This content, written by Rob Martin, was initially posted in Looker Blog on Sep 23, 2020. The content is subject to limited support.
As the Chief Architect for Games at Google Cloud, I was honored to participate in Looker’s recent Data Solutions for Gaming Event. We featured a series of speakers from Google and Looker, as well as customers like FACEIT and King. I’m really excited to share some of the highlights from the event. In particular, I want to recap the trends we’re seeing in the gaming industry and how the data solutions we discussed can help you get ahead of those trends to understand your players better, unlock insights at scale, and use those insights to improve player experience.
Trends in gaming are putting pressure on developers to unlock more insights
One clear trend I see is developers moving toward digital distribution of their games.
Working with AAA game developers — those who traditionally release their games on platforms or consoles — as well as mobile-first developers, we’re in a unique position to see the convergence of these two worlds happening right now. Many traditional AAA developers are moving from physical to digital distribution of their games, like Activision, who released “Call of Duty: Warzone” to major app stores this spring. This shift removes a major friction point for onboarding new users and opens up all sorts of new player experiences. We all have mobile devices in our pockets, we don’t necessarily need to invest in a physical console — which expands the possible player base for these games. This trend is also prompting AAA developers to adopt their mobile-first peers’ business model: try it for free, and then make in-app purchases. This model removes a second major friction point for users, who are likely to try new games first and then move to paid versions.
This digital distribution is bringing a lot of great innovations to the market, from AAA developers to mobile gaming. It’s also creating a new set of pressures on developers. Now more than ever, it’s important to monetize “free” games by converting in-app purchases. To do so successfully, you have to be able to understand and leverage your game data — which likely amounts to millions or billions of events each day — at a very granular level. If you can’t ingest or collect those events, analyze them rapidly, and then unlock the insights, you’ll miss out on the opportunities.
Unlocking insights with Google and Looker
The combination of Google and can help you unlock your organization’s gaming insights. BigQuery ingests and analyzes data at scale, while Looker surfaces insights so you can understand how to monetize your games and drive player engagement. And because BigQuery is a serverless platform, it’s easy to get up and running, removing the need to worry about managing and scaling your infrastructure as your game grows and audience expands.
Looker then integrates seamlessly with BigQuery or your other data warehouse solutions, helping you build data models, dashboards, and unified key performance indicators (KPIs) across your organization. You can also leverage to accelerate your analytics-to-insights timeline. Plus, as an end-to-end, cloud-native solution, your data never leaves the governed zone in the cloud.
Another benefit of Looker’s cloud-native architecture is that it allows you to unlock insights as your game grows. As we move toward multi-player streaming game environments, this is becoming even more critical. For instance, today, “Call of Duty: Warzone” enables about 150 players per match. In the future, I see the potential for thousands or even millions of players to interact in real time, in the same game or match. Analyzing, monetizing, and maximizing the player experience in a game environment that epic is only possible at the scale supported by the combination of technologies like Google and Looker.
Another exciting element of the Google and Looker integration is the ability to integrate machine learning and artificial intelligence into your analytics. During the event, Maria Laura Scuri, Director of Business Intelligence at FACEIT, shared a great story about how the company is using BigQuery and Looker to automate the labeling of player messages and remove toxic content from their platform. This is possible because we expose all our services application programming interfaces (APIs), making it easy to integrate the into your dashboards and make your analytics even more useful with AI.
FACEIT Leverages Looker Blocks to reduce costs and manage analysis
As a combative gaming experiences and tournament platform, FACEIT has many elements of a social gaming network. Their users post content, share highlights from matches, and connect and play with friends. To give you an idea of the scale they’re working at, BigQuery handles about 1 billion events for them each month.
To handle this amount of data efficienty, FACEIT leveragesith the Looker and Blocks, which has significantly reduced a massive analysis bottleneck. Thanks to implementing these Blocks, they’ve seen a marked reduction in the cost and complexity of managing data analysis. They’ve also written a Python script to automate the generation of new LookML tables when content is available, so product managers and developers can immediately see the impact of new features and releases. Today, over half the company is self-serving data, and they’re targeting achieving 100% Looker usage by the end of Q2 2021.
Sharing insights across the organization at King
We were also excited to have join us for the event. With 270 million monthly active users spanning across popular games like Candy Crush, Farm Heroes Saga, and Bubble Witch Saga, they rely heavily on the combination of Looker and BigQuery to serve up insights to a variety of stakeholders, including data scientists, marketers, game artists, and business performance managers.
Principal Data Scientist Simon Wright and Business Intelligence (BI) Platform Director Ian Thompson explained that King Games exposes pre-aggregated data on daily dashboards for easy consumption by their teams to share high-level statistics and trends with everyone in the organization.
They also use Looker to explore data organization-wide. For example, they use data to explore the relationship between user retention and progression through a game. King also analyzes raw event data — win rates, level of duration, purchases — and aggregate it to whatever level they need in order to understand the impact decisions are having on user experience and monetization.
Level up with resources from the Data Solutions for Gaming event
It was a blast to be a part of the Data Solutions for Gaming event. Find out more about the topics we covered in the , or watch a recording of the if you weren’t able to join us live. Plus, you can explore more BigQuery and Looker gaming use cases and how-tos in .
If you’re interested in learning more about the specifics of how FACEIT or King use Looker Blocks to unlock player insights, watch this with Looker’s author Ernesto Ongaro. You’ll get a walk through of the types of user-level and game data you can gather, along with insights about how to use , the funnel explorer, and customizing Looker visualizations for your organization.
Keep leveling up on your competition by unlocking gaming insights with data!