Introduction
Customer Insights - Data helps your organization unlock insights, build deeper understandings of your customers, and power personalized customer experiences by unifying your customer data from all your organizations various transactional, behavioral, and observational data sources into a single 360-degree view of the customer.
Customer profiles are created through unifying data ingested from your organization's different data sources. Data can be ingested from a wide range of data sources through built-in connectors that connect to many different data providers.
Data can be ingested into Customer Insights - Data in the following ways:
Microsoft Power Query: Used when you want to import data such as Microsoft Dataverse, Azure Blobs, OData sources, etc. For more information, see Power Query Connectors.
Azure Synapse Analytics (preview): Used when you want to connect to Azure Synapse Analytics. For more information, see Connect an Azure Synapse data source.
Azure data lake storage - Used when you want to connect to an Azure Data Lake Storage Gen 2 Account. For more information, see Common Data Folder.
Microsoft Dataverse - Used when you want to connect to data sets in the Dataverse data lake. For more information, see Dataverse.
Once your data sources are successfully ingested into Customer Insights - Data, the next step is to create a unified customer profile. This is done through data-unification. The goal of data unification is to separate data sources and unify them into a primary customer dataset providing a more complete view of your customers.
For example, let’s say that you have one system that you use to manage all your customer purchases that are made through an online store, and another separate system that is used when customers make purchases from your retail store. Since you likely have the same customers making purchases from both channels, you want to unify customer data from both channels into a single customer profile. This ensures that you can use the data from both sources in a single spot.
It's important to remember that not all data ingested into Customer Insights - Data represents data that would be used to create a unified customer profile. Some data might represent transactional information such as purchases, emails, support cases, membership renewals and more. While that information is important, it's typically used to represent customer related activities and not to define customer profile data. Customer profile data typically includes data like addresses, phone numbers, ID numbers, profile pics, birth dates, and so on.
Once you've identified the customer data that you want to use in your unified customer profile, you'll need to unify the data. The Customer Insights data unification process includes the following steps:
Source columns - Defines which tables and columns will be combined to create a unified customer profile.
Duplicate records - Defines how to handle any duplicate records in your datasets.
Matching conditions - Defines the rules that will be used help combine your datasets into a unified customer profile.
Unify customer columns - Defines final information such as which items to exclude, column ranking, and other details that could impact the merge.
Throughout the remainder of this module, we'll examine each stage in this process in more detail.