The right AI models can revolutionise player experience, increase retention, and increase revenue. Just imagine the possibilities they unlock for your iGaming venture – tailored strategies, informed decisions, unparalleled player satisfaction, and more await. With AI, every move is smarter and every win is bigger!
In this post, we will introduce you to InfinityAI which can be used for modelling in iGaming.
Adaptive models aren't your run-of-the-mill, static algorithms that get outdated faster than last season's game meta. Nope. You can take advantage of them, offering the kind of flexibility and precision that makes sure your strategies are sharp.
The Adaptive AI technology automatically evaluates multiple models to find the best-performing model for your unique data set, use case and goals (1:1 approach). At scale and at pace.
Yes – these models learn from your data, evolve with your challenges, and make sure that you're not just keeping up but setting the pace.
Ready to see how these smart models can transform your approach, from player retention to optimising your next big campaign? Let's level up your game with adaptive models that promise to keep you at the top of your game.
The time-series forecast model predicts future iGaming trends by analysing historical data. It focuses on understanding past player behaviour, game popularity, and transaction volumes to forecast future events. With its insights, iGaming businesses can plan more effectively, optimising operations and increasing profitability in a competitive market.
The binary classification model is a key component of iGaming analytics. It is designed to make predictions on two possible outcomes. It relies on historical data where the outcomes are clearly labelled, making it possible to learn patterns and predict future events.
Such a model is instrumental in identifying player behaviours and outcomes, helping iGaming businesses tailor interventions and enhance player experiences. Through its predictive power, operators can improve engagement strategies to a previously unknown level.
The multi-class classification model extends the predictive capabilities of iGaming platforms by categorising players into more than two distinct groups.
This approach uses historical data with predefined labels to identify patterns that assign new or existing players to specific value tiers or segments. On top of that, it facilitates targeted marketing and customised player experiences.
Using this model, iGaming businesses can refine their strategies to better meet the needs and preferences of different player groups.
Enhancing VIP management programs through precise segmentation improves player loyalty. Accurately categorising players into different levels of VIP status based on their behaviour and value ensures that VIP programs are effective and appreciated.
With regression modelling in iGaming analytics, you can predict continuous numerical outcomes based on a variety of variable, such as amount wagered, player age, or previous lifetime value (LTV), the model can forecast key metrics like lifetime value, the total number of bets, transaction volumes, gross gaming revenue (GGR), and bonus utilisation. As a result, iGaming operators are better able to optimise player engagement and financial planning, as well as their overall business strategy – all while making precise, data-driven decisions.
Forecasting a player's lifetime value provides insights into long-term profitability from individual players. Accurate LTV predictions help tailor engagement strategies and allocate marketing resources more effectively, ensuring efforts are focused on players with the highest potential return.
Predicting the total number of bets a player will place enables operators to gauge engagement levels and gambling behaviour. This information is crucial for managing risk, tailoring player experiences, and developing strategies to increase betting frequency and volumes.
Estimating the number of transactions players will initiate helps in understanding their activity patterns. Insights into transaction frequencies aid in optimising payment processes and identifying opportunities to encourage more frequent deposits or game plays.
Calculating expected gross gaming revenue (GGR) from players aids in revenue forecasting and financial planning. Forecasting GGR enables operators to plan for growth, allocate resources, and manage budgets more effectively.
Assessing bonus usage patterns among players assists in optimising promotional strategies. Understanding how different players utilise bonuses enables the design of more effective promotions, enhancing player satisfaction and loyalty while ensuring bonus spending is efficient and targeted.
The customer lifetime value (CLV) model in iGaming is dedicated to quantifying the total value a player brings to the platform over their entire relationship. In addition to predicting whether a customer will remain active, it forecasts their next purchase date and lifetime value.
Predictive insight drives player experiences, optimises marketing spend, and prioritises customer engagement. The CLV helps iGaming operators nurture the most profitable relationships, enhance customer satisfaction, and, in turn, maximise long-term revenue.
Optimising customer acquisition strategies by focusing on attracting players with high potential lifetime value. Analysis of high CLV players can be used to refine acquisition efforts, improving the overall quality of the customer base and enhancing revenue growth.
This model analyses player data, such as days since last bet, days since last deposit, average deposit amount, and average stake, to create distinct player groups.
These segments can then be targeted with tailored strategies to maximise engagement, retention, and revenue. Players' diverse behaviour and preferences allow iGaming businesses to deliver more personalised experiences, improve customer satisfaction, and promote loyalty.
Refining risk management and responsible gaming strategies by segmenting players based on risk indicators, such as frequency and amount of bets. This enables operators to proactively address responsible gaming concerns by providing targeted support and interventions to those who may exhibit risky gambling behaviours, promoting a safer gaming environment.
RFM segmentation in the iGaming industry involves categorising players based on three key metrics:
Using this model, iGaming operators can tailor their strategies across different segments to effectively engage and value players. Businesses can enhance customer satisfaction, retention, and revenue, all through differentiating players based on these dimensions.
Improving product and game development strategies by analysing the preferences and behaviours of top RFM segments. Understanding the games and features favoured by the most valuable and engaged players can guide the development of new offerings that are more likely to succeed.
New vs. Returning is an important model for understanding player dynamics in iGaming analytics. This segmentation lets operators measure growth, loyalty, and engagement trends over different periods, such as daily, weekly, monthly, or yearly. The analysis of new versus returning players can help iGaming businesses improve their acquisition efforts and increase overall lifetime value of players.
The Cohort model in iGaming analytics segments players based on their first purchase date, giving a clear view of customer behaviour over time within defined groups.
In this way, engagement, retention, and value can be compared across different acquisition cohorts. These cohorts help iGaming operators gain deep insights into customer lifecycle management, marketing strategies, and onboarding processes.
ABC analysis in iGaming is a strategic approach that categorises products or services based on their importance to the financial success of the business.
This model divides offerings into three categories:
In order to maximise revenue and profit, iGaming operators need to identify which sports, markets, bet types, and casino games contribute most to revenue and profit. ABC analysis helps with that, ensuring that the most impactful elements receive the highest priority.
Through Plug & Play Predictions, operators can maximise campaign success and improve personalisation levels. Easily deploy ready-made models to identify high-value players, prevent player churn, and more to increase player retention and lifetime value.
Churn prediction models in iGaming leverage machine learning to identify players at risk of leaving the platform.
Through analysing player behaviour, transaction history, and engagement patterns, these models can predict which players will churn. Based on this insight, operators can intervene proactively with targeted strategies aimed at keeping the players.
LTV (Lifetime Value) prediction models in iGaming utilise advanced analytics to forecast the future value of players to the business.
The models provide important insights for strategic decision-making by estimating how long players will remain active, the number of bets they will place, and the total amount they will wager. This information can be used by operators to tailor bonuses, messages, and rewards to each player's predicted value.
RFM segmentation uses real-time data about recent purchase behaviour, transaction frequency, and overall spending to automatically divide the customer base. In this manner, operators can understand their players on a deeper level, categorising them based on their engagement and value. This dynamic insight facilitates stronger, more personalised relationships with customers and increases their loyalty.
InfinityAI is the premier solution for iGaming operators who aim to leverage the power of artificial intelligence to predict and influence player behaviour, value, and preferences with precision.
It uses Adaptive AI technology, which automatically selects the most effective model tailored to an operator's unique data and use case – allowing for real-time customisation and optimisation of AI models for unmatched results.
InfinityAI's Adaptive AI provides operators the flexibility to adapt AI models specifically to their data. Such capability allows operators to address niche business needs and swiftly adapt to evolving player behaviours.
For operators seeking immediate results, InfinityAI’s Plug & Play models offer a quick and efficient solution. These models are pre-configured for instant deployment and rapid implementation – without the need for deep technical knowledge.
With Explainable AI, InfinityAI demystifies the AI decision-making process. With this transparency, operators can understand the reasoning behind predictions, all with confidence and trust in the AI. This feature is particularly valuable in managing and adjusting the most complex models.
InfinityAI’s capability extends beyond simple data analysis to facilitate real-world applications. It empowers operators to launch sophisticated, predictive, omnichannel marketing campaigns and gamification strategies. With its Single Player View, operators can initiate personalised player journeys for better retention.
In the iGaming world, AI models make tackling complexity not just manageable, but truly exciting. With these smart solutions, you can improve your retention strategies, increase player engagement, and drive even more growth.
It's no longer just about keeping up with an industry that's constantly evolving, but instead, setting the benchmark.
So, as you move forward, carry with you the insights and inspiration from these advanced models to truly revolutionise the iGaming experience you offer.