Become great at product analytics

This class is about getting familiar with product analytics and its associated terms, common questions and pitfalls, as well as differences to other types of analytics (such as web analytics). You’ll also learn about what the difference is between a “classic” website and a web product.

Topics covered:

• Product analytics definition
  
• Differences between product and “classic” web analytics
  
• Common questions and mistakes

Collecting data correctly, at the right time and in the right format is a prerequisite of being able to do any kind of analysis afterwards. Knowing what (and what not) to collect is usually quite difficult, as many questions will not be known at the time data collection needs to be set up. This class covers all of these areas and sets you up to be as future-proof as possible with your data collection setup.

Topics covered:

• Where, when and how to collect data correctly
  
• Data formatting and standards
  
• Implications of incorrect data

Mixpanel, Heap Analytics, Google Analytics, Amplitude, Snowplow - many tools exist on the market today that allow you to collect data and analyze it. Tying in with the previous class about data collection, you will learn about how that data is used in the different tools and most importantly, the core differences in their data collection and analysis strategies in regards to product analytics specifically.

Topics covered:

• Overview of the tools available and their good & bad sides
  
• Gathering requirements and defining use cases
  
• Evaluating tools for your use cases

All products are different and yet, there is a set of common metrics that can be applied universally to each product. This allows comparison across different industries as well as for analysts to compare with previous experiences. Learn some of these core metrics and especially why they are useful in your case.

Topics covered:

• 3 core metrics: Customer Acquisition Cost, Customer Lifetime Value, Churn Rate
  
• Leading vs. lagging metrics
  
• Benefits and drawbacks of core metrics

In order to understand how well a product is performing, users must be understood as much as possible. In this class you will learn more about how to look at users and, specifically, subsets (known as cohorts) of these users for different purposes. Additionally, you will see what kind of metrics can be used to understand your users and their behaviour better.

Topics covered:

• How to understand users
  
• Cohort creation and analysis
  
• Sample user-based metrics used in product analytics

This class addresses many questions that arise when analyzing products. In addition to looking at sample questions, you will also see many challenges that can arise due to, among other reasons, the nature of product analytics being very retroactive.

Topics covered:

• Example questions in product analytics
  
• Common challenges in product analytics
  
• Tactics for addressing challenges
  

In previous classes, multiple metrics are shown as examples that can be used in product analytics. In this class, you will learn methods about how to report and monitor on these metrics and more. You will also learn some basic steps to visualizing data.

Topics covered:

• A selection of metrics for product analytics
  
• Setting up reporting and fundamental data visualisation principles
  
• Setting up monitoring

In this class, you will take all that you have learned about product analytics and learn how take your analysis to the next level by augmenting your data with data from other sources and systems. The real insights happen when you’re able to combine data from multiple places, giving you a more complete view of the users, group of users or aspect of the product you’re focused on.

Topics covered:

• Data fusion how-to, do’s and don’ts
  
• Examples of data fusion
  
• Course wrap-up