Product Analytics: Data-Driven Growth and Retention

Learn from real examples, Workbook and free Ebook on Product Data Analysis included

What you'll learn
- Understand core product analytics concepts such as funnels, retention, churn, and LTV, and how they relate to user behavior and product success.
- Learn event-based tracking and segmentation techniques to uncover user patterns, segment behaviors, and optimize product decisions.
- Interpret key metrics to identify product strengths, detect drop-offs, and improve retention through data-driven experimentation.
- Translate user behavior into insights that support prioritization, roadmap planning, and outcome-focused decision making.

Requirements
- Some familiarity with product management concepts is helpful, but no technical or coding experience is required.

Description
Are you a product manager, growth lead, marketing manager, or founder looking to make smarter product decisions using data without relying on a data science team?

In this hands-on course, you’ll learn how totrack, interpret, and act on product analyticsto improve user experience, retention, and revenue. Whether you're launching a new product or optimizing an existing one, this course gives you the frameworks, metrics, and thinking tools you need to turn user behavior into actionable insights.

We’ll cover essential concepts likefunnels, retention, churn, LTV, and segmentation, and guide you through practical exercises using real-world data patterns. You’ll learn how to define what to track, make sense of messy spreadsheets, and prioritize decisions that move your product forward.

No coding or advanced math required, just a curiosity for product data and a desire to build better experiences.

By the end of this course, you’ll be able to:

Understand and apply core product analytics concepts

Set up event-based tracking and meaningful metrics

Identify growth opportunities through retention and funnel analysis

Segment users and translate data into product strategy

The course includes:

Part 1: Product Analytics Foundations

Unit 1:What is Product Analytics?

Why do Product Analytics Matter?

Clarity and purpose

Uncovers new insights

Helps you figure out how to not let your product sink

What are the “right” data points to measure?

The “low” performing game

How can metric results influence the product strategy?

Bias in interpretation of data

Unit 2:

Metrics vs Mission, Why they matter and North Star Thinking

Unit 3:Measuring the Entire Journey

Going through the Funnel

Measuring the journey

Getting to the juice

Part 2: Product Metrics (Acquisition, Usage, Retention, Cost & Monetization)

Unit 4:User Data

Installs, First Launches, Sign-ups

Conversion Rate

Unit 5:Revenue Metrics

DAU/MAU Ratio

ARPU

LTV

CAC

Unit 6:User Retention and Stickiness

Retention curves

Revenue retention

Event-based retention

Churn analysis

Reactivation strategies

The cost of poor retention

UX and value examples

Unit 7:Monetization and Metrics

Pricing models and revenue streams

IAPs, Ads, Paywalls, Subscriptions

Monetization and UX tradeoffs

Experimentation and A/B testing

Monetization examples

Unit 8:Distribution and Channels

CAC across channels

Channel competition

Measuring product-channel fit

Key metrics per channel

Part 3: Behavioral and Experience Metrics

Unit 9:Behavioral Metrics

Feature usage

Product and feature pairing

Sentiment analysis

Emotion detection (experimental)

Location analysis (experimental)

User interviews and surveys

Segmentation

Device specs and UI/UX analysis

Who this course is for:
- Product managers, marketing managers, growth leads, and startup founders who want to make better product decisions using data even without a data team.
- Individuals interested in the product side of marketing and improving acquisition and retention
More Info