Analytics for Product Managers

New
·

3 Weeks

·

Cohort-based Course

Grow your analytics skills to build better products. Learn to define metrics, do analysis, distill insights, and make data-driven decisions.

Previously at

Stripe
Lyft

Course overview

Learn analytics skills that make you dangerous

As a product manager, your success depends highly on your quality of decision-making, strength of execution, and ability to influence your team and stakeholders at your company. Analytics is a key part of the puzzle, and the best product managers consistently leverage their own analytics skills to drive greater impact within their organizations.


In this 2-week course, I will teach you the core analytics tools and skills you need to build better products, make better decisions, and communicate your ideas using data.


WHAT YOU CAN EXPECT


This is a tactical and applied course aimed at giving you skills you can apply immediately in your job. You will be getting your hands dirty! By the end of the course, you will have learned enough skills to be dangerous, and you'll be well on your way to being self-sufficient in driving analytics for your product.


There are 4 modules that cover different ways product managers interact with data in their day-to-day work:


1. Product metrics: defining and operationalizing metrics, and connecting them to business outcomes.

2. Working with data: instrumenting, modeling, querying, and manipulating data.

3. Analysis frameworks: experimentation, user behavior analysis, roadmap prioritization, and other common analysis patterns.

4. Data-driven decision-making: distilling insights, making decisions, and telling stories with data.


Each module contains:


3 hours of live session dedicated to covering concepts, tactics, examples, and discussion.

1 hands-on mini-project to help you apply and practice the skills and frameworks we cover.

Individual feedback on your projects from me.


Finally, I will host an optional AMA / office hours each week to answer specific questions and discuss topics in more detail.


WHO WILL BENEFIT MOST FROM THIS COURSE


* Product managers and engineers who want to up-level their analytics skills and become self-sufficient, especially those who don't come from a quantitative background.

* Product managers and engineers who recently switched to a new role/product that is significantly more data-driven.

* Product managers and engineers who don't have analytics partners and need to become more self-sufficient.

* Product and business leaders who want to dive into the details and engage with their teams on analysis, metrics, and decision-making on a more tactical level.


WHO THIS IS NOT FOR


* This is not for you if you're not interested in doing the mini-projects. This is very much an applied course.

* This is not for you if you work at a company that's pre-PMF or where data doesn't play a big part in product development (e.g. non-software). Much of what we discuss won't be applicable to you.

* This is not for you if you're an experienced data scientist or analyst. Most of the material will be familiar to you.

Who is this course for

01

Product managers and engineers looking to become self-sufficient in analytics in order to make better decisions and build better products.

02

Non-technical founders looking to build a data-driven product culture at their companies and want to develop the skills to lead by example.

03

Business leaders looking to engage at a deeper level with product managers and technical teams on roadmaps, decision, metrics, and goals.

What you’ll get out of this course

Identify the right metrics for your product

Define the core metrics that best fit your product and goals. Understand how to operationalize them via dashboards and connect them to business goals to measure your team's impact.

Query and manipulate data without an analyst

Learn the fundamentals of SQL and spreadsheets and become self-sufficient in querying the data you need. Understand how data models and event data is created and used to calculate metrics.

Perform common product analytics tasks

Learn and apply common product analytics patterns such as hypothesis exploration, A/B testing, user behavior analysis, conversion flow optimization, roadmap prioritization, and more.

Make data-driven decisions, communicate with data

Distill insights from data and translate them into data-driven decisions. Create compelling narratives using data for different audiences.

This course includes

7 interactive live sessions

Lifetime access to course materials

In-depth lessons

Direct access to instructor

Projects to apply learnings

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Week 1

Oct 30—Nov 3

    Oct

    30

    Optional: Meet and greet

    Wed 10/3010:00 PM—10:45 PM (UTC)
    Optional

    Nov

    2

    Product metrics

    Sat 11/24:00 PM—7:00 PM (UTC)

    Nov

    3

    Working with data

    Sun 11/35:00 PM—8:00 PM (UTC)

    Product metrics

    5 items

    Working with data

    5 items

Week 2

Nov 4—Nov 10

    Nov

    6

    Optional: Office Hours

    Wed 11/61:00 AM—2:00 AM (UTC)
    Optional

    Nov

    9

    Analysis frameworks

    Sat 11/95:00 PM—8:00 PM (UTC)

    Nov

    10

    Data-driven decision making

    Sun 11/105:00 PM—8:00 PM (UTC)

    Applied product analytics

    7 items

    Data-Driven Decision Making

    4 items

Week 3

Nov 11—Nov 13

    Nov

    13

    Optional: Office Hours

    Wed 11/131:00 AM—2:00 AM (UTC)
    Optional

What people are saying

        George had a profound impact on my understanding of analytics, its powers, limitations and how to effectively apply it in a fast-growing organization. George has a unique experience scaling a data team from 1 to 100+ in a context of an extremely competitive market and knows first hand the dos, don’ts and what it means to be data-driven.
Gleb Mezhanskiy

Gleb Mezhanskiy

Co-founder and CEO @ Datafold
        George is the definition of a best-in-class data and product professional. He understands what’s required to set product up for success from a practical, hands-on perspective and also how to scale and lead efficiently in various stages of growth. Having worked with him for years, I appreciate so much of what he brings to the table."
Ann Ferracane

Ann Ferracane

GM New York, Director of Growth @ Lyft
        This course build on George's decade-plus experience building products, leading analytics teams, and advising startups. Having worked with him directly, there's no better teacher for this topic.
James Hsu

James Hsu

VP Product and Data @ Xero
        I can say from firsthand experience that I benefited from George's mentorship and advice in the data science and analytics space. So glad to hear others will too!
Tyler Postle

Tyler Postle

Director, Data Science and Analytics @ AppFolio
        Analytics is a highly-leveraged skillset every PM should have but is rarely taught with product managers as the audience. George's course gives PMs a blueprint to up-level their skills and accelerate their careers.
Ojus Padston

Ojus Padston

Staff Product Manager @ Vanta

Meet your instructor

George Xing

George Xing

Product lead at Stripe. Former head of analytics at Lyft and startup founder.

George has spent his entire career working in data: as a product builder, analytics leader, founder, and startup advisor.


He was head of analytics at Lyft from 2014-2020 and spearheaded data-driven decision-making at the company through a period of 100x growth.


After Lyft, George co-founded Supaglue, a data integrations company that raised $6M from Benchmark Capital and exited to Stripe.


Currently, George is a product lead at Stripe where he works on analytics and data products. In his free time, he enjoys helping early-stage startups and occasionally writes in his data blog.

A pattern of wavy dots

Join an upcoming cohort

Analytics for Product Managers

Cohort 1

$500

Dates

Oct 30—Nov 14, 2024

Payment Deadline

Oct 29, 2024

Course schedule

4-6 hours per week

  • Saturdays and Sundays

    9am - 12pm PST

    Live course instruction over 2 weekends. Each 3 hour session corresponds to a module.

  • Hands-on projects

    4-6 hours total

    We will have 4 take-home mini-projects that give you an opportunity to apply the learnings and frameworks from the modules.

  • Office hours (optional)

    Tuesdays 5-6pm PST

    Each week I will host office hours to answer questions and topics from the course.

Learning is better with cohorts

Learning is better with cohorts

Active hands-on learning

This course builds on live workshops and hands-on projects

Interactive and project-based

You’ll be interacting with other learners through breakout rooms and project teams

Learn with a cohort of peers

Join a community of like-minded people who want to learn and grow alongside you

Frequently Asked Questions

What happens if I can’t make a live session?

I work full-time, what is the expected time commitment?

What’s the refund policy?

I have a question about the course. How do I get in touch with George?

A pattern of wavy dots

Join an upcoming cohort

Analytics for Product Managers

Cohort 1

$500

Dates

Oct 30—Nov 14, 2024

Payment Deadline

Oct 29, 2024

$500

3 Weeks