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Course · PMs, designers, and analysts new to experimentation

Product Experimentation 101

A conceptual crash course in designing, running, and measuring one product experiment end to end. Learn the hypotheses, metrics, feature flags, and tracking habits that good growth teams rely on, with no statistics or engineering background required.

37 lessons PMs, designers, and analysts new to experimentation Included with membership
JJ

Your instructor

Javid Jamae

Growth engineering leader who scaled Postman from $60M to $100M+ ARR and 20M+ users as Head of Engineering for Growth. Has built and audited experimentation systems at Achieve, Earnest, and Tout. 20+ years in engineering and product leadership.

What you will learn

What you will be able to do by the end.

Explain what an experiment is, why experiments commonly fail, and what good fullstack experimentation looks like end to end.

Write a strong, testable hypothesis and judge whether a hypothesis is actually good.

Pick primary, secondary, and counter metrics, then size the experiment and estimate runtime before you launch.

Set correct demarcation, distinguish exposure from assignment, and target the right users so your analysis holds up.

Write an Experiment Design Document and apply it to a real case study.

Use feature flags for assignment and track clean start and end events while avoiding bad data.

Curriculum · 37 lessons

Everything inside the course.

01

Intro to Experimentation

Build a shared mental model for what an experiment is, why experiments so often fail, and how a single experiment flows through a team from idea to decision.

01What is an Experiment?
02Why Experimentation Fails
03Fullstack Product Experimentation
04The Experimentation Lifecycle
05Roles in a Product Experiment
06Real World Experiment Examples
02

Experiment Design

Turn an idea into a runnable experiment: a sharp hypothesis, the right metrics, correct sizing and runtime, clean demarcation, and a written design document.

07Defining a Hypothesis
08Scope and Prioritization
09Action Plan
10Picking Success Metrics
11Experiment Design Calculators
12Estimating Experiment Runtime
13Demarcation: Start and End
14Traffic Allocation and Variant Assignment
15Exposure vs Assignment
16Targeting and Segmentation
17Writing an Experiment Design Document
18Case Study: OTP Form Prefill
03

Variation Assignment

How users get bucketed into variants with feature flags, what breaks assignment in practice, and how to keep it trustworthy.

19Feature Flags and Assignment
20When Assignment Fails
21Assignment Integrity
22Tools and Ownership
04

Measurement and Tracking

Track the right events cleanly so your analysis reflects reality, including the client versus server pitfalls that quietly corrupt data.

23Event Analytics
24What to Track
25Start and End Events
26Client vs Server
27Tracking Tooling
28How to Avoid Bad Data

How to get access

Included with your Delivering Growth membership.

You do not buy this course on its own. Subscribe to the Delivering Growth community on Skool and you get this course plus every other course, the calculators, and the Custom GPT.

  • All video lessons and written breakdowns for this course
  • Every other Delivering Growth course, included in the same membership
  • The Custom GPT trained on the full course material
  • Free A/B testing calculators and design templates
  • Community access and all future course updates
Subscribe on Skool to get access