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Customer data literacy for product managers
10 articles from segmentation basics to operational analytics. A product manager data guide for making better decisions with customer data from every tool.
Step 1: Fundamentals
What event tracking captures and why PMs need it
Event tracking is how product usage becomes measurable data. Understand what gets tracked and where it lives so you can request the right data for feature decisions.
Customer segmentation types and when each matters
Segmentation drives targeting, onboarding flows, and pricing experiments. Know the five types so you can build segments from data your tools already have.
Why real-time data changes product decisions
Stale data means stale insights. Understand how real-time sync keeps your analytics and CRM current so you can act on what users did today, not last week.
Step 2: Building Skills
Behavioral segmentation examples for product teams
Demographics tell you who users are. Behavior tells you what they do. Learn how to segment by purchase patterns, feature usage, and engagement without building ML models.
User segmentation for product-led growth
PLG depends on identifying product-qualified leads from usage data. This article shows how to flag upgrade-ready users and churn risks from your product database.
Analyzing customer data without a data team
Customer analytics reveals which features drive retention and which users expand. Learn how to build reports from synced tool data instead of waiting for analyst headcount.
Step 3: Advanced Strategy
Building a unified customer view for product decisions
Product decisions improve when you see the full customer picture: billing status, support history, and usage in one place. Learn how to build a customer 360 without a warehouse.
Closing the feedback loop with operational analytics
Dashboards show what happened. Operational analytics pushes data into the tools where your team acts on it. Learn how to get product data into CRM and support without engineering tickets.
How data silos block product teams
When analytics, CRM, and billing hold different versions of customer data, every cross-functional decision starts with a reconciliation project. Understand the architecture that prevents silos.
Ensuring data quality across product tools
Bad data quality means bad product decisions. Learn the five dimensions of data quality and how automated sync keeps your tools consistent without manual audits.