3 - Matchmaker Implementation Considerations

Plan Your Implementation

As you consider implementing Matchmaker, please review this list of pointers that will help ensure a successful trial and deployment.

Test in a Sandbox

As with all new features and functions, it is strongly recommended that you install and test Matchmaker in a sandbox before you deploy it to a Production org. Matchmaker delivers features that touch standard Salesforce fields and can have impact to the user experience while working leads and contacts. You should validate that you are observing your desired business processes particularly as they relate to lead assignment and conversion. We recommend that after you have read and understood how Matchmaker Assign and Convert functionality work, you map out the desired process and outputs with your team, implement and then test with multiple users and roles.

Existing Test Data in Production

Evaluate the data in your production org to recognize how existing data may impact Matchmaker.

Test Accounts and Contacts

There is a very good chance that you have test accounts and contacts in your org that were created to validate features or train users. Consider excluding email domains associated with test accounts so that Matchmaker does not evaluate this test data. For example in Full Circle's production org, we exclude the email domains "fullcircleinsights.com" and "fullcirclecrm.com" from Matchmaker's calculation. You can add to the list of domains that Matchmaker omits from evaluation under the Email Domain Calculation settings.

Test Account Websites

You may have many test accounts that share a dummy website, such as http://none.com, http://unknown.com or http://example.com. We have observed some customer orgs that have over a hundred such account records. If you are unable to delete or cleanse this data, it is recommended that you create duplicate rules to ignore these websites. In addition to cluttering up the user experience, Salesforce Duplicate Management may even prevent you from enabling the default matching rule upon initial implementation if there are too many similar accounts. This topic is covered here.

Leads that Should Never be Matched

Some companies routinely import leads that should never be matched to existing contacts and accounts. There can be business process reasons for this. During your planning session with colleagues, once you identify this category of leads, set up an exclusion rule under Lead Matching settings to disallow matching.

Lead Company Name and Account Name

Do your company lead import lists always have a company name or is that field sometimes blank? Similarly, do all accounts have a name, or is that field sometimes blank?

Matchmaker's default matching rule and criteria work best when leads and accounts have known company names. If there is a significant portion of the account data where the account name is unknown, additional duplicate and/or matching rules may be required for optimal Matchmaker functionality. Full Circle can work with you to evaluate your data and guide you on how to configure duplicate or matching rules. For example, it may be necessary to create a duplicate rule that runs prior to the packaged duplicate rule that ignores the company name on the lead if it contains certain values.

We recommend that you start by evaluating your company data to understand where pitfalls exist. Start by running reports on lead and account data to see where data are missing from lead company and account name fields. Many organizations have leads with company names like "n/a", "not provided" or "unknown". You should understand the prevalence of this before you deploy Matchmaker.

Implement Match Before You Enable Assign and Convert

Before you enable Assign and Convert, we recommend that you start by setting up Match criteria first and allow the application to run an initial match batch before you enable the other two features. When you allow the application to Match, only Matchmaker application fields are set on the lead. It is much easier to make corrections to match settings if the outcomes are not those desired. Once you enable Assign and Convert, it becomes more difficult to diagnose undesired results. Any mismatching in Matchmaker can cause assignment and conversion problems, which are harder to correct so it's important to ensure that you have matching set up correctly first.

Test with Valid Data

Once you have lead matching settings configured and the feature enabled, it is important to test lead matching with good, valid data. Create some test accounts with real company names, i.e. Full Circle Insights, Inc. and add some contacts with the corresponding email domain, i.e. @fullcircleinsights.com. Import or create leads where the company name is representative of what you might bring back from a tradeshow, i.e. Full Circle. Matchmaker has the ability to match solely on lead Company Name, it is better to test using records that resemble the typical lead/account information you would be importing to your org.

Find the Right Balance

The Salesforce Duplicate Management system that Matchmaker leverages is very good, but not perfect. Like any statistical or data problem, there is an underlying balance between accuracy and volume. More stringent logic will result in more accurate data but also fewer matches. Fewer logical constraints will result in more matches, but more false positives.

Full Circle Insights suggests testing the Matching Rule, Duplicate Rule and Matchmaker configurations in a sandbox prior to deploying to production, with the goal of finding the right balance between high match rate and high accuracy.

Prevent Recursion & CPU Timeout Errors

Matchmaker makes various updates to the Lead and Account records in your org. If you have processes or Apex triggers that execute after leads or accounts are updated, this could potentially cause an infitine loop of re-entrancy between Matchmaker triggers and your components, which can result in a CPU timeout error. To avoid this scenario, consider modifying your processes and/or triggers so that they don't execute if Matchmaker is making updates to these objects. When updating leads/accounts, Matchmaker increments the value in a field called FCMM__LAM_Admin_Update_Counter__c. If the value in that field has changed then Matchmaker is updating the record and your process/Apex code can exit quickly. Below are some code examples.

Process/workflow formula:

You can use the following formula in your criteria so that your process/workflow/validation rules only execute when Matchmaker isn't updating a record:

NOT(ISCHANGED(FCMM__LAM_Admin_Update_Counter__c))

Apex trigger context:

The following Apex trigger code exits quickly if Matchmaker is making the update to the lead object. The same approach can be used on the account object.

trigger MyLeadTrigger on Lead (after update) {
    for(Lead newLead : Trigger.new){
        Lead oldLead = Trigger.oldMap.get(newLead.Id);
        if(oldLead.FCMM__LAM_Admin_Update_Counter__c != newLead.FCMM__LAM_Admin_Update_Counter__c){
            // exit quickly because Matchmaker is performing update
            return;
        }
    }
}

Do you need assistance or have questions? Contact our Customer Success team by logging a case in the Full Circle Customer Success Community.