How Sportsbook use Analytics

Today, the hype surrounding data analytics has converted into real, documented returns for sportsbooks. Many have achieved double-digit ROI on their analytics investments.

Filling the Seats

From mining a company's website data to understand where customers are dropping out of the marketing funnel to using cluster analysis to understand and reduce customer churn, to utilizing decision trees to raise marketing campaign lift, to pricing seats with revenue optimization models that will provide the sportsbook with the most profitable selling price, analytics is a holistic tool to be used throughout an organization.

  • Descriptive Analytics

    Descriptive analytics includes pattern discovery methods that help with customer segmentation models. These divide customers into their preferred choice of purchase or service. Market basket analysis can help a company's marketing department bundle together more enticing betting promotions. Detailed customer purchasing behavior can also help develop future products and services.

  • Diagnostic Analytics

    Diagnostic analytics attempts to understand customer behaviors by utilizing such techniques as data drill-down, data discovery, data mining, and data correlation. Building a decision tree atop a web user’s clickstream behavior pattern is a form of diagnostic analytics as these patterns often reveal why a browser clicked his way through a sportsbook's website. Information like this is useful for marketing, and operations, which can improve the customer experience. 

  • Predictive Analytics

    Moving up the analytics graph, predictive analytics is useful for CRM, collection analysis, cross- and up-selling, reducing customer churn, improving direct marketing lift, fraud and flaw detection, and labor optimization, amongst many other things.

    Predictive analytics utilizes the following techniques:

    • Regression
    • Linear regression
    • Discrete choice models
    • Logistic regression
    • Multinomial logistic regression
    • Probit regression
    • Time series models
    • Survival or duration analysis
    • Classification and regression trees
    • Multivariate adaptive regression splines
    • Machine learning
    • Neural networks
    • Naïve Bayes
    • K-nearest neighbors

    By utilizing data from within an entire organization, predictive analytics becomes holistic, helping improve departments company-wide. However, this methodology is limited. It only tells you 'what could happen', whereas prescriptive analytics can tell you how to make it happen again. 

  • Prescriptive Analytics

    Prescriptive analytics attempts to optimize a key metric by not only anticipating what will happen next but when and why it will happen again. Risk management models can predict skillful bettors amongst new players. These bettors should not receive marketing offers as they are not customers the sportsbook wants long-term. Problem gambling models can spot players who should be cut off. 

Analytical Models

Simple + powerful analytics accelerates decision-making

Cluster Analysis is a method used to classify objects into groups where those similar in characteristics are grouped together in a cluster. It is also known as segmentation analysis or taxonomy analysis. Clustering helps us look at the data as a whole so we can classify the points and logical structures based on the groupings we choose to create. Clustering has several uses, including in marketing, where it is used to identify homogenous groups of customers, like business travelers or holiday seekers.

Customer Personalization

Customer Churn

Logistic Regression is a binary classification algorithm. Meaning, it predicts either true or false, churn or not, pass or fail, and other binary categorical values. This algorithm also uses a regression function that classifies the target variable based on probability. This splits the data into one of the two categories and each row of data is classified by comparing the probability to a threshold between categories. 

These are some of the easiest models to understand and illustrate as they are straightforward and don't require complex interpretation. Decision Tree models are good for handling complex, non-linear relationships, and outliers on the data. However, they also have their disadvantages. Some of its predictions tend to be weak since they are prone to overfitting. They are not very robust, because small changes in the training data can give a larger change in the output. However, they are one of the most commonly used analytical models around. 

Marketing Uplift

Optimizing Marketing Spend

Spatial data, also known as “Geospatial Data” refers to records in the dataset that have a geographic aspect. It can be the location of a store, the distance between two bus stops, or the boundaries of a state. Spatial analytics help users derive meaningful insights and information from spatial data.  


Intelligencia is partnered with such well-known software vendors as Adobe, Alteryx, Domo, SAS, Pegasystems, Qlik, Tableau, Vantana, HDS, Salesforce, and ITRS, as well as such uniquely casino-specific vendors as Casino Data Imaging, which produces a data visualization tool that helps casino executives understand a patron’s detailed activity on the casino floor. Intelligencia also understands how to integrate open source systems with commercial software, which allows our clients to cut down on data processing time as well as cost.

Intelligencia can help its clients understand the rapidly evolving analytics market so they buy just the right amount of analytics for their unique needs. ROI must be considered when it comes to purchasing analytics and we can show you what's available in the market, as well as what should be avoided. Our clients call us 'trusted advisors' and we wear that moniker with great pride.  


Intelligencia can help its clients understand the rapidly evolving analytics world, with AI and machine learning taking center stage. ROI must be considered when it comes to purchasing analytics and we can show you what's available in the market, as well as what should be avoided. Our clients call us 'trusted advisors' and we wear that moniker with great pride.


Cloud offerings today are anything but simple - private, public, hybrid, edge cloud - all of which have a unique purpose and raison d'etre. At Intelligencia, we can show you how to navigate through this tricky terrain, terrain that gets very costly very quickly if not done right. Do you go with a prepackaged option like Red Hat's Open Stack or will you build something from scratch on your own? So many choices. So many dead-ends. We're here to help. 

Business Intelligence

Intelligencia can help you implement complex BI solutions from the ground up. We can help you understand your data in ways that will simplify your BI initiatives. Our data integration and BI experts can help you navigate the challenging data visualization world so that the data you're expecting to see is exactly what you see in your final dashboard.

Data Integration

The goal of data integration is to extract data from an operational system, transform it, merge it into new datasets, and then deliver it to an integrated data structure built for marketing, analytics, loyalty, and/or social media purposes. DI challengers are intensifying because of the increased demand to integrate machine data and support Internet of Things (IoT) and digital business ecosystem needs for analytical processes. It's a complex world. Don't go it alone. 

Customer Experience

CX solutions include aspects of CRM, loyalty, MCM, and even social. Implementations are highly complex, taking into account multiple source systems, strong data cleansing tools, detailed loyalty programs that track every dollar and every secret and non-secret loyalty point, as well as marketing systems that both send out digital content and track offers used.


Intelligencia can help businesses implement complex marketing and customer experience solutions with their legacy software or help you build them from scratch. We'll help you understand your data in ways that simplify your digital marketing initiatives. Our experts can show you how to augment your legacy data environment to add powerful real-time streaming and in-memory elements that will immediately be recognized by your customers.


+852 5196-1277 HK

+853 6616-1033 Macau

505 Hennessy Road, Suite 613, Causeway Bay, HK

Rua da Estrela, No. 8, Macau


Intellligencia is a Hong Kong- and Macau-based software consulting company that works specifically in the hospitality, gaming, fintech, esports, manufacturing, retail, sports betting, and travel industries. Although located in Asia, we work with clients as far away as North America, Mexico, India, Armenia, Australia, and the Philippines.


Address: 505 Hennessy Road, #613, Causeway Bay, Hong Kong

Phone: +852 5196 1277




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