The matching depends on the value of your attributes. If you want to ingest customer data into the CDP and you don't have a strong identifier like CRM ID, you can combine between multiple attributes in order to get a higher probability of customer data matching. For example, you can combine between firstName, lastName, and address in order to make the matching of your customer data stronger.
Customer Unified and Contextual Profiles have separate sets of matching rules. Usually, Unified Profiles will rely on more probabilistic, or marketing-based rules (such as the same zip code or home address), while Contextual Profiles rely on stronger identifiers and deterministic rules (such as matching Master Data ID, CRM ID, and CIAM ID).
Multiple matching rules can be defined in SAP Customer Data Platform. They are applied in the order by which they're defined. That means if no match is found using the first matching rule, for example, using Master Data ID, then a match will be attempted using the next matching rule.
The CDP Identity Resolution – Bringing your customer data together
Merge rules are configured to determine how to handle event data coming in from different sources. They decide which application has a greater level of trust, meaning it will override existing data coming from less trusted sources.
Merge rules are configured when defining the customer schema, and are used in the following scenarios:
First, when more than one value can be saved for an attribute. This is defined per attribute.
Second, when overriding existing customer data, based on the quality of the incoming data vs. the quality of existing data. This is defined per application.
And third, when deciding what to do in case a data conflict occurs for an attribute that is an application identifier. This is defined per attribute.
Matching and merge rules
In this video, you ‘ll learn how to create a matching rule and create an attribute merge rule. You’ll also see matching and merge rules in action.