How can game industry research help you stay ahead of the competition?

3 How to conduct game industry research?

Game industry research can be tailored to your goals, resources, and budget. Generally, a framework for game industry research consists of four steps: defining your research question and objectives, choosing the research method and source, analyzing and interpreting the data and information, and applying and communicating the results. When defining your research question, consider what you want to learn and why. When choosing your research method and source, evaluate the advantages and limitations of each one. During analysis and interpretation, process and organize the data into key findings and insights. Finally, when applying and communicating the results, think about how you will use the findings to inform your team or stakeholders.

4 What are some examples of game industry research?

Game industry research can be applied to various aspects of game development and marketing, such as market research, audience research, competitor research, design research, and performance research. Market research may include questions about the size and growth of the game industry in different regions and platforms, as well as popular and profitable genres and subgenres. Audience research may include questions about potential and existing players' demographics, psychographics, motivations, preferences, and pain points. Competitor research can involve looking into direct and indirect competitors' games, features, prices, reviews, marketing strategies, and distribution methods. Design research may involve best practices for game design, mechanics, features, aesthetics, usability, accessibility, and monetization. Performance research may involve measuring and optimizing game performance, retention, engagement, satisfaction, loyalty, and revenue. Additionally, key metrics and indicators for comparison with other games can be identified.

5 What are some challenges and tips for game industry research?

The game industry research landscape is not without its challenges and limitations. Data quality and availability are major issues, as not all data and information are reliable, accurate, relevant, and up-to-date. To ensure accuracy, you must verify and validate your sources and methods, using multiple and complementary sources and methods to triangulate your results. Additionally, data analysis and interpretation can be complex, ambiguous, and contradictory. You need to use appropriate and rigorous tools and techniques to analyze and interpret your data and information while avoiding biases and assumptions. Finally, data application and communication is essential for success; the data must be translated into actionable insights and recommendations that are communicated clearly and persuasively to your team, stakeholders, or audience.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?