Previously (Part 1), we learned about how we could ingest the data from various sources with the help of different Dynamics Power Query Connectors.
Now, let’s talk about how we could use this data to perform unification in Customer Insights and build a unique customer profile.
Customer Insights would require data from at least two data sources to perform the unification. So we’ll need to have the following:
- Dynamics 365 Customer Insight Instance;
- At least two data sources (we’ll use Dynamics 365 CE for Contact entity and Online Customers from Azure Blob Storage)
Perform Data Unifications:
To start the unification, we’ll have to ensure we have data loaded and entities are connected, as we did in part-1.
The unification process will require three steps:
When we go to the map, we’ll have to first select the entities that we like to unify.
Step 1: Log in to CI instance and Navigate to Menu –> Data and click on Unify –> Select Entities.
Step 2: Select the entities and click Apply. You may also select specific fields if required.
Step 3: Once we have the entities selected, we’ll tell the system how to interpret or map the semantic meaning and type of attributes by using common definitions.
We also need to identify the primary key for each entity.
Notice that Customer Insights is smartly recommending the attribute types. We can use them as defaults or override by changing the types.
We’ll leave them to default, click Save.
Match rules will tell the system how to unify the data from two different sources. Here we’ll set the rules about the way matching should be done between the entities.
Step 4: Click on Match under Unify and click on Set Order.
The first entity is called the primary entity, we’ll pick the most complete source or highest quality data source as our primary entity.
Let’s pick D365 CE as the primary source and include all records (even if no match with other entities) and Online sales to be the 2nd entity.
Once selected, click Done.
Step 5: Now, click the new rule button to define the criteria for matching.
Step 6: Build a rule to check the record using the Email field. Select the Email address field for both entities, and precision to be an exact match.
Note that I have selected 2 normalization options, to ensure that there are no whitespaces and match the data using the lower case to give me higher matches.
We can add more match conditions if required.
Click on Done –> Save –> Run.
Once the run is complete, we’ll be able to see total matched records, total unique customers and percentage of record matches.
The system is telling us that it’s able to find 5,154 unique records but could match only 15 records between two sources. This is because we told the system to use everything from CE which has 5,154 records and online customer data quality is not very good hence match % is very low.
So, the final step in the unification process is to Merge.
Step 7: Click on the Merge tab under the unify menu option.
The merge process will combine attributes from all matched source entities but add precedence logic to determine which attribute value to display on the merged profile.
For instance, we can choose to display full name from either of the sources on the merged customer profile. In this case, D365 CE is ranked as 1, which means that CE full name will be used but if the CE full name is blank then full name will be taken from another source.
Let’s Save and Run the merge configuration.
Setup the Search & filter Index
Now that we have completed the unification process, there is one final step before the unified profiles are to set up the search and filter index. This will enable quick search and filtering of the unified profiles based on the defined attributes.
Click on Customers menu and click ‘Search & filter Index’.
Add or remove fields from the list and click on save and Run.
That’s it, we now have the unified customer profiles created from two different sources.
Hope you find this post helpful. Please drop your questions or suggestions in the comment box below. Thank you for reading.