When it comes to staying competitive in the gaming marketplace, launching your game is just the beginning. Players expect games to improve over time, offer new content, and evolve.
Keeping track of player engagement, retention, and conversions means monitoring player activity over time. Putting those stats to work means understanding the context around them:
Where are players spending their time?
What gameplay activities drive conversions?
What rewards keep players coming back?
Capturing these data points requires telemetry, code that reports on in-game events or player properties like the device and OS they use to play your game. Telemetry can get pretty granular, but it can be limiting.
Each data-capture point needs to be individually architected and implemented, meaning that the data you collect, and the picture you build of your players, needs to be precisely planned ahead of time. Adding new telemetry later requires digging into your game code.
In-game chat offers an avenue to gain deeper insights into player activity, without significant ops overhead. With filtering, augmentation, and aggregation techniques, you can consume and leverage large volumes of chat data across your game. And, because you’re acting on a single stream of data, you can more flexibly update how you consume and act on it.
In concert with telemetry, In-game chat data will allow you to improve your community, solve player frustrations, grow your player-base, and level up your live Ops. It’s a brave new world, so let’s jump in:
Trolls or bad actors can swiftly ruin any player community. Meanwhile, family-friendly titles need to guard against profanity as a matter of survival.
Thankfully, machine learning has led to the development of easy-to-use profanity filter APIs that integrate seamlessly into in-game chat to censor foul language and filter abusive messages.
Beyond simple censoring, the best profanity filters implement an understanding of a player’s reputation. Using this metric, you can go one step further than blocking abusive chatter.
Instead, you can aggregate records of a player’s interactions with others to determine whether that player is a true bad actor, and trigger an automated response based on your determination. Auto-ban trolls, relieve players grief, and save on moderation costs!
It may go without saying, but blocking trolls and removing bad-actors will allow your community to flourish as a positive place. This is great on its own. But, as a bonus, it’s just one more thing that will help players build a positive relationship with your game.
One way or another, your players will run into friction while playing your game.
When they encounter bugs, lose matches, or get stuck, players will post to your subreddit, fill out feedback forms, or leave angry reviews. With all these options, the conversation about your game will happen anywhere and everywhere.
But, as with any feedback, the words here only tell half the story. To truly diagnose, understand, and act on feedback, you need context, and that’s where in-game chat comes in.
Using sentiment analysis on chat, in concert with player telemetry, you’ll be able to see precisely where and when players encounter pain points. If you’re looking to fine-tune your balance, look to where players are asking their peers for help, or, in competitive games, which match-ups prompt complaints about the meta.
Using data in this way lets you turn venting players into a resource to improve the game, and ultimately, each player’s experience. Then, as you implement fixes, map player satisfaction over time to see how players respond to your fixes.
Surprise and delight are two well-known ways to keep loyal players interested in your game, and mechanisms like daily log-in rewards have become commonplace. Chat data will let you discover more about your players’ preferences, so you can stay one step ahead, finding unexpected ways to gift them something they’ll love without extensive live-ops overhead.
Specifically, you may want to reward players who strengthen your player community. The flip-side of detecting bad actors is finding (and rewarding) players who bring joy to others. Through chat data, you can see who plays well with others, how often players participate in team activities, and how they interact with peers.
Combine this with in-game performance stats to build player reputations, and allow all this good behavior to trigger in-game celebrations, special offers, and rewards. Community-minded gamers are a valuable resource. Rewarding community stars keeps them engaged, amplifies their positive influence on others, and promotes good vibes all around.
Most of today’s chart-topping games have players spread across the globe, and offer ample opportunities for players to play with those from other countries.
Yet, even if you’ve localized UI text, it’s difficult, if not impossible, to make sure players from different countries can easily and freely communicate through text.
As with profanity filtering, the growth of ML-assisted technologies has made it easy to implement world-class, AI-powered translation into in-game chat. IBM Watson’s Translation API, Amazon Translate, and Microsoft Translator all easily hook in to any well-designed chat app.
Implementing these will let players interact seamlessly, worldwide, no matter what language they speak. On top of bringing your players together, this means less stress, minimal localization costs, and easier rollout to new markets around the globe.
Players love when the game developer takes an active role in the community, especially when it comes to making in-app purchases. This is especially true when it comes to live events and offerings. As games evolve into services across mobile, console, and PC, developers have broadly embraced live-ops as a way to inject content into their titles, keep the game fresh, and respond to the needs of their players.
But, as always, players are voracious, excited, and opinionated. If you’re rolling out fresh characters, offering interesting rewards, or testing time-limited events, traditional engagement stats aren’t always enough to know how your experiments were received.
Using chat data, sentiment analysis, and telemetry, you can get a fine-grained understanding of players’ take on your live content. Build a detailed picture of what your players are reacting to, and how, and roll these insights into future plans. The freshest games survive, and your players will thank you.
Visibility into player activity is invaluable as a resource to improve your game. Traditionally, a specific, highly-orchestrated approach to telemetry would be your only option for gathering deep player insights.
But, with in-game chat, you have access to a trove of dynamic, detailed player interactions. When it comes to improving your game, new technology makes it easy to filter, augment, aggregate, and ultimately analyze player chat data to gain creative insights into player behavior.
Even though apps like Discord offer custom chatbot integrations that can do some of these things, you’re best off implementing chat directly inside your game. In-game chat is the only way to reliably access all this data in one place.
Without in-app chat, these conversations can happen on your official server, but they will also take place on far-flung message boards, in private chat rooms, and manifest in reviews or, simply, silent churn.
With in-game chat, you give yourself a treasure trove of data that lets you improve your player community, get a detailed picture of player pain points, and make your game stand out from the crowd by surprising and delighting players in dynamic ways.
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