5 Data Analytics Mistakes Gaming Companies Make

Home » 5 Data Analytics Mistakes Gaming Companies Make

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The gaming industry has been transformed by big data. At some point, your developers likely just sat and observed people playing your games. They interviewed them about how they felt and used this information – essentially nothing but player sentiment – as a guide for modifications and improvements.

Today’s decisions are driven by more specific, calculated metrics. Data analytics and automated databases provide rapid results. With this also comes the opportunity for significant data analytics mistakes. There is no question that having big data is vital to the success of your gaming company, but what happens when it is used incorrectly?

Here are 5 common data analytics mistakes gaming companies make and how to avoid them.

  1. Tracking Every Player Action

Not all data is good data. In fact, too much data analysis can lead to an inability to measure what is truly relevant. Smart gaming companies pinpoint those analytics which are most important and focus on them. Are you doing this?

You also need to place a priority on data that furthers your company goals. By analyzing player behaviors that specifically align with your company goals, you provide yourself with better information. That data can then guide changes in your game mechanics.

  1. Responding to Single Metrics

Data analytics is about seeing the bigger picture. Gaming companies often hurry to respond to a downturn in a single metric. You’ve implemented quick changes in the hopes of improving retention or monetization. That’s expected.

But you also need to consider the impact these types of changes may have in other areas, or even just on other players. It is essential that you give yourself the ability to measure the secondary effects of changes.

  1. Prioritizing Numbers Instead of Player Behaviors

It’s easy to fall into the trap of comparing how your game is doing against competitors. It’s also common to focus heavily on player retention rather than digging deep into the numbers that really matter: the ones that provide path analysis information critical to understanding your player behaviors.

The highest priority metrics are those that let you know what drives retention. Is it the type of device your game is being played on? Is it the game version? You must analyze what your data is telling you and assess whether it is something that you can act on or improve.

  1. Not Using Game-Specific Metrics

Key performance indicators related to conversion and monthly active users do have value. They can also be misleading. This is especially the case if they are used to generalize information. Game developers need metrics that are specific to player behaviors in each of their games. Non-game specific metrics are a wasted analytics effort. The more precise you are, the more valuable your data becomes.

  1. Not Using Built-in Event Tracking

One of the most expensive data analytics mistakes comes from not planning ahead. When event tracking is left out of early development, for example, it leaves developers unable to make the correlations necessary to monetize or respond to valuable insights. This not only creates delays but also adds unnecessary expenses. These metrics will then need to be added long after they could have been most valuable. They will also take more time to set-up and measure.

Your gaming company relies on data to drive improvement and understand player behaviors. You need immediate access to your data no matter where it is stored. Implementing a data management solution that is efficient and improves productivity can help.

The experts at ShareArchiver are ready to help you implement a data storage management system that is tailored to your needs and will grow with your company.

Call us today for more information at (855) 927-2448.