Suite 300.

Only the street number and street name match, so the field has a match score of 70. This score isn’t considered a match because it falls below the threshold of 80.
Fuzzy: ZIP 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 come up with one score for the field.

  • First five digits (Exact, 90% of field’s match score)
  • Next four digits (Exact, 10% of field’s match score)

For example, these ZIP codes are being compared: 94104-1001 and 94104.

Only the first five digits match, so the field has a match score of 90. This score is considered a match because it exceeds the threshold of 80.
Fuzzy: Title

Acronym

Exact

Kullback-Liebler Distance

 Maximum 50
#### See Also - [_Knowledge Article_: Fuzzy Match on First Name Doesn't Detect the Expected Duplicate](https://help.salesforce.com/s/articleView?id=000389625&type=1&mode=1&language=en_US)