Fuzzy logic is a way to model logical reasoning where the truth of a statement is not a binary true or false, but rather it is with the degree of truth that ranges from 0 (false) to 1 (true).
When there is uncertainty in data and the search criteria, the fuzzy logic option helps to filter the available best match account, as it can incorporate all intermediate values between True and False.
Note
Refer to the article What are Fuzzy Matches in Salesforce Deduplication? for a detailed explanation an examples on fuzzy logic in Salesforce.
Duplicate rules for BMA
Currently all the duplicate accounts coming from all the active duplicate rule are considered. You can pass only particular duplicate rules name to filter the duplicate records for BMA.
If string value is NULL, it will pick the matched account from all the duplicate rules.
If string value is comma separated values of Duplicate Rule API name, then only matched account from those Duplicate Rules are picked.
If there are any Custom Duplicate Rules Enabled and if the following mapping rules to lead and account gives a set of accounts. Those accounts are also considered for calculation of BMA.
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. More than one rule can be added or removed, as needed.
For accurate matches, the new or edited record must include a value in the Account Name field and either the City or the ZIP Code field.
(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).
Triggering the BMA function: After setting up the rules, it is essential to trigger the process either by enabling the flags in Fullcast setting or by calling BMA in Flow.
Matching rules and duplicate rules
Matching Rules
A matching rule applies criteria to determine how closely a field on a new or edited record matches the same field on an existing record. Standard matching rules include predefined criteria. When you create a custom matching rule, you define the criteria.
Duplicate Rules
A duplicate rule defines what happens when a user views a record with duplicates or starts creating a duplicate record. Salesforce provides standard duplicate rules for business and person accounts, contacts, and leads. Customized duplicate rules can also be created.
Difference between matching rules and duplicate rules
Matching Rules will identify what field and how to match. For example, Email Field, Exact Match or Account Name, Fuzzy Match. They don’t do anything on their own.
Duplicate Rules will use those Matching Rules to control when and where to find duplicates. For example, Use Account Name, Fuzzy Match to find duplicates on the Account object upon creation or Use Email, Exact Match, to find duplicates on Leads and Contacts, upon create and edit.
The following display different case studies of BMA with the fuzzy logic results for the account name Athena Health Limited.
BMA functionality with fuzzy logic
BMA decides which fields and which appropriate criteria to compare the leads and accounts to fetch a BMA. Use fuzzy logic criteria when you are unsure about the data fields.
Create a Fullcast policy rule in the Salesforce environment.
Enable the trigger flags or set up a flow to call into the BMA functionality.
Note
BMA displays in the BMA field available in Lead details when created or updated.
configure standard duplicate rules and matching rules in Salesforce
configure standard duplicate rules and matching rules in Salesforce
Review this article to learn the step-by-step process of how Best Match Account Functionality works in Fullcast.
Review this Salesforce article, Standard Account Matching rule, to get an understanding of how the matching keys are formulated in Salesforce.
Rules for standard and fuzzy matching
All the company name suffixes like Incorporation, Corporation, and Ltd., are all normalized before comparing the name fields. So Fedex Inc. and Fedex are considered the same.
Acronym company names are also recognized when there is a website match. IBM and International Business Machines can be identified as the best match.
Close company name match is also not recognized as the best match with public email domains like gmail or hotmail.com
To some extent, fuzzy logic can recognize parent and subsidiary companies. For example, Instagram and Facebook will be recognized as the best match.
Note
Fullcast gives the flexibility of ignoring BMA while routing and also Fullcast version 2.166 allows considering only certain customized duplicate records which makes filtering records easier.
Exact match
When the names match exactly, without even considering the other data fields, Fullcast will fetch BMA.
Mismatched fields
When the names do not match exactly but do to some extent, there is a close match between the names, and there are no other supporting data fields that match, BMA is not retrieved.
When the names are entirely different, but when the website matches, BMA is not retrieved.
Match with fuzzy logic
When the names don't match exactly but the websites, phone numbers, or addresses match exactly, then we retrieve BMA through fuzzy logic. With Fuzzy logic, when there is no exact match with the names but a close match between the names, one more data field match is considered important to retrieve BMA. When there is a close match between the names, the next criteria is considered. Following the name, the Website field match is considered the strongest field to fetch BMA as in most leads the phone number and address are not provided.
