As a game developer, you know the importance of data in understanding player behavior and optimizing your game. But with so much data available, it can be difficult to make sense of it all. That’s where datamining comes in.
What is Datamining?
Datamining is the process of collecting, organizing, analyzing, and interpreting large amounts of data to uncover patterns and insights that can be used to improve a product or service. In the context of mobile games, datamining involves collecting data on player behavior, such as how often they play, what levels they complete, and which items they purchase. This data can then be analyzed to identify trends and patterns that can help game developers make informed decisions about their game’s design, monetization, and overall success.
What Data Should You Collect?
When it comes to mobile games, there are several types of data you should collect in order to effectively datamine your game. These include:
- User Acquisition Data: This includes information on how players find your game, such as whether they came from social media or an ad. By analyzing this data, you can identify which marketing channels are most effective for acquiring new players.
- In-Game Data: This includes data on player behavior within the game, such as how often they play, what levels they complete, and which items they purchase. By analyzing this data, you can identify which features of your game are most popular among players and which may need improvement.
- User Demographics Data: This includes information about the age, gender, and location of your players. By analyzing this data, you can identify which demographics are most likely to play your game and tailor your marketing efforts accordingly
- Retention Data: This includes data on how long players continue to play your game and how often they return. By analyzing this data, you can identify which features of your game keep players engaged and which may cause them to churn.
- Revenue Data: This includes data on the amount of money generated by your game through in-app purchases and ads. By analyzing this data, you can identify which monetization strategies are most effective for your game and optimize your revenue streams.
How to Collect Data
Now that we’ve discussed the types of data you should collect, let’s talk about how to collect it. There are several methods for collecting data in mobile games, including:
- In-Game Analytics Tools: These tools allow you to track player behavior and other key metrics within your game. Examples include Google Analytics and Mixpanel.
- Surveys and Questionnaires: By sending surveys and questionnaires to your players, you can collect detailed information about their demographics, preferences, and behaviors.
- Social Media Monitoring Tools: These tools allow you to monitor social media conversations and reviews related to your game. By analyzing this data, you can identify common complaints and areas for improvement.
- Focus Groups: Focus groups are a great way to get in-depth feedback from a small group of players. By conducting focus groups, you can gain valuable insights into player behavior and preferences.
How to Analyze Data
With your data collected, it’s time to analyze it. There are several tools and techniques you can use to analyze mobile game data, including:
- Descriptive Analysis: This involves summarizing the data in a meaningful way, such as calculating averages and identifying trends.
- Predictive Analysis: This involves using statistical models and algorithms to make predictions about future player behavior or revenue streams.
- Segmentation: This involves dividing your data into smaller groups based on demographics or other criteria. By analyzing each group separately, you can identify which features of your game are most popular among different types of players.