A customer buys from your company, signs up for emails, downloads a guide, visits your website, and later contacts support. How much of that history can the employee speaking with them actually see? In many organizations, Sales sees one piece of the relationship, Customer Service sees another, Marketing owns engagement information, and website behavior sits somewhere else entirely. Dynamics 365 Customer Insights is designed to bring those pieces closer together so organizations can understand the customer more completely and communicate based on that context. In this episode of Microsoft Knowledge Nuggets on M365 FM, we explain the two major parts of Dynamics 365 Customer Insights—Customer Insights - Data and Customer Insights - Journeys—and follow customer information from disconnected records through unified profiles, segments, journeys, triggers, personalization, consent, analytics, and human follow-up.
WHY CUSTOMER DATA BECOMES FRAGMENTED
Customers do not think about your organization as separate applications and departments. They simply interact with your business. They purchase something, request information, visit your website, open an email, speak with Sales, or contact Support. Internally, however, every interaction can land somewhere different. Dynamics 365 Sales may contain the opportunity. Customer Service may contain the support case. An ecommerce platform records purchases. A website records form submissions and browsing behavior, while marketing systems track emails and other interactions. The result is one customer with multiple disconnected versions of their story. Customer Insights is intended to make that customer story easier to understand and use.
WHAT DYNAMICS 365 CUSTOMER INSIGHTS ACTUALLY IS
Dynamics 365 Customer Insights helps organizations understand customers and use that understanding to provide more relevant communication. That broad definition makes more sense when Customer Insights is separated into its two major building blocks: Customer Insights - Data and Customer Insights - Journeys. Customer Insights - Data brings information together and helps organizations understand the customer. Customer Insights - Journeys uses customer information to plan and deliver communications based on who somebody is and what they do. A simple way to remember the distinction is: Data helps you see the customer. Journeys helps you respond to the customer.
WHY THE CUSTOMER INSIGHTS NAME CAN BE CONFUSING
Microsoft's naming changes are one reason Customer Insights can initially seem more complicated than it is. Before September 2023, Dynamics 365 Marketing existed as its own product. Microsoft renamed that product Customer Insights - Journeys, while the existing Customer Insights product became Customer Insights - Data. Both capabilities now sit underneath the broader Dynamics 365 Customer Insights name. This means somebody saying, “We use Customer Insights,” could mean Data, Journeys, or both. A useful question in any Customer Insights conversation is therefore simply: Do you mean Data or Journeys?
CUSTOMER INSIGHTS DOES NOT REPLACE SALES OR CUSTOMER SERVICE
Dynamics 365 Customer Insights should not be confused with Dynamics 365 Sales or Dynamics 365 Customer Service. Dynamics 365 Sales remains where sellers manage leads, accounts, opportunities, calls, follow-ups, and the sales process. Dynamics 365 Customer Service remains where service teams manage customer cases, knowledge, and support activities. Customer Insights adds customer understanding and communication around those existing processes. A salesperson can gain additional context about customer behavior. A service employee can better understand previous interactions. Marketing can communicate using information the organization already possesses. The goal is connection rather than replacing the systems where employees perform their actual work.
CUSTOMER INSIGHTS - DATA
Customer Insights - Data can be understood as a shared customer filing system. A customer might appear as a contact in Dynamics 365 Sales, have transactions in another purchasing platform, submit forms through a website, and have previous support interactions recorded elsewhere. Every source knows something useful about that person, but no individual source necessarily contains the complete relationship. Customer Insights - Data brings relevant information from those different sources together to create a more complete customer picture.
BRINGING CUSTOMER DATA TOGETHER
Customer information can originate from Dynamics 365 applications, websites, loyalty platforms, purchasing systems, customer service environments, and other business systems. The objective is not to collect every available field simply because it exists. Organizations should bring together the information that helps them understand customers and make better decisions. Imagine a home equipment company. Sales knows Alex requested a quotation last month. The ecommerce system knows Alex purchased equipment two years ago. Customer Service knows Alex recently requested assistance with a repair. The website knows Alex has started researching an upgrade. Separately, these are four records. Together, they begin to describe a customer relationship.
FROM RAW RECORDS TO A UNIFIED CUSTOMER PROFILE
Customer Insights - Data can help identify records from different systems that refer to the same customer. Those source records may contain slightly different names, customer identifiers, addresses, or email addresses. The objective is to match appropriate records and create a unified customer profile. Instead of employees seeing several disconnected versions of Alex, the organization can create a more complete profile containing relevant information from across the relationship. That unified profile becomes the foundation for better segmentation, analysis, personalization, and communication.
MATCHING RULES MATTER
Customer matching cannot simply assume that similar-looking records represent the same person. Two customers may share a surname. An old email address may now belong to somebody else. Addresses can change, and customer records can contain incomplete information. Customer Insights - Data uses matching rules configured by the organization to determine how records should be connected. Good matching logic helps reduce duplicates without incorrectly combining different people into one customer profile.
BUILDING A COMPLETE CUSTOMER STORY
Once records are appropriately unified, the resulting customer profile becomes considerably more useful. Teams can potentially see purchase history, service history, marketing interactions, preferences, interests, website behavior, and other relevant information brought together around the customer. Instead of treating somebody as an email address inside a marketing list, the business can understand them as a person with an existing relationship. This changes the questions employees can ask. Has this customer purchased before? Did they recently contact Support? Are they showing interest in another product? Did they engage with previous communication?
SEGMENTS: DYNAMIC GROUPS OF CUSTOMERS
Customer Insights - Data allows organizations to create segments. A segment is simply a group of customers who satisfy particular conditions. Instead of exporting a spreadsheet, manually filtering rows, saving another list, and repeating the process later, the organization defines the conditions that determine membership. For example, a segment could contain customers who purchased a particular product, live in a certain region, and visited a related webpage during the previous month. As customer information changes, membership can change as well. Customers who satisfy the conditions enter the segment, while customers who no longer satisfy them leave.
BEHAVIOR-BASED SEGMENTATION
Segments do not need to depend exclusively on static profile information. Organizations can also create audiences based on customer behavior. Perhaps the business wants customers who clicked a product link but have not purchased, or customers who opened a support case during the previous thirty days. This allows organizations to focus on what customers actually did rather than simply who they appear to be based on demographic or profile information.
PREDICTIVE CUSTOMER INSIGHTS
Customer Insights can also provide predictive insights. Customer lifetime value can estimate the potential value a customer may generate over the relationship with the business. Churn likelihood can estimate whether a customer may stop purchasing, stop using a service, or otherwise disengage. These predictions are not guarantees. They are estimates derived from the available information and historical patterns. If the organization's underlying customer data is incomplete or poor quality, the resulting predictions will also be limited. Used appropriately, however, predictive insights can help teams identify customers or situations that deserve additional attention.
COPILOT AND CUSTOMER DATA
Copilot can help employees work with customer information using natural language. Instead of beginning with complicated filtering logic, an employee could describe the audience they are trying to identify—for example, customers with a strong purchasing history who have not engaged recently. Copilot can help translate that request into something the employee can inspect and refine. The important point is that Copilot does not remove the need for reliable customer data. AI becomes more useful when the information underneath it is accurate, connected, and meaningful.
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