Understand Identity Resolution Rulesets
Learning Objectives
After completing this unit, you’ll be able to:
- Define rulesets.
- Create match rules.
- Use reconciliation rules.
Identity Resolution Rulesets
Now that you have reviewed your data and understand the importance of data mapping, let’s discuss how you match data across systems. Rulesets allow you to configure match rules and reconciliation rules about a specific object, such as individual. The system follows these rules to link together multiple sources of data into a unified profile.
Regardless of what objects you use in your account, it’s a good idea to carefully review the data requirements to make sure your source data complies with the mapping requirements. It’s easier to fix a data stream before ingestion than to update it after ingestion. Let’s first review your match rule options so you can make an informed decision on what can work for your account.
Match Rules
Match rules are customizable based on your business needs.
To create a match rule, you first need to select an object (1) from either: individual, contact points (email, app, phone, and address), device, or party identification. Then select your field (2). Select the attributes available based on the object selected. Next, depending on the object and the field type selected, you have the option of selecting match methods (3). Let’s review those options for match methods.
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Exact: Matching based on an exact match. No typos or alternative formats.
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Fuzzy: Matching based on a similar match. Typos and slightly different spelling are OK. This is only available for first name.
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Normalized: Matching based on the same exact info, regardless of formatting. This is available for email, phone, and address.
Once selected you can add additional criteria to your match rule. You can create a combination of match rules based on standard and custom attributes to meet your business needs. Just be sure to give your match rule a descriptive name such as Fuzzy First Name and Custom Field 2. Just know that the more rules you configure, the more mapping requirements you need to follow.
Reconciliation Rules
While match rules are used to link together data into a unified customer profile, reconciliation rules determine the logic for data selection. For example, if the same email address is available from two data sources, a reconciliation rule helps the unified profile know which one to display. Let’s review the options for reconciliation rules.
Rule |
Description |
|---|---|
|
Last Updated
|
This rule specifies that the most recently updated value must be selected for inclusion in the unified profile. It’s worth considering what data gets updated most regularly—would it be customer service data or perhaps Marketing Cloud Engagement preference data? |
|
Most Frequent
|
This rule specifies that the most frequently occurring value must be selected for inclusion in the unified profile. |
|
Source Sequence
|
This rule allows you to sort your data sources in order of most to least preferred for inclusion. Basically it allows you to select based on your confidence in the data source. As an example, you can specify that the system use Commerce Cloud data first and S3 data last. |
It’s important to note that you can select reconciliation rules at the object level and field level.
In this example, loyalty balance and loyalty tier are using the Source Sequence rule (2) instead of the default Most Frequent rule (1).
What happens with data you don’t select for the unified profile? Let’s say you have a profile that has two email addresses (like Rachel’s info in Commerce Cloud). Regardless of which version is selected to be displayed, all unique emails are still stored for each customer. So you don’t have to worry about deleting important data.
Next Up: A Use Case
In the next unit, we review a use case and share best practices for using identity resolution rulesets.
Resources
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Salesforce Help: Data Modeling Requirements for Identity Resolution
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Salesforce Help: Party Data Model