Big Data (also known as data analytics) is among the foremost vital developments of the 21st century. In our growing online world, it is the most powerful tool for learning, analyzing and influencing human behaviour. Simply put, big data is the asset and use of information for more effective decision-making. This is something that humans have been doing since the beginning but on an immeasurably large scale. The use of probability equations to understand possible outcomes and behaviours has been established since the 17th century; however, where early mathematicians used smaller data sets for their calculations, modern analysts used larger ones.
What is big data?
Big data refers to the large chunks of structured and unstructured data that businesses accumulate daily. It is not just in the accumulation of data but how a company leverages information to its advantage.
From reducing daily operating costs, developing new games, customizing its offerings to new revenue generation opportunities, understanding players’ behaviour, and improving operational efficiency, Big Data has myriad benefits.
Globally expected to reach $103 billion by 2027, according to Statista, big data is projected to take over 45-percent of the software market.
Three types of big data
Broadly speaking, big data is classified into three categories:
Customer data analytics refers to gathering information about your audience and analyzing behaviour, current living situations, and more that will help you make strategic decisions. You find answers to player-related questions and ways to optimize their journey better using customer data analytics.
Operational Data Analytics – It uses both Big Data Analytics and Business Intelligence to simplify everyday operations and improve your efficiency in real-time. An ideal tool for large corporations to medium-scale gaming companies, Operational Analytics needs a strong team of data scientists and analysts to be successful.
Gaming businesses that follow a traditional model and analyze customer data quarterly, semi-annually or annually will much less frequently make adjustments to their workflow and customer strategies.
Big data analytics in finance refers to a large amount of structured and unstructured data that can be used to study and understand customer behaviour to create growth strategies for financial institutions and banks.
Using financial big data analytics, companies can detect and prevent fraud, better target their customers, improve their overall customer service, gain real-time stock market insights, etc. And can easily identify potential risks.
Mobile games will become more social in the future
An excellent example of this trend is the game called “Among Us”. It was first released in 2018. This game encourages people to work together on different tasks while one or two people secretly trying to prevent the team from winning.
Reasons behind using big data in the mobile games market
Personalized in-game marketing
Personalized in-game marketing increases user engagement while still attracting new people. By using data science, companies can create meaningful marketing messages in the gaming industry.
Live data can be defined as tracking the progress of a large number of users playing an online game. Analysis of this data then determines how many percentages of users are stuck in a particular section of that game. In addition, the data reveals whether players persist to solve the problem or whether they switch off and don’t come back.
It’s hard to know at any particular moment in a game but can be determined through pre-release testing. Knowing how real users respond to that trickery is the key to deciding what to do about it.
Games for all generations
Today, you can play games on any device, with friends in the neighbourhood or your grandparents. In addition, you can watch the game in real-time. The possibilities are unlimited.
Since big data is collected and analyzed in real-time, it can be used to influence behaviour by testing changes. Has easing a challenge or changing the music played on it driven greater user engagement? Big Data allows analysts to quickly divide users into test samples, run various gameplay changes, and analyze their effectiveness. It can test the relative efficacy for different demographics, gameplay experiences, or any data subset to create personalized play experiences. An example of big data usage in the mobile gaming industry can be clearly seen in online slots and casinos. This unprecedented growth sector of the 21st century has leveraged big data into almost every part of its offering. By analyzing the data of both its users and competitors, the gameplay can be fine-tuned in all ways. Providers can measure engagement from the first search to the last minute a player spends on their site or app.
Ads and their placement can be changed or personalized for maximum efficiency for every penny spent.
Another way online casino providers attract new players or re-engage existing players is through bonuses and promotions. For example, 888 is currently offering a 100% welcome bonus and free spins to attract new Irish players. Big data is used to analyze sports trends to maximize the effectiveness of these promotions. For example, a provider may discover that the trending lunchtime habits of a certain demographic are checking Facebook and playing roulette. Offering deposit incentives or bonus jackpots through Facebook advertising at the correct times will increase your chances of connecting with those customers.
5G is changing the experience of gamers
Key benefits of 5G for mobile gaming:
- Minimizes the time required to transfer the dataset between two points.
- Enhanced capabilities for a more immersive multiplayer experience.
- Better streaming opportunities for live service games. Often referred to as cloud gaming.
Business Intelligence (BI) in Mobile Gaming
There are many commercial intelligence services available in the market. All tools have similar functionality and allow the end-users to analyze the collected data without programming knowledge. As in the gaming industry, most companies prefer Tableau, Looker, or Google Data Studio (GDS) because of their compatibility with extensive data mobile sets, data lake architecture, and data warehouses. All this is to say that a visualization tool and a data modelling layer depend on the current infrastructure.
Given the continuous growth of the gaming industry to reach its vast stature, it is no surprise that business leaders are beginning to embrace the potential of big data to the maximum extent. The gaming industry is leading other businesses to maximize the stock of data stored during online activity. Big data allows the video game industry to personalize its service to consumers, whether it’s learning what types of ads to use or how to build social media engagement.