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Game Analytics

Advanced Game Analytics

Building on Game Analytics Fundamentals, we focus on advanced analysis include A/B testing, monetization, economies, features, segmentation and predictive models.

4 Weeks
16 hrs Of Instruction

 

Next Course:     
August 2024

What You'll Learn

Feature Lift Analysis: how to deconstruct a feature and apply analysis techniques to measure its performance. how to use feature lift analysis to predict the impact of marketing campaigns and understand their impact. 


Jupyter Notebooks: How to install and use Jupyter, a web-based notebook for analytics. How to use Jupyter to analyze data using SQL and Python. How to use Python libraries for game analysis. Common Python libraries for statistics, visualization, machine learning and more. 


Economy Analysis: How economies achieve balance. What is TRUE and FREE spend. The inflows and outflows of a game economy. How to analyze a game economy and how to assess economy balance. 


Predictive Model Building: The Model building process. Basic techniques for predictive model building. How models are used in gaming. Examples of models for churn, payer prediction and revenue forecasting. 


Return Rates: Advanced concepts in retention. Engagement segments and grouping. Engagement forecasting for marketing campaign spend. How to understand inflows and outflows for subscriber growth monitoring.


A/B Testing: How A/B testing is effectively used in game design and development. Basic statistical testing and confidence intervals. Which test for which data. Experiment design best practices. 


Player Segmentation: How to discover player segments. Advanced analysis  techniques like K-means clustering and decision trees. How to use SQL and Python libraries to segment players and build models. 


Capstone Project: Capstone project requirements. Capstone project template and recommended approach. How to utilize assignments and course work for your capstone project.

Success strategies

Advanced Game Analytics

Building on Game Analytics Fundamentals, we focus on advanced analysis include A/B testing, monetization, economies, features, segmentation and predictive models.

4 Weeks
16 hrs Of Instruction

Next Course:

August 2024

This Course Includes

  • Office Hours With Instructor, Schedulable Instructor 1-On-1s

  • 16 Hours of Instruction Delivered Over 8 Lessons

  • Downloadable Lesson Slides, Downloadable SQL and Python code

  • Lesson Assignments, Lesson Quizzes, In-Class Exercises

  • Final Course Quiz, Capstone Project For Analytics Portfolio

  • Certificate Of Completion, Digital Certificate Credentials

Course Content

LESSON 01: Retention & Engagement

  • Weekly & Monthly Inflows/Outflow

  • Lapsers And Return Rates

  • Committed Users (Subscribers)

  • Forecasting With DAU & Retention

  • Workshop: Minimum Install Rate

  • Lesson Assignment & Quiz

LESSON 05: Feature Analysis

  • Deconstructing Features

  • Feature Analysis Frameworks

  • Example: Fortnite Loot Chest

  • Workshop: Exploratory Analysis

  • Workshop: Flash Sale Analysis

  • Lesson Assignment & Quiz

LESSON 02: Monetization & Economies

  • Pricing/IAP Analysis 

  • The Layer Cake Model

  • Economy Inflow/Outflow

  • Understanding Economy Balance

  • True vs Free Spend

  • Workshop: LTV Calculation

  • Lesson Assignment & Quiz

LESSON 06: Experimentation (A/B Testing)

  • Statistical Significance

  • Which Statistical Test

  • Confidence Intervals

  • How To Setup An Experiment

  • Experimentation Best Practices

  • Lesson Assignment & Quiz

LESSON 03: Integrating Jupyter Notebook & Python

  • Installing Jupyter Notebooks

  • Access To MySQL Database

  • Python Libraries For Data Analysis

  • Workshop: Gaming Analysis With Python

  • Lesson Assignment & Quiz

LESSON 07: Advanced Analysis Workshop - Part I

  • Advanced SQL Query Techniques 

  • Efficient Sampling & Querying

  • Predictive Model Building

  • Workshop: Payer Prediction Model

  • Capstone Project - Part I

  • Lesson Assignment & Quiz

LESSON 04: Player Groups & Relationships

  • How To Discover Player Segments

  • Workshop: Segment Identification

  • Cluster Analysis Using Python

  • Lesson Assignment & Quiz

  • Workshop: Payer Segmentation Analysis

LESSON 08: Advanced Analysis Workshop - Part II

  • Workshop: Churn Prediction Model

  • Workshop: Decision Tree Analysis

  • Workshop: NLP For Game Reviews Analysis

  • Capstone Project - Part II

  • Lesson Assignment & Quiz


Requirements

  • As an advanced course, learners are recommended to complete the Game Analysis Fundamentals course or have some previous experience in product or business analytics.


  • While not a prerequisite, candidates taking this course would benefit from some experience using SQL for data extraction and analysis. Candidates with no prior SQL experience should review the Game Analysis With SQL Course, which we recommend taking before this course.


  • Note: Learners who purchase multiple courses are entitled to bundle discounts. 


  • Learners will need to be able to install MySQL, DBeaver, Python and Jupyter Notebook software on their Windows or Mac PC to access and use the course data and code.

Description

This course is a natural progression from the Game Analysis Fundamentals course. If you are new to game analytics, our recommendation is to take the Game Analytics Fundamentals course first or the Masterclass: Game Analytics bundle, where you’ll receive a discount. 


Building on top of the Game Analytics Fundamentals course, this course brings several practical and hands-on workshops for advanced analysis of retention in game economies, monetization and player groups. 


Learners will have the opportunity to install and use a MySQL database with game data and Jupyter Notebooks for analysis using supplied SQL and Python code.


In addition, learners will understand how to build predictive models for Lifetime Value (LTV), player churn and player payer propensity, as well as how to segment users into different groups based on engagement and spending behavior.


Finally, in a lesson covering experimentation, learners will understand how A/B testing is used in gaming to optimize the player experience and how feature lift analysis can provide insights that can be used in DAU and revenue prediction. 

This course features several assignments and quizzes to ensure that learners develop a full understanding of the course materials, are able to complete their capstone project and are eligible for a course completion certificate with distinction.

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