Microsoft’s Brand New CDP – Customer Insights

Know your customers like never before with a real-time customer data platform. Discover the new, powerful engagement insights from Microsoft that delivers  the most comprehensive view of your customers.

CDP Workflow
CDP Workflow

Holistic view of Customers : To understand Customers or Prospects by Unifying and Enriching data in complete, centrally accessible profiles that deliver more personalized experiences. Create comprehensive view of each customer across channels—including campaign responses, in-store and online visits and purchases, loyalty redemptions, customer service encounters, social interactions, or IoT signals.

Customer Data Platform. Microsoft Customer Insights

Data from Multiple Sources equals Comprehensive Insights : Access demographic, transactional, or behavioral data in real time from a variety of sources. This data helps ensure customer profiles are up to date and can generate relevant insights.
Simplify the process of pulling in data with pre-built connectors available for myriad first- and third-party data sources, and organize customer data to derive powerful insights.

Unify Data for More Actionable Insights:  The Data Unification Process aims to bring together data that is locked in disparate systems and applications to create a master customer data set for a more complete view of your customers.

The data unification process entails three steps: Map, Match, and Merge.

  1. In the first stage, entities are mapped to a Common Data Model (CDM) schema.In Customer Insights, entities are data sets.
    • Many of the product processes—including data unification, relationships and segmentation, and measures and activities—are organized around the entities you choose.
  2. Once the entities have been identified, select the attributes that you want to combine and reconcile in the Match and Merge phases.
    • The Match phase allows you to specify how to combine your data sets into a unified customer profile using deterministic and probabilistic matching. One can learn to evaluate the quality of match pairs and define rules to improve.
  3. The Merge phase is the last step in the data unification process.
    • Conflicting data, such as customer names or phone numbers, might appear in different formats in data sets for the same record. The primary purpose of this step is to reconcile conflicting data

Enrich Data to Extend Solutions: Microsoft Graph provides proprietary audience intelligence such as demographics and interests, market trends, and product and service usage data. Bring in third-party sources to further enrich customer profiles and find new audiences and segments.

Generate Insights for an Improved Customer Experience: AI proactively recommends segments and generates predictive insights that drive optimized customer experiences and processes.

  • Discover new audience segments with AI-driven recommendations or define custom segments.
  • Segments group your customers into Cohorts based on Demographic, Transactional, or Behavioral Attributes.
  • Define sophisticated filters around the customer profile entity and its graph of related entities. Each segment outputs customer records that you can export and act on.
  • Measures represent key performance indicators (KPIs) that reflect the performance and health of specific business areas. 
  • Create an intuitive experience for building different types of measures by using a query builder that doesn’t require you to code or validate measures manually.
    • Export segments to sales and marketing applications to generate more targeted actions, such as promotional campaigns, sales activities, or customer support.

Activate Insights to Drive Better Solutions : Now that we have seen the power of data configuration and segmentation, let’s look at how this comes to life in day-to-day business operations. The Export destinations page shows you all the locations you’ve set up to export data to. You can add new destinations to personalize marketing strategies and safely connect with brands across social, digital, and TV ecosystems.

  • Leverage Timeline Control and Demographic Control to unlock rich insights on selected customers, including their location, age, and latest activities.
  • Connect Customer data with Microsoft Power BI to customize dashboards and reports.
  • Trigger workflows in response to customer signals by using Power Automate.
  • Build Custom Apps with Customer Insights embedded with Microsoft Power Apps.
  • With mobile apps that provide a 360-degree view of their customers, this empowers sales representatives to provide more personalized service.

Advanced Analytics for Deeper Insights : Leverage Azure Machine Learning (AML) to customize and train models for predictive insights that can be directly imported into the customer record. The predictive web service can be scheduled at predetermined intervals to automatically refresh and update the prediction scores.

Derive deeper insights with Azure Synapse Analytics, which combines customer data and enterprise data to improve data completeness, run high-speed analytical processing, and build custom machine-learning models.

Data Security, & Compliance to help one stay Current : Built on a secure and hyper-scalable Azure platform, advanced features help ensure that your organization is secure and compliant.

  • You can support data privacy and General Data Protection Regulation (GDPR) compliance with corporation-ready security and built-in governance tools, all while retaining full ownership of your data.
  • Customer Insights is available for government and public customers with higher compliance needs, allowing them to better understand and interact with citizens, empower employees, and transform cities at scale.

Deepak Nair

Deepak is a Digital, & Analytics SME with about 15+ years of experience in the fields of New Media, Analytics, Machine Learning, Data Engineering, & AI

Recommended Articles