Category posts
Product

GoPractice opens a series on how to create products that people need – on the basics of product management.

From this article, you will learn how product work differs through the prism of “problems and pains” from work through the prism of “increasing the effectiveness of the solution.”

ARPU and LTV are often used interchangeably. But in reality, they are two fundamentally different metrics. They are calculated in different ways. They answer different questions.

This article will discuss the following:

• How to calculate ARPU
• How ARPU differs from LTV
• How increasing ARPU can harm your business
• How decreasing ARPU can benefit your business
• Why you need to be careful about using ARPU to make product decisions

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.

Cohort analysis is a highly effective product and marketing analytics tool. Unfortunately, few people know about it, and those who do rarely use it.

This essay will discuss the following:

• What is the essence of cohort analysis?
• What is the difference between growth metrics and product metrics?
• Why do attempts to build product analytics based on growth metrics fail?
• How to use cohort analysis in marketing and product analytics
• Which product metrics should you monitor and why?

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.

LTV (Lifetime Value) is an important metric for decision-making in both marketing and product management. But measuring LTV is a bit tricky and you can easily make mistakes when calculating it. Moreover, even articles that have found their way to the first first page of Google search results contain mistakes when it comes to calculating LTV.

In this essay, I will discuss how to (not) calculate LTV, and how to avoid these common mistakes:

• Calculating LTV based on revenue instead of gross profit.
• Calculating LTV by using users’ Lifetime which is calculated as 1/churn or in any other way.
• Calculating LTV based on the average number of user purchases.

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.

Forecasting the dynamics of revenue, audience, and other key metrics is an important process for any product that is in its growth phase. Having a good forecast helps to prioritize projects at the planning stage, and then helps to keep track of how quickly you are growing against the forecast, allowing you to spot problems as early as possible.

The very process of creating a forecasting model allows you to synchronize the team in terms of understanding the product’s growth model. It also provides a tool for assessing the impact of working on different areas of the model.

Today we will talk about building audience and revenue forecasts for your product using cohort analysis. We will also find out the pitfalls and difficulties of this process.

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.

In the previous essays of this series, we discussed how established companies and products can grow by entering new markets through movement into adjacent dependent segments in the value chain and building new products for an established user base.

Today we will talk about growing through expanding your product to new audiences. Here, the most typical growth paths are geographical expansion and movement up and down the market (B2C – SMB – Mid Market – Enterprise).

We will explore several examples where companies have successfully—and at times, not so successfully—used this growth path. We will also try to define a set of questions that will help to make a more informed decision about choosing this vector for a particular company.

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.

The most common metrics gaming companies focus on are Day-1, Day-7, and Day-30 retention rate. While these metrics are of great help early in the journey, it’s long-term retention which is key to lasting success and a seat in the top-grossing charts. This post makes a case for long term-retention and why your focus should be first and foremost there.

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.

In the previous essay of this series, we discussed how established companies and products can grow by entering new markets through movement into adjacent dependent segments in the value chain. Today, we will talk about another growth path: building new products for an established user base.

We will explore several examples where companies have successfully—and at times, not so successfully—used this growth path. We will also try to define a set of questions that will help to make a more informed decision about choosing this vector for a particular company.

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.

I have been familiar with the concept of the value chains for quite a long time. However, it wasn’t until I read Ben Thompson’s Stratechery blog (I highly recommend reading it at https://stratechery.com/) that I came across its practical applications in market analysis. Looking at products and companies from the point of view of their position in the value chain opens up a new perspective that helps to understand them, find not-so-obvious opportunities, and make more effective decisions.

Today I’ll talk about value chains within the context of expanding an established business or product to new markets. There will be more essays devoted to companies entering the new markets. In each, I will focus on different aspects of this process.

In this series of essays, I want to analyze the possible ways for businesses and products to enter adjacent and new markets. I will also discuss the advantages, nuances and pitfalls of these methods.

In this post, I focus on one of the most risk-free ways to enter a new market, which basically involves moving along the value chain towards the related dependent segments.

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.

Many articles online compare the freemium conversion rates of Spotify, Dropbox, Slack and Evernote. In one article, the author claims that Spotify’s freemium conversion tops Dropbox by 667%. Another article states that Spotify freemium conversion rate is above 40% while “for most companies that leverage this business model, freemium conversion rates hover somewhere between 2 and 5 percent.”

In this post, I will dispel the myth that Spotify’s conversion rate is somewhere around 40-50%. More importantly, I will discuss why It is very important to be clear about what data underlies a certain metric, because people sometimes use the same metric name but in effect they mean different things.

→ Test your product management and data skills with this free Growth Skills Assessment Test.

→ Learn data-driven product management in Simulator by GoPractice.

→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.

→ Join our discussion on LinkedIn. New topics to talk about every week.