Product analytics [Online course]

Make data-driven decisions with product analytics

Online course:
Product Analytics

By Matthew Brandt, digital analyst @ Bexio / co-founder @ Cook Eat

Course length: 6h

Some of the companies that train their teams at CXL Institute:

How do you turn product insights into action?

It’s all about gathering, measuring, analyzing and communicating product milestones so your company can make data-driven decisions.

Through real-world examples, case studies and a look at what not to do, this course will teach you how to make product analytics a core competency and driver of growth at your company.

Course Overview

After 8 sessions, you’ll:

  • Be a master of collecting and analyzing product-level data accurately
  • Understand how to implement and track important product metrics
  • Know how to compare multiple segments of users with distinct traits and consolidate data from multiple users into single profiles
  • Be a pro at applying useful Google Sheets functions like VLOOKUP and COUNTIF and clustering data as well as apply common MySQL arguments such as COUNT, LIKE and CASE

Matthew does not only carry a deep analytical mindset, but also has the skill of conveying his knowledge in a precise and convincing manner. It’s always a pleasure to discuss innovative data approaches with him.

Janine Lee, Head of Customer Analytics & Business Intelligence @ Ringier Axel Springer Schweiz AG

Benefits

Google Analytics. Mixpanel. Adobe Analytics.

We’ve all heard of them — they’re great for websites and apps with predefined goals and metrics.

But your product is much more complex and often lacks clear targets or paths to success.

This course will demystify your product data and teach you the methods and techniques you need to turn that data into actionable insights.

Working with Matthew means constantly improving yourself: He challenges his coworkers, supports them on difficult tasks and is an ideal sparring partner when developing new ideas. I had the pleasure to work with him in the DA team at Unic for about 1 year and it certainly was a pleasure to have a colleague who never gives less than 100% – be it for customers, projects or when supporting his coworkers.

Martin Seifert, Business Intelligence at Mobility

This course is right for you if…

  • …you’re a Product Owner and need to understand more about your product
  • …you’re an Analyst in a product-driven organization
  • …you’re a UX Researcher and want to understand more about the product

This course is probably not for you if…

  • …you have no experience with traditional web analytics
  • …you already have 2+ years of experience in Product Analytics
  • …you’re not working with a product

Skills you should have before taking this course

  • Some familiarity with data collection, data storage (databases)
  • Good knowledge of common analytics tools such as Google Analytics, Kissmetrics, Webtrekk, Adobe Analytics
  • Experience using a web product (e.g. Trello, Dropbox, Salesforce, etc.)

Matthew is a highly self-motivated digital analytics specialist with a knack for new stuff and automating data flows. He is also well-known for his work in the Swiss Analytics community, being one of the driving forces behind the Analytics Camp.

Lukas Oldenburg, CEO and Analytics Consulting & Implementation Specialist at dim28

Sneak preview: Lesson 1

Introduction to product analytics

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About your instructor, Matthew Brandt

A digital analyst for more than six years, Matthew has done end-to-end analytics for over 50 companies from the ground up by tracking concepts, overseeing implementations, building reporting and performing analyses of the data collected.

The last 2 years Matthew has been delivering deep insights to all different departments and teams of a SaaS-company with a web-based accounting product. In this process he has helped improve trial signup and trial to sale conversion rates, leverage onboarding to give users a faster time-to-value, reduce customer support requests and improve product development through precise data and insights.

Your full course curriculum

Product analytics

Lesson 1

Introduction to 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

Lesson 2

Data collection done right

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

Lesson 3

Analysis tools

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

Lesson 4

Core metrics

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

Lesson 5

User & cohort analysis

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

Lesson 6

Common questions & challenges

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

Lesson 7

Reporting on and monitoring product metrics

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

Lesson 8

Tie it all together

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

Show off your new skills: Get a certificate of completion

Once the course is over, pass a test to earn a CXL certification.

Add it to your resume, your LinkedIn profile or just get that well-earned raise you’ve been waiting for.

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CXL quality guarantee

  • Guaranteed return on time spent or money back.
  • You can immediately apply learnings and improve your results.

Some of the companies that train their teams at CXL Institute: