Building a successful game is all about figuring out what players want and how to get them to pay you to provide it. If only there was a way to peer into the minds of gamers to discover their innermost thoughts and desires.
What if I told you there is? Game analytics is the closest thing to a crystal ball when it comes to understanding your players. However, there are a few things you need to know to get the most out of your analysis.
Every time a player opens your app, they generate new data. Regularly analyzing this data provides insights into how players play your game, what they want, and what you can do to increase engagement, retention, and monetization. To get the most out of your analysis, track data from multiple sources and cross-reference it to create telemetric data.
Telemetry describes the communications process companies use to receive and record data. Telemetric data consists of multiple variables and data sets that you collect over time.
Examples of telemetry in the gaming industry include naming conventions, data structures, and the operations you perform on data. However, telemetry can also describe raw data. When working with telemetric data, it is important to understand which things are objects and which are attributes of those objects.
To maximize the value of your game analytics, you must organize your data. This process begins with creating naming conventions and ensuring your team understands any conventions that are unique to your project.
Analyzing data involves collecting and tracking variables. To accurately track variables, you must define your data set’s domain and standardize your measurements. For example, if you are measuring time, are you measuring it in minutes or seconds?
Be specific about which data you are tracking and how you intend to track it. For example, when tracking player purchases, are you tracking the total amount of money players spend, the number of items they buy, or both?
To put analytics to use, all of your stakeholders must be able to understand the results of your analysis. To achieve this, you need to be able to share your analytics.
Start by choosing a high-performing data warehouse, data lake, or compute environment. A cloud-based environment makes sharing easier when working with stakeholders who are not located in the same physical space.
Store your telemetric data in formats that you can easily turn into commonly understood metrics for reporting purposes. If you are new to game analytics, you may benefit from integrating with a game analytics solution that uses standard metrics.
Data warehouses, data lakes, and compute environments are resources that help you manage disparate data sources in the cloud and process structured and semi-structured information.
For complex games, you may need to utilize multiple resources to analyze and enrich player data, generate constant insights, and ensure you meet privacy and regulatory standards.
Most traditional data analysis techniques were not designed for use with the terabytes of data that modern complex games generate. You can overcome the challenges of working with so much data by employing techniques, such as sampling and parallel programming.
Games have so many variables you can analyze that it can be easy to focus too much on micro-optimizations. Because you only have so many resources to work with, though, it’s better to focus on the big picture.
Identify which aspects of your game have the largest impact on your goals and focus your resources on analysis that supports those aspects. Spend your time and computing power analyzing only what matters and what is relevant to what you want to improve.
Begin planning your game analytics strategy early in your development process. Choose which metrics you want to monitor based on your goals. Integrating analytics from the start allows you to track the lifetime value of your players and make development decisions based on the insights you gain from analyzing your players’ behavior patterns.
The most common analytics mistake developers make is hyperfocusing on short-term results. The insights you gain from your analysis will tend to be more accurate over the long term, because temporary shifts in player behavior can skew a short-term analysis.
It is also important to remember that your analysis is not infallible. Errors can creep in along every step of the process. Don’t be afraid to change your methods or retest if you don’t think your analysis makes sense.
Implement a retention policy from the start. It is impractical and expensive to retain all of your data forever. Regularly cleanse your data to avoid generating inaccurate analysis based on erroneous data.
At Sonamine, we blend machine learning, hands-on live ops, and CRM services with game analytics to help companies like yours take their games to the next level. Our team of expert data slingers provides advanced analysis, creative services, AB testing, reporting, and ongoing tweaks to help you achieve your goals. Contact us today to find out more about how we can help you build an engaged, long-term, profit-generating player base for your game.
For a limited time until Sep 30, 2023, Sonamine is offering a free trial to Leanplum customers. Come experience the ease and simplicity of the First Time Spender Nudge package and watch your conversions soar.