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Tencent Data Analytics Project

Description

This project focused on analyzing player interactions and optimizing engagement strategies for Tencent's Game of Peace, one of the most popular battle royale games in China. By leveraging Python, SQL and Machine Learning,  uncovered key business drivers, enhanced player retention, and optimized monetization strategies to maximize in-game revenue. 

 

Project Highlights:

  • Uncovered Key Business Drivers – Analyzed 500K+ player interaction records to assess the impact of new feature adoption, seasonal trends, and in-game events on engagement and revenue.

  • Boosted User Retention by 12% – Conducted exploratory data analysis (EDA) to identify player behavior patterns, improving user engagement and reducing churn.

  • Optimized In-Game Monetization – Implemented linear regression models with a focus on P-value significance to detect revenue predictors, refining pricing and monetization strategies.

  • Leveraged Sentiment Analysis for Marketing Insights – Analyzed Bilibili gaming video comments to understand player preferences and feedback, helping shape targeted marketing strategies.

  • Collaborated with Tencent’s Data Team – Translated analytical insights into actionable recommendations, directly impacting game design, player experience, and revenue growth.

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Project Impact:

  • 12% Increase in User Retention – Identified engagement trends and optimized game elements to boost retention.

  • Enhanced Monetization Strategies – Developed data-driven revenue models to improve in-game purchases and ad revenue.

  • Marketing & Player Sentiment Insights – Leveraged player feedback to refine in-game promotions and user experience.

  • Scalable Analytical Framework – Built automated reporting pipelines for continuous game performance tracking.

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This project demonstrates how data analytics and predictive modeling can drive player engagement, revenue growth, and marketing optimization in the gaming industry.

Solar Panels

Code & Report

Link for Code

Link for Report

Code

Skills

- Programming & Data Tools: Python (Pandas, NumPy, Scikit-Learn), SQL

- Statistical & Machine Learning Techniques: Linear Regression, Sentiment Analysis

- Visualization & BI Tools: Tableau, Matplotlib, Seaborn

- Gaming & User Behavior Analytics: Retention Analysis, Engagement Trends, Monetization Strategies

Image by Chris Ried
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