Overview

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Discover how to transform scattered customer data into actionable intelligence using Customer Insights - Data and Customer Insights - Journeys. You'll learn to ingest data from CRM systems, web analytics platforms, marketing tools, and point-of-sale sources, then unify it into comprehensive customer profiles that provide a complete view of customer behavior and engagement. Build high-value audience segments, design both rules-based and propensity-driven segmentation matrices, and use Segment Discovery to identify the behavioral and demographic drivers behind customer lifetime value. You’ll also explore how customer insights can improve personalization, campaign targeting, and engagement strategies across multiple channels. By the end of the course, you'll evaluate segmentation effectiveness using Power BI dashboards and reporting tools to measure open rates, click-through rates, conversions, customer engagement, and overall campaign uplift for data-driven decision-making.

Syllabus

Ingest Data: Configure Data Connectors

Learn to connect external data sources to Customer Insights - Data, configure refresh schedules, and verify successful data ingestion—the essential first step before unification and segmentation.

Ingest Data: Map the Customer Insights Data Model

Understand how Customer Insights data organizes customer information into profiles, interactions, and measures, and document your data model so your team can build on a shared foundation.

Unify Data: Configure Identity Resolution

Learn to configure the Unify process of Customer Insights - Data to match and merge duplicate customer records, creating the single customer view that powers accurate segmentation and personalization. In practice, match rules are refined iteratively based on results; you will learn how to evaluate and adjust over time.

Unify Data: Establish Data Governance

Configure consent tracking and data quality rules that ensure your segments only include valid, permission-based contacts—protecting your brand reputation and maintaining regulatory compliance.

Segment: Build High-Value Audience Segments

Learn to define and publish audience segments in Customer Insights - Data using unified profile attributes, calculated measures, and behavioral criteria—the building blocks of targeted marketing campaigns.

Segment: Analyze LTV Drivers with Segment Discovery

Use Customer Insights' Segment Discovery feature to understand what differentiates your high-value customers, then communicate those insights to stakeholders in a format that drives strategic decisions.

Refine Segments: Design a Segmentation Matrix

Learn to build a two-dimensional segmentation matrix that combines engagement scores with propensity predictions, enabling differentiated treatment strategies that maximize conversion while respecting contact preferences. This approach directly addresses common challenges such as over‑messaging low‑intent contacts and missing opportunities with high‑intent but low‑engagement audiences.

Refine Segments: Evaluate Effectiveness in Power BI

Pull email metrics into Power BI, analyze segment performance against baseline, identify underperforming segments, and recommend optimization or consolidation to stakeholders. This measurement loop is iterative—ongoing analysis informs continuous segment refinement, not just one-time reporting. Each measurement cycle informs the next segmentation update, ensuring campaigns evolve with audience behavior.

Project Module: Customer Segmentation Analysis and Strategic Recommendations

Apply your customer intelligence skills to a comprehensive segmentation analysis project. You'll document your data architecture, build a strategic segmentation framework, analyze segment performance, and present recommendations to leadership in a portfolio-ready deliverable. This is a synthesis and storytelling exercise: you're assembling and presenting prior work, not re-executing tool configurations. If you’re missing outputs from earlier modules, you may use placeholder or summarized data as long as you provide a brief justification explaining assumptions and data limitations. Who this is for: Designed for marketing analysts, CRM specialists, lifecycle marketers, and marketing managers who need to demonstrate end‑to‑end customer intelligence capabilities.