Consume Customer Insights data
Typically, most end users don't access Customer Insights data directly in the Customer Insights - Data application. Instead, they consume it inside the applications they use every day. For example, a marketer might use segments created in Customer Insights - Data in Customer Insights - Journeys. A sales organization might surface profile details in its CRM system to help sellers deliver better customer experiences.
To get to this point, you need to build your Customer Insights - Data environment to support your organizational needs. At a high level, the process involves:
Ingest and unify data
Data can be ingested from a wide range of sources through built-in connectors that connect to many different data providers. This step is the foundation - without data, there's nothing to unify.
Once ingested, you build customer profiles by unifying data from your different sources into a single record. The unification process has four stages:
- Map customer data - Identify which entities and fields represent the customer record, such as a customer number or email address.
- Deduplication rules - Identify duplicate customer records within a table and specify which record to keep.
- Matching rules - Define how datasets are combined into a unified profile by specifying which fields are used during matching.
- Unify - Complete the process and reconcile any conflicts.
Track activities and measures
Activities consolidate customer interactions from across your data sources into a single chronological timeline - purchases, service cases, website visits, and more. Measures define the KPIs that best reflect your business performance and customer health, such as satisfaction scores, revenue targets, or customer lifetime value.
Enrich and predict
Enrichments add supplemental data from Microsoft and partner sources to build a richer profile, such as brand affinities, interests, and financial or demographic details. AI prediction models then let you forecast customer behavior - for example, whether a customer is ready to purchase or at risk of churn. Use out-of-the-box models or bring your own from Azure.
Segment and activate
Segments group customers based on shared demographic, transactional, or behavioral attributes, making it easier to target the right audience at the right time. Once you build your environment, that data - measures, activities, and insights - flows into other applications such as Dynamics 365 apps, Power Apps, LinkedIn Ads, Google Ads, and more.
Data activation
Here's an example of data activation.
Mark works as a greeter in one of Contoso Coffee's retail stores. As customers enter the store, Mark captures their names and phone numbers into a greeter application that Contoso uses. Then, Mark sends the customers to a store representative who can assist them. After the customer's information is captured in the greeter application, supported by data in Customer Insights, Mark provides the store representative with a complete picture of who the customer is.
This customer description includes:
All recent activities across Contoso's different touch points.
The customer's current reward points balance.
How much the customer has spent over their lifetime with Contoso.
Product recommendations based on past buying patterns.
Because the store representative has this context before the conversation starts, the interaction feels personal rather than transactional. The customer doesn't need to repeat their history, and the representative can focus on delivering value - whether that's recommending a relevant product, acknowledging loyalty status, or proactively resolving a potential issue. That's the outcome Customer Insights - Data is designed to enable: the right information, in the right hands, at the right moment.