Become A Data Driven Product Manager

The only course that focuses 100% on data for product managers.

What you'll learn
Product Management
Data analytics
Data Driven Solutions
Define success metrics
A/B test
Read data
Take decisions based on Data
Product Data Driven
User funnel (AARRR) analysis
Conversion rates
Find relevant metrics
Answer interview questions on Data Analytics
Cognitive Biases
Design charts
Present data to stakeholders
Communicate with stakeholders on data
Define events and properties
Requirements
No prior experience is required
Description
Hello and welcome to the course Data Analytics for Product Managers. This course covers all topics you need to know to be a data-driven product manager.In this course, you will learn #1 - How to look at user metrics & business KPIs #2- Look at your data and get insights#3- Take action on your data#4- Track feature success#5- Communicate on data with your stakeholders#6- Use tools like A/B test to drive Data-Driven DecisionsWorking for a software company and having to make decisions on the product can be tricky and complicated. All courses, conferences on product management talk about being data-driven, "take data-driven decisions", "use data to drive decisions…" but articles don't really give a deep understanding of what it means. What should you track? How to look at company KPIs and catch insights? How to act or react to dataHow to work with data departmentsHow to use Data analytic tools like A/B testetc.I was there 6 years ago and I quickly understood that if I want to be a proactive PM who makes data-driven decisions, I need to become an expert in data analytics. For the past year, after feeling confident about it, I decided to gather all my learnings from articles, experiences as a PM and create the most complete course on Data Analytics for Product Managers. My Name is David Kremlinsky. I work for now 6 years in the software industry. Before that, I studied Business Management and completed an MBA in Business Management and Entrepreneurship. I am passionate about data and in this course, I want to turn you into an expert but most importantly, make you enjoy data analytics. What will you learn in this course?Very simple. Be a Data-Driven Product ManagerWhat makes it different from other courses?I thought about the perfect syllabus to cover all topics. To remember something, you have to practice it. In this course, I used real-life examples using the known product as Airbnb, Facebook, Twitter, Amazon, Google, etc, to cover a maximum of industries and make sure the knowledge you acquire doesn’t stop to a simple theoretical knowledge. For this purpose, you will practice on a real case. You will use everything you learned during the course to analyze the situation and give your thought.Most important, you need to practice. The last part of this course is a simulation. You will be a PM at Podcasty and together we will go over your first weeks. I want this course to be interactive! So, don’t hesitate to send me feedback, contact me if you have any questions!After the course, you will be part of a community! I hope to share with you the best articles on product KPIs, open discussions on data and new courses, videos coming!I wish you good luck!David

Overview

Section 1: Chapter 1 - User Funnel Analysis (Part 1)

Lecture 1 Introduction

Lecture 2 Top of the funnel > Acquisition Metrics

Lecture 3 Activation metrics

Lecture 4 Engagement metrics

Lecture 5 Retention metrics

Lecture 6 Churn metrics

Lecture 7 Revenue metrics

Lecture 8 Vanity/Lagging metrics VS Actionable/ Leading metrics

Section 2: Chapter 2 - User Funnel Analysis (Part 2)

Lecture 9 Metrics by industry

Lecture 10 Monetization metrics

Lecture 11 Define actionable company KPIs

Lecture 12 Practice: Define KPIs

Lecture 13 BONUS: practice interview questions on product KPIs

Lecture 14 Your turn! Analyze user funnel analysis

Section 3: Chapter 3 - Measure Product Success

Lecture 15 Introduction

Lecture 16 Type of KPIs

Lecture 17 Good metric definition

Lecture 18 Define success of your features

Lecture 19 Track performance of your features

Lecture 20 BONUS: interview questions

Section 4: Chapter 4 - Get insights from the data

Lecture 21 Introduction

Lecture 22 Approach the data - Define Correlation

Lecture 23 Approach the data - Correlation VS Causation

Lecture 24 Read the data

Lecture 25 Conversion rates metrics

Lecture 26 Cognitive Biases

Section 5: Chapter 5 - From metrics to product decisions

Lecture 27 Introduction

Lecture 28 Act on Data

Lecture 29 React on data

Lecture 30 Let's practice!

Section 6: Chapter 6 - Track actions in your product

Lecture 31 Introduction

Lecture 32 Prerequisite on Data Infrastructures

Lecture 33 Define your events

Lecture 34 Define your properties

Lecture 35 Common tips on events tracking

Section 7: Chapter 7 - Stakeholder interactions

Lecture 36 Introduction

Lecture 37 Collaboration with data teams

Lecture 38 Present data to other stakeholders

Lecture 39 Design charts

Lecture 40 Common tips for data visualisation

Section 8: Chapter 8 - A/B testing

Lecture 41 Introduction

Lecture 42 Before the A/B test

Lecture 43 A/B testing: define a winner!

Section 9: You just get hired as new PM! Welcome to Podcasty!

Lecture 44 Introduction

Lecture 45 1st day at work! Meeting with the HR

Lecture 46 1st day: Interview with Stakeholders

Lecture 47 2nd day at work - Define new KPIs

Lecture 48 3rd day at work - Find assumptions

Lecture 49 2nd week at work - Assumptions to hypothesis

Lecture 50 3rd week at work - Test your hypothesis!

Lecture 51 AB test results!

Lecture 52 7th week at work! Define metrics

Lecture 53 7th week at work! Define events

Lecture 54 8th week at work: Drop in one metric!

Lecture 55 18 week at work: First results…

Section 10: Conclusion

Lecture 56 Conclusion

Product Managers who want to take data driven decisions,Product Managers who use analytics in their daily routine,Students who start or want to start a career as product managers,Students who wants to improve their skills in Data analytics tools like A/B test