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Player Churn

Player Lifetime Value

Early Vip

Responsible Gaming

Bonus Abuse

Player Frequency

Anti Money Laundering

Dashboards

Self-Service BI

Alerts

Marketing Intelligence

Risk Intelligence

Compliance Intelligence

Customized Intelligence

Benefits

Advantages

FAQs

AI MODEL

Strategic Advantages of Accurately Forecasting Player LTV

Marketing Efficiency

Segmenting players into low, medium and high-value buckets, helps gaming operators in optimizing marketing spends.

Creating personalized offers and promotions tailored to players’ predicted Lifetime Value, increases their engagement and spending.

While low-value players may not spend much initially but eventually could convert into medium or high-value players if nurtured correctly with appropriate campaigns.

Improved Monetization

Predicting Player LTV helps the operators in designing and optimizing their platform, ensuring that the pricing and content align with the players' predicted value.

Understanding Player LTV can guide decisions on pricing tiers and also the introduction of premium content.

Churn Prevention

Identifying a low-value player at risk of churning allows for targeted retention strategies, such as offering rewards or creating engagement campaigns to keep them active.

Player LTV predictions helps in designing loyalty programs that reward players based on their potential value, encouraging long-term engagement.

Product Development

Developers can focus on features that are likely to appeal to high-value players, ensuring that development resources are used effectively.

Player LTV insights can be used to balance the game in a way that maximizes player enjoyment while also encouraging players to spend more.

When all of these factors work together—acquiring the right players efficiently, monetizing them effectively, preventing churn, and enhancing the product to keep players engaged—the overall Return on Investment (ROI) for a gaming business improves significantly.

ROI=

Player
Lifetime Spend

-

Player Acquisition Cost

Player Acquisition Cost

x100

Challenges in Predicting Player Lifetime Value

Varied Player Behavior

Players exhibit diverse behaviors, from casual play to high engagement. This makes it challenging to create a one-size-fits-all prediction model.

Players' preferences and engagement levels can change over time, influenced by new game updates, changes in their personal lives, or shifts in the gaming community.

Privacy and Data Regulations

Stricter data privacy laws (like GDPR) can limit the amount of data that can be collected and used for predictive modeling, reducing the accuracy of PLTV predictions.

Modelling Difficulties

The relationship between early player actions and their long-term value is often non-linear, making it hard to model accurately.

High-value players are often a small segment of the overall player base, resulting in sparse data that can be difficult to generalize in predictive models.

GAMWIT can maintain accuracy in PLTV predictions even as player behavior evolves

Handling Data Complexity and Volume

GAMWIT automatically identifies and engineers relevant features from large datasets. This helps in capturing subtle patterns in player behavior that might be too subtle or complex to detect manually.

GAMWIT is designed to update and learn in real time, adapting to new data as players interact with the game.

Our Proprietary Feature Factory

GAMWIT can predict when a player’s LTV is likely to drop, not only based on their behavior patterns but also GAMWIT’s Proprietary Feature Factory. This allows proactive intervention to prevent such drops.

Our Proprietary Feature Factory, developed in-house from decades of experience in the iGaming industry, enhances the prediction accuracy.

Advanced Player Segmentation

GAMWIT leverages complex AI/ML models which can capture non-linear relationships between player actions and their predicted Lifetime Value.

It segments players into different buckets based on their behaviors and characteristics, allowing for more tailored interventions.
This segmentation helps in understanding different player types and predicting their value with higher accuracy.

Enhancing Compliance with Privacy and Data Regulations

GAMWIT trains on behavioral patterns of your players and patterns displayed in your games, it does not need Personally Identifiable Information (PII).

It detects and mitigates biases in data and models, ensuring that predictions are fair and not influenced by unethical factors.

It provides explainable predictions that can help in maintaining ethical standards and building trust with players and regulators.

GAMWIT uses different techniques to predict PLTV

Neural
Networks

Ensemble
Methods

Clustering and Segmentation

Deep Learning Methods

Player Behavior is Dynamic

They vary from:

Game to Game

Company to Company

Demography to Demography

Geography to Geography

The set of behaviors that flag a player as a "High Lifetime Value Player" on your platform may not necessarily be the same for another platform.

Since our model trains on your data, it identifies those behaviors that are specific and relevant to your players.

GAMWIT’s AI Adapts Dynamically

The cognitive capabilities of the GAMWIT's AI detect changes in behaviors of Players over time.

It then adjusts the model to efficiently adapt and improve accuracy of prediction.

ima

This is almost impossible for a human to do without any bias.

GAMWIT’s AI Adapts Dynamically

The cognitive capabilities of the GAMWIT's AI detect changes in behaviors of Players over time.

It then adjusts the model to efficiently adapt and improve accuracy of prediction.

This is almost impossible for a human to do without any bias.

Business Benefits

Optimized Customer Acquisition by identifying profitable acquisition channels.

Optimized Marketing Spends

Maximizing Monetization and Revenue

Enhanced Retention and Reduced Churn

Effective Cross-Promotion and Upselling

Improved Customer Support and Loyalty

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Plug and Play Solution -
No Technical Expertise
Necessary!

Our Player LTV Model is a Plug-and-Play Solution that your Marketing, Finance, Risk, and Compliance team can use without any experience or skill in data analytics or technical know-how.

This allows you to identify and categorize these potential problem gamers early in your risk and mitigation program, saving time and resources.

Works with all Data Formats

Our dedicated team of experts, helps integrate your gaming data with GAMWIT, no matter where, how and in what format you are collecting or storing it.

Runs Automatically, so you
can Focus on Growth!

Once integrated, GAMWIT is automatic! It delivers individual player wise Predictions to your Risk, Marketing, and Customer Assistance team, scientifically and consistently.

We can also help you integrate GAMWIT with your CRM Systems.

You completely eliminate human bias, or guesswork, because this is data driven - data that is specific to you!

Plug and Play Solution - No Technical Expertise Necessary!

Our Player LTV Model is a Plug-and-Play Solution that your Marketing, Finance, Risk, and Compliance team can use without any experience or skill in data analytics or technical know-how.

This allows you to identify and categorize these potential problem gamers early in your risk and mitigation program, saving time and resources.

Works with all Data Formats

Our dedicated team of experts, helps integrate your gaming data with GAMWIT, no matter where, how and in what format you are collecting or storing it.

Runs Automatically, so you can Focus on Growth!

Once integrated, GAMWIT is automatic! It delivers individual player wise Predictions to your Risk, Marketing, and Customer Assistance team, scientifically and consistently.

We can also help you integrate GAMWIT with your CRM Systems.

You completely eliminate human bias, or guesswork, because this is data driven - data that is specific to you!