Product School Course Notes, Product Manager Certificate

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Product School's instructors and program are, in my opinion, the best on the internet. It's credential seems to also be the most widely regarded. Here is my review of the course along with my notes from it.

Rating:
Outstanding
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Introductions

Course: Product School

From assessing all of the Product Manager-related programs currently available, I believe Product School's instructors and program is the best out there. It's also the most legitimate credential from my perspective. After the first day of the week-long intensive, I'd have to agree.

The following are my notes from the course. If you're reading these and haven't done the course, I recommend doing it for the following reasons:

Instructor: Oleg Pashinin

Oleg has spent 8 years at Google. Oleg working in ads, moved to cloud, then ended in research. He's writing about product management regularly on LinkedIn and open for advice.

As an aside, Google is renound for having the best product managers. They invented the associate product manager program to train PMs. So you can trust what Oleg teaches to be the best in the industry.

Table of contents

The definition of a product manager

A product manager sits in between engineers and users and does everything to make the product succeed. You have to fill in any gap, be it: product marketing, vision and guidance, etc. Simultaneously everyone and no one. You manage the team, present the product, and guide everyone towards what they should do.

Key skills on the PM career path

Traits of successful and unsuccessful PMs

Successful PMs

Unsuccessful PMs

Great content for product managers

Doing a professional reflection

Ask yourself these questions to gain more clarity into how yourself as a professional.

On the product development lifecycle

Broadly, you'll come up with hypothesis on how to solve the problem, figure out how to build a business out of it, validate it, build it as scrappy as possible, delegate. There are two schools of thought on this process: Waterfall and Lean. In reality, the approach is hybrid. Start with a high level plan, then break it down into small initial steps, and iterate towards goal.

There are two schools of thought on this process: Waterfall and Lean. In reality, the approach is hybrid.

Product development lifecycle steps

1. Identify

Pick the right problem to solve. If you're a founder, don't try to solve someone else's problems that you don't have a relation to. Try to solve a problem that you have yourself.

2. Plan

Minimum viable product (MVP) process:

  1. What value are you delivering?
  2. List each feature and why it matters.
  3. Cross off features that don't aid core value prop.
MVP process

An even better MVP is a minimum lovable product.

Building a minimum lovable product

3. Design

  1. Write Product Requirements Document - written by you from user perspective. Could include UI/UX mockups. Write high level with vision to start to share context with team.
  2. Write Technical Design Document - should be done by engineering team.

4. Develop

Build prototype as scrappily as possible to validate it.

5. Launch

6. Assess

Has the launch been successful? You shouldn't celebrate the launch itself very much. Celebrate when it's successful.

7. Repeat

User personas

User personas represent groups of customers. When capturing them, you should focus on how they behave, think, what they want to accomplish, why they want to accomplish it.

Only include details that are relevant to all users of the persona. For example, if age doesn't matter, don't include it.

It's fine to start with an educated guess of what your user personas look like, then iterate on them as you gather more info from your team and users.

It's important to distinguish who makes the buying decision and who is the user. Especially at larger companies.

Example user persona

Metrics (keeping score)

Process of using metrics:

  1. Establish a baseline
  2. Determine course of action
  3. Build a business case
  4. Evaluate success
  5. Move forward using data
When picking metrics to track, chose actionable ones versus vanity.

Product roadmaps

Tools

On assessing the competition & market climate

It's important that a product manager assesses the competition and climate.

Content sources to follow trends are the a16z podcast and Stratechery.

Use the 5Cs to assess competition:

Public speaking

Along with writing, public speaking is one of your other primary skills as a PM.

Here are some general tips:

Verbal speaking tips:

Non-verbal speaking tips:

On speaking structure:

Q&A section tips:

Creating an opportunity hypothesis

How do you know that product is the right one? This is where you apply the scientific method to product.

The world is not short of ideas, it's short of quality execution. 95% of new products fail.

Roughly 50% of the time, your work as a PM will improve the metric it's supposed to. So you need to make sure you do your work to validate your hypothesis before spending the time to build the product.

Your job as a PM is figuring out the critical user journeys that your users are coming to your product for, and then improving them.

No matter the idea, you need to validate and test it if you want the company to be successful. Think of yourself like a scientist in a laboratory who meticulously validates ideas to see if they're correct.

Find Blue Ocean opportunities — areas where your competitors aren't yet. Then you're not limited by your local maxima. This involves risk though.

Setting and approaching goals

  1. What noticeable change do you want to see in the world?
  2. What type of product/feature will get us there? Is it an iterative change in an existing product? Or something entirely new. Come in at a humble place where you don't know if the solution is accurate. Gather data from team, stakeholders, and users, on whether the idea is correct.

Quantitative validation methods

These are less risky and more proven, but less likely to make a breakthrough.

The reason metrics are important is because people often tell you one thing that's not necessarily the case. Different departments can spin their success with a narrative, but including metrics shows more of the truth. (How could blockchains affect this since it's reliant on trust?)

Keep asking "why" a metric is what it is. This gets you to the root cause. Call the "5 whys" and originally invented by Toyota.

Leveraging data effectively

The sequence for leveraging data effectively is:

  1. Collecting
  2. Processing
  3. Analyzing
  4. Publishing

You'll be collaborating with data scientists, data engineers, and data analysts here. So it's important you're friends with these people!

Looking at data

Segmentation - Grouping users by a common trait

Cohort analysis - Adding time to segmentation

Funnels - Looking at a sequence of actions

Pirate metrics funnel

Be sure you sanity check your analytics. Make sure you're tracking the right metrics, using consistent labels, they're properly reported, and the tool is properly collecting data.

Figuring out highest leverage opportunities

You can employ one of the following tactics:

1. Create a grid of scenarios and how each would affect metrics

2. Do a feature audit

Side note: if your product only has one core feature and there's another competitor doing it better than you, then you're in trouble.

3. Use the RICE method

Measure the following against each other:

  1. Reach - How many users it would affect
  2. Impact - How much a metric will move
  3. Confidence - Confidence it will have the level of impact stated
  4. Effort - How much human resource it will take

More details on RICE

4. Use the Kano model

Figure out how much time you would have to spend versus resources needing to be spent.

Definitions:

Over time, as technology evolves, delighters become satisfiers, then satisfiers become basic expectations. Think about the phone touch screen? That never used to exist but now everyone expects it.

Qualitative validation methods

While Quantitative Validation can help you make incremental progress, qualitative validation metrics are where the breakthroughs are made.

Areas that you'll prioritize due to qualitative reasoning are:

Methods of qualitative validation

Business Model Canvas: High level thinking towards business and customers

Value Proposition Canvas:

Internal validation

Doing a SWOT analysis is a popular way to validate hypotheses:

It's important to be able to say "No" as a product manager so you're focused. Steve Jobs said that he's most proud of the things that Apple chose not to work on. This is especially a problem with Junior PMs. You need soft influence to do this.

Ways to say "no":

Customer development

It's recommended that you have a vision for your product before you do customer development.

Customer development is not:

To do customer development, prepare for interviews.

Interview questions fall into the following categories.

As your last question, be sure to always ask: "Is there anything else about <this topic> that I should have asked about?"

This can be a golden question since users will mention things you never thought of.

Finding customers to speak with

While you can ask users to jump on a call and many will for free, you can also offer a $25-50 Amazon gift card. If the person is higher paid, offer a more expensive gift card.

Drawing conclusions

After 10 or so interviews, you'll notice the same trends. You're kind of being a psychologist here — understanding why people want what they want.

While interviews let you talk directly to a small number of customers, surveys are great for being at the quantitative level.

Survey tools: Google forms, Survey Monkey, Typeform, Ask your target market (aytm.com), targeted ads.

A/B testing

A/B testing is a method of validating whether the opportunity hypothesis is working. For this to be effective, you need a lot of data. Optimizely is a great tool to use here.

At larger companies, you'll start your A/B test with a very small number of users, then increase the number.

Example of a small change that has a big impact:

MVPs

Building the leanest MVP (or MLP) possible to validate the hypothesis is the goal. A few ways to do this:

Pre-order MVP - This helps you evaluate if people are interested enough in your idea to open their wallet to it.

Concierge MVP - You work with your customers like a concierge to accomplish whatever your opportunity hypothesis is around. So you're doing things manually instead of building a product.

Google Ads MVP - You A/B test ad copy with different product pitches on them. Then drive the traffic to a landing page. But the data you want to look at is the ad clickthroughs.

Wizard of Oz MVP - Appears automated to the user but it's actually note. You're manually doing everything.

Fake Door MVP - Add a UX trigger (like a button) in your product for whatever feature you're proposing. It won't do anything but throw up an error (or similar). Record how often people take the action. Then if enough people want it, build it.

Random notes

A list of small things to gain respect and rapport with teams, and specifically engineering teams:

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