Data-driven Product Management Simulator - free course from GoPractice, training Approximately 2 months, Date November 30, 2023.

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Introduction: basic metrics and concepts when working with the product

You will learn basic metrics, the difference between correlation and causation, percentages and percentage points, and the arithmetic mean and median.

How Google Chrome captured the browser market

A brief overview of the history of browser wars. A good analogy for what your new company wants to achieve.

Soft Launch and calculation of basic metrics using Amplitude

The first task from the Chief Product Officer. You will have to understand the Amplitude analytics system, calculate the basic metrics of the application and draw the first conclusions about the product’s readiness for growth and scaling.

Market and competitor analysis

While everyone is preparing for the launch, you have time to study the market based on publicly available data, evaluate audience and downloads of competitors' applications, visualize data, select the most suitable segment for capture.

Product launch

This is a big day for the company - the public launch of a product that has been in development for several years.

Evaluation of the launch result. old friend

Time to evaluate the launch results and their impact on key metrics. Is everything good or bad?

Retention and forecasting the active audience of a product

You will understand the intricacies of the Retention metric and how it is calculated in Amplitude. You will understand how Retention, new users and active audience are related to each other. Build an audience forecasting model to evaluate the impact of different changes and projects on key metrics.

Product metrics and growth metrics

You will compare different things with each other. Find out what metrics are and what they are used for. And also get retention guidelines for different product categories.

Cohort analysis is the basis of product analytics

You will need to understand how the changes made in the new version of the product affected user behavior and key metrics. Amplitude's cohort analysis and funnel tool can help with this.

Statistical significance

To compare the metrics of two versions of a product, it is not enough to count them. It is necessary to check whether the change is statistically significant. You will learn to apply mathematical statistics methods in practice to compare metrics.

Assessing the potential of new functionality

Your manager tells you about a new feature that will soon go into development. You decide to take the initiative and evaluate its potential, for which you create a product model and evaluate the conversions of key funnel steps. This way you understand where to focus your team’s efforts and resources.

Value Hypothesis and Product Model

You'll learn what a value hypothesis is, formulate it, and build a product model to better understand it.

CEO notices something strange

Sunday morning begins with an unexpected letter from the CEO of the company. What's the matter?

Experiments and A/B tests

You will learn to distinguish between hypotheses and facts. Test your instincts by guessing the results of real experiments. Learn to design your own experiments and interpret their results. Formulate an important hypothesis, test it and get unexpected conclusions.

Why? Qualitative user research methods

The unexpected results of the experiment will baffle the team. But you will find a way out of it by using qualitative methods of user research - interviews, surveys and others.

History of WeChat messenger

Time for another cautionary tale to help you rethink what's going on with the product.

We are looking for value. How do people use the product?

You'll learn to use a range of frameworks to find the hidden value of a product. This is how you will find an unexpected use case. Or maybe not. Everything depends on you.

Detuning the product from the found value

You'll use the insight you found in the last chapter to redesign the product around what users find most valuable. And who knows where it will take you.

Test the riskiest hypothesis

You will step into the shoes of real product managers and make difficult decisions. And at the same time, understand why it is so important to remove product risks as early as possible.

Growth hypothesis

The second key hypothesis when creating a product. You will guess the main distribution channels for well-known services and prioritize growth hypotheses for the product.

The ROI metric is the basis of marketing analytics

It's time to understand marketing analytics. It's simple. It is enough to study the intricacies of the ROI metric and learn how to apply cohort analysis for this task.

Target market

The product is progressing, but for meaningful development you need to understand the target market: who your user is, who your direct and indirect competitors are, how the market dynamics work.

Buying traffic in advertising networks

The team begins testing advertising traffic channels. You will understand how advertising networks work. Analyze a number of user test purchases. Assess the product's monetization potential. Make a decision whether to invest in the channel or not.

ASO (App Store Optimization)

You have to form a semantic core for the product, assess the volume of potential traffic and competition.

Step of faith

Despite progress on many fronts, you are far from your goal. The situation is complicated by the fact that the company is running out of money. To get the next round of investment, something needs to change. You have to collect all the accumulated knowledge about the product and make a difficult decision.

Pichok

The decision taken leads to unexpected results. You have to conduct an investigation using all the skills you have previously mastered. This may lead to unexpected conclusions and results.

Consolidation

The denouement of the story. Repetition and consolidation of all skills and knowledge acquired during the training process