The title of this article may look somewhere between incorrect and confused. However, we stand by its principle because, in our opinion, the relationship between big data and gaming is not just one influencing the other. It’s more like them influencing each other in something of a symbiotic manner.
We may live with the impression that the usage of big data has changed gaming, and that’s that. Yes, data has been around for decades, starting with the usage of increasingly powerful computers. However, the popularity of gaming as a medium of entertainment has also forced data to adopt even more dynamic purposes. Its nature as a collection of information has moved into a phase where it needs to be understood and adapted in real-time.
The reason for this is that gaming, unlike other pieces of media belonging to the entertainment industry, is intrinsically interactive. Data has interacted with dynamic fields before, especially in the case of sports. However, gaming’s interactivity has forced data management (and its applicability) to move extremely fast. It’s gotten to the point of moving beyond reaction and going toward intuition.
What’s capable enough to process data and generate answers immediately? It’s artificial intelligence. And so, the rabbit hole of change starts going deeper. This exact idea is what inspired this article. We believe that gaming and big data (management) have this exactly symbiotic relationship, and we will look into the effects of this dance between the two phenomena.
How Do We Perceive Data Collection And Management?
Data collection is the simple and highly technologized task of farming all kinds of information for a myriad of purposes. They imply your ability to provide your personal and behavior-related information. Once the data collection process gets going, this data gets organized and used for various tasks.
One of these tasks is to understand the data source and its tendencies and anticipate its movements. Since data management is a method of identifying clues, drawing conclusions, and preparing for change, it has become synonymous with understanding phenomena behavior and taking tailored action based on semi-empirical information.
Naturally, today’s data management has created its own phenomenon that pins privacy against the data industry itself. Controversy caused by data farming, not to mention the industry of targeted ads and the creation of sterile products and services, has also been central to every data-related conversation.
In the context of gaming (and not only), we see that data management appears to have inspired decision-making that feels like it’s specifically profit-driven. Rather than using originality and taking a leap of faith for the sake of pursuing vision, data-driven results have become the norm for the sake of what companies call scalability.
Gaming Entries For Various Players
Players have their own wants and needs regardless of the type of gaming that we discuss. Their desires are a bit hard to determine without seeing them materialize in the collected data.
One such idea is the fact that some players tend to play more than others. Some users prefer not to invest in gaming and prefer to play without paying anything to play. Others would prefer to pay their way into progression – something that brought forth the idea of microtransactions in the first place.
In other cases, we see the gacha concept, which is a soft approach akin to gambling. We may even see games that are specifically made with the idea of providing competitive gameplay, while others emphasize the idea of solitary immersion and visual storytelling.
The key idea is that the data industry tries to determine the optimal methods of creating a game type that would fit into a preexisting mold. Adding innovation through upgraded engines and a stronger sense of immersion is yet another idea that is unmistakable. Naturally, the main challenge that we see data contribute to is the indomitable monetization factor.
The Creation Of Player Phenotypes
Player phenotypes are somewhere between a purpose and a result. It’s a bit dehumanizing to think about real human beings as mere categories. It’s also normal, given that we see social classes, races, and even nationalities as being similar categories. However, gaming takes it to the level of turning them into consumers with varying degrees of involvement.
This is nothing new since commercial data usage works in this exact vein. In gaming, we see such categories with varying applicabilities. We see gaming companies create phenotypes that see players as occasional, casual, serious, or hardcore gamers. We also see them look at us as free-to-play users, occasional investors, or even whales.
This idea is all about knowing what to recommend and doing it for a certain reason. Do you, a game publisher, want to turn casual gamers into more involved users? Do you want to stimulate involved users to turn even more competitive? Do you want to ensure that a hardcore gamer doesn’t lose interest?
Real-Time And Targeted Changes
Well, the answers to our rhetorical questions lie in how the managed data is transformed into fast changes. You want to see in real-time if a user’s playing time fluctuates for various reasons. It may be because of lost or won interest or as a result of changes within the game’s infrastructure.
It may also happen because of carefully injected events or micro-tasking opportunities that you, the developer, have created with the use of data. This is where the interactivity becomes more apparent. You throw data-driven elements at the gamer and expect results. You study the effect of said results and their longevity. Now, you have a series of trends and tendencies that you can implement with patching, expansion, or even overhauling during the development of a new title.
The idea is all about knowing what, why, and how to implement change for the sustainability of your game. Data indicates vectors, and the vectors indicate the performance of a game. As a result, your decisions become targeted changes. As AI joins the party, we see how it becomes the holder of data-driven intuition.
Cheat Detection And Fairness Reassurances
This is a bystanding factor that shows us another facet of the behavior. As talented programmers can wear hats of various noncolors, their practices show us that accessing the source code of a game can be the death of fairness. Naturally, countermeasures are usually in place; how do they work?
Well, at first, you can look at the unnatural changes in scripting and how it deviates from the usual flow of a game’s programming entrails. As detection tools perform better, so do the assailants, hence the constant struggle.
However, the idea of cheating moves beyond simple code alteration. It can also be a form of exploiting a weakness or loophole in a game’s operative movements. In cases like online gambling, such exploitation (as opposed to reporting the issue) is a blatant form of abuse that is automatic cheating.
Using data can help the maintenance party to determine abnormalities. Does a player’s in-game currency revenue not match the minimum cooldown for that revenue source? It must mean that something is not going according to plan.
Naturally, there are countless examples of this sort, but the principle remains the same. Data shows tendencies, tendencies formulate pieces of behavior, and behavior can point to cheating.
The Advent Of Personalization
We’ve seen personalization come into its own in various ways. Traditional gaming companies try to think of them as personalized objectives that give the player a sense of purpose. They may also provide random gifts that can generate a renewed interest from the player while also fitting their interests.
Online gambling is one of the most interesting examples of this tendency. If you’re an online gambling operator, offering 40 free spins no deposit for casino game usage would not work if you gift them to a sports betting enthusiast.
The idea of understanding the player and their investments can provide you with the opportunity to give them something for which they can be grateful. Given the tendency to bring out instant gratification as a powerful tool, personalized entries are extremely important in ensuring the efficiency of such gifts.
Conclusion
Since this article is an entry point into the world of data-driven gaming and gaming-driven data management, we see that targeted efficiency is the essence of this relationship. What comes next (i.e., AI-driven decision-making) will be extremely interesting to see how it shapes the industry and the clientele.