Taking gaming data analytics to the next level with GPU-accelerated databases

25th July 2018 by Brytlyt

Today, gaming studios are using data analytics to identify and understand their players, but often they do not have the necessary analytic and visualisation tools for their data scientists to quickly and efficiently make sense of all the metrics they are collecting. This leaves money on the table by missing countless opportunities to acquire new, extremely motivated and highly profitable players.

As the gaming industry generates more and more revenue – $40.6 billion in global revenue in 2017 on mobile devices alone – and the release of new games by both large studios and start-up developers accelerates, the market for gaming keeps increasing.

The problem for gaming studios is their analytic capabilities are not keeping up

No industry is more data driven than the gaming industry. Many modern-day games, especially those developed for mobile, are built on business models that revolve around data, and understanding how gamers think and respond within a product.

Real-time data analytics can enable gaming companies to collect and model data in order to get a clear picture of how their users interact with their games. With the right tool monitoring player behavior in real-time, gaming studios can keep gamers engaged and happy, even as the gamer learns and adapts to real-time micro-changes to parameters within the game.

With more games comes more data and greater challenges

With the increasing number of mobile games available from both Apple Games and Google Play, along with tight integration to Social Media, there is certainly no lack of data that is collected and compiled about these gamers.

According to the online publication, Reality Games, more than 2 billion gamers are generating 50TB of data per day. AAA multiplayer games alone generate more than 1TB per day from in-game telemetry, and social media games generate another 150GB per day. That is a lot of data and a huge opportunity to increase revenues.

Here are a few statistics to prove it:

Overall, 50% of mobile gaming revenue comes from the top 10% of mobile gamers who are regularly making purchases. These heavy spenders, or “whales”, have been directly compared to the “big fish” courted by traditional gambling casinos. To generate enormous profits, freemium games don’t have to “hook” everyone, they only need to attract a fraction of these die hard players.

By using data analytics in freemium games, gaming studios can accurately measure, predict, and track player behaviour to optimise the experience and increase conversions to paid subscriptions and in-game purchases.

The problem today is not how to collect more data, but rather the challenges that surround the analysis of that data. How to understand the contextual factors that drives new players to become frequent players, how to quickly identify casual players from the whales that represent the high-spending players and who account for the majority of profit.

A critical challenge is using data analytics in real-time to enhance game design and customise an individual gaming experience based on a specific gamer’s tolerance for difficulty and change, or identify features that are not being used.

When gaming studios can quickly understand player behaviour and adapt to that information, they are able to keep players engaged for longer periods of time, so they are more likely to make in game purchases and generate more revenue.

By identifying and understanding key segments in behavior and engagement, gaming studios can more accurately identify the coveted whales and offer them targeted specials and dynamic pricing that increases revenue.

Better Insight Leads To Greater Player Satisfaction

Connections between gamers naturally form clusters, and clusters indicate a desire for certain types of games that correspond to their interests and behaviors. Gaming studios can create gaming experiences that are unique to each player, getting more people to play for longer, and playing longer enhances gamer satisfaction.

Gaming studios can improve marketing campaigns by isolating common player characteristics and leveraging those insights in campaigns. Conversely, they can isolate what characteristics contribute to their non-conforming behaviors and target those segments differently.

A strong membership in a community of gamers decreases the chances of churn. The greater the incentives for gamers to belong to a group of active participants, the more desire they have to engage in competitions. This increases the “stickiness” of players and can lead to more game subscriptions.

Introduction to Brytlyt GPU-Accelerated Database

Recent years have seen massive shifts in technology and use case as databases have re-invented themselves. From clustered servers to in-memory solutions and NoSQL, the focus has largely been on analytics. The growth of datasets and the pressing need to reduce query times has triggered yet another major evolution in how data is processed.

The trend today is to use innovative hardware accelerators like Graphics Processor Units (GPUs) that can run SQL queries on multi-billion row data sets in milliseconds.

Brytlyt’s GPU database acceleration technology, with its patent-pending IP, features:

  • Astonishing Performance: Brytlyt’s GPU-accelerated database technology is transforming the way gaming studios use data. With Brytlyt, gaming studios can query multi-billion row datasets in milliseconds.
  • Easy integration with existing systems: There’s no need for gaming studios to give up their current investments in code, analytics, and visualization. Instead, they can accelerate them with Brytlyt with little to no effort.
  • Smooth scalability: Gaming studios can add and remove GPU resources at will, scaling their processing capability to suit their needs, ensuring they can massively reduce data processing costs.
  • Functionality-rich & easy to use: Brytlyt is built on PostgreSQL, and its deep functionality is complimented by outstanding ease of use.

In Conclusion:

Brytlyt’s goal is to provide gaming studios with real-time visibility and insight that allows them to make the time-sensitive business-critical decisions that directly impact the bottom line of the company, drives player engagement, increases monetization and revenue, and provides a truly tailored gaming experience that significantly increases player satisfaction and loyalty

Brytlyt’s cutting edge solution exponentially improves data processing power without the corresponding massive financial investment current technology require.

Gaming studios looking to get the most out of their GPU database need to understand how important JOINs are and if the vendors they are considering are proficient in this area. Brytlyt has a scalable solution, capable of running JOINs on large data sets. It is PostgreSQL-based so it is also very easy to use and is feature rich. It runs on GPU machines on premise or in the cloud, so setting up Brytlyt for your company is fast and easy!


 How Big Data is disrupting the gaming industry: https://www.cio.com/article/3251172/big-data/how-big-data-is-disrupting-the-gaming-industry.html

Game analysis: Developing a methodological toolkit for the qualitative study of games: http://gamestudies.org/0601/articles/consalvo_dutton

Player-Centred Game Design: Experiences in Using Scenario Study to Inform Mobile Game Design: http://www.gamestudies.org/0501/ermi_mayra/

Empirical Analysis of User Data in Game Software Development https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/Hullett-MSR.pdf

Gaming guru explains why “freemium’ is actually the best business model for multiplayer video games: http://www.businessinsider.com/sean-plott-explains-why-he-thinks-freemium-games-are-the-best-business-model-for-both-players-and-developers-2015-3?IR=T

The future of IAP Monetisation in Mobile Games: https://www.pocketgamer.biz/comment-and-opinion/65748/the-future-of-iap-monetisation-in-mobile-games/