Analysis of global video game sales
My first educational project in the gaming industry, starting with descriptive analysis in Excel and ending with cluster analysis in Python, followed by the creation of a visual dashboard presentation in Tableau.
Project Objective: The overarching goal of this project was to equip GameCo, the esteemed fictional client, with actionable insights for their strategic foray into the dynamic global video game market. Leveraging data extracted from the VGChartz database, the project revolved around an in-depth analysis of this industry, focusing on the optimal allocation of marketing resources across different regions and game genres.
Context: GameCo, as an aspiring player in the gaming industry, was determined to make informed decisions. These included identifying the most lucrative markets, pinpointing the genres that promise the highest returns on investment, and obtaining an overarching understanding of the prevailing market dynamics. This project was conceived to provide GameCo with a compass that would guide their entry strategy, ensuring it was both prudent and profitable.
What was done:
- Cleaned and analyzed data sets from VGChartz and Steam Store games
- Conducted cluster analysis on Steam Games data to identify trends and patterns
- Recommended strategic marketing budget reallocation based on data analysis of VGChartz data
- Presented suggestions for future research in the gaming market and profitability analysis
- Defined data limitations due to incomplete data sources and potential bias.
Primary stakeholder:
CareerFoundry Project
Project Duration:
May & August 2023
Tools:
Excel, PSPP, Python, Tableau
Skills:
Grouping and Summarizing data
Exploratory and Descriptive analysis
Linear Regression
Clustering
Data visualization
Creating Dashboard
Links:
Resuls:
Based on the analysis conducted, the potential company GameCo obtained data to make data-driven decisions. These decisions could serve the game development department in the most profitable genre and gameplay type, helping identify future market research directions and the most profitable sectors.
Retrospective:
Working on both VGChartz analysis and Steam database analysis, I still haven’t received a detailed answer to all the arising questions. For example: future market growth trends, information about customers and their clusters.
The biggest challenge for me throughout this time has been the search for information, specifically databases for analysis. To address this issue, I plan to delve deeper into studying data collection through APIs and explore all the possibilities of consolidating individual pieces of information into one final dataset.
The gaming industry has always appeared to me as one of the most dynamic and evolving fields, serving as both a leading medium of the future and an excellent opportunity for profit. Therefore, I intend to dedicate time to searching for and studying research on the topic of Customer Behavior and Purchase Prediction.
Some slides from the final presentation:
analyticswithlechner 