Our Vanilla Out‐of‐the‐Box solution delivers a consistent data structure tailored for sport betting operations. Designed for marketers, it enables easy segmentation and personalized campaigns. Below, you will find detailed information on the output attributes for the Sport vertical.

What Data Should You Send?

To unlock powerful segmentation, predictive insights, and personalized campaigns for your sports betting platform, Optimove requires specific data about your players and their activities. Providing accurate and complete data ensures you can leverage the full range of attributes—like demographic details, betting behaviors, and predictive scores—described in this article. The following data types are essential:

• Customers: Information about your players, such as age, country, and contact preferences, used to build personalized profiles and target specific audiences.
• Transactions: Records of deposits, withdrawals, and bonuses, critical for calculating financial metrics like average deposit amounts and identifying high-value players.
• Bets: Details of player betting activity, which drive insights into preferences and engagement levels.
• Bets Details: Granular data on individual bets, enabling tailored promotions based on players’ favorite sports or bet types.

Properly preparing these data sets allows Optimove to deliver the actionable insights needed to engage New Players, retain Active Players, and reactivate Churned Players effectively. See Prepare your data for Optimove for more information.

What You Will See in Your Instance

Our solution provides a rich set of attributes to help you understand and engage your sports betting players effectively. Below, each category of attributes is detailed with practical use cases and comprehensive tables.

Demographic Attributes

Demographic attributes provide essential information about your players’ identities and locations, enabling personalized marketing and segmentation. For example:

• The sports betting company uses the AGE attribute from the Customers table to segment players into different age groups and tailor targeted promotional campaigns that increase engagement and retention.

 

Consent Related Attributes

The consent-related attributes track a customer's communication preferences and verification statuses across channels, including email, SMS, and push, as well as flags for opt-in status, test accounts, and general eligibility—all sourced from the Customers table. A kickoff meeting will be held for each channel to provide specific guidance and ensure proper setup based on the channels in use. For example:

• A company utilizes the ALLOW_EMAIL attribute to determine which customers have opted in for email communication, allowing them to send personalized marketing emails only to customers who have explicitly consented, ensuring compliance with privacy regulations and improving email campaign effectiveness.

Please Note: As consent-related attributes are provided alongside other customer data, you are responsible for managing the associated logic, rules, and maintenance.

Calculated Attributes

Calculated attributes track players’ betting and financial behaviors, providing insights for targeting high-value players and optimizing campaigns. These attributes are categorized into Frequency Attributes, Monetary Attributes, and Recency Attributes, calculated over the following snapshot periods:

• Lifetime: Daily aggregated data over the entire customer history
• 2 Weeks: Daily aggregated data calculated based on the last two weeks' data
• 1 Month: Daily aggregated data calculated based on the last month’s data
• 3 Months: Daily aggregated data calculated based on the last three months' data
• 1 Year: Daily aggregated data calculated based on the last year’s data

For example:

• A company uses the AVERAGE_DEPOSIT_AMOUNT to analyze customer deposit behavior over a lifetime, helping them identify high-value customers who consistently deposit large amounts, allowing them to tailor personalized offers, reward programs, or exclusive services to improve customer retention and encourage more frequent deposits.

Note: Attributes marked with * are part of the Activity History feature.

Lifecycle Stage (LCS) Attributes

Lifecycle Stage attributes track the progression of players through different phases of their relationship with the sports betting platform, enabling tailored retention and engagement strategies. For example:

• A company uses the CHURN_FACTOR attribute, which quantifies the likelihood of a customer churning based on their historical behavior, to identify high-risk customers in real-time, enabling the marketing and customer success teams to take proactive steps like offering personalized retention offers, improving engagement strategies, or reactivating dormant customers before they fully churn.

 

Predictive Model Attributes

Predictive model attributes forecast player behaviors, helping you prioritize retention and conversion efforts for maximum impact.

For more information regarding predictive metrics available within the Optimove instance, see the following articles:

• Top Spenders Predictive Model 
• Segmenting Customers by Future Value

Product Attributes- Game History

Product attributes detail players’ betting preferences, allowing for tailored promotions based on their favorite sports or events. For example:

• The sports betting company uses the DISCIPLINE_DISCIPLINE attribute (e.g., 'Football') from Bets_Details to identify players who primarily bet on football. They can then send these players targeted promotions for major football tournaments or offer special odds on important matches, aiming to increase betting activity and engagement with their preferred sport.

Out-of-the-box Campaign KPIs

Out-of-the-box (OOTB) Campaign KPIs measure the success of your sports betting marketing campaigns by comparing the performance of targeted Player Groups, such as Active Players or New Players, against a control group. These metrics, drawn from the Calculated/Activity Attributes, help you evaluate how campaigns drive engagement, deposits, and revenue, enabling data-driven optimization.

• Number of Activity Days: Counts days with player activity (e.g., deposits or bets), showing campaign impact on engagement.
• Number of Deposits: Tracks deposit frequency, indicating campaign success in encouraging financial commitment.
• Total Real Sport Bet Amount: Measures real-money bets placed, reflecting campaign influence on betting behavior.
• Total Sport Net Gaming Revenue: Calculates net revenue from sports betting, highlighting campaign profitability.
• Total Deposit Amount: Sums all deposits made by players, reflecting campaign effectiveness in driving financial activity.

Understanding Your Sport Players: Grouping and Predicting Behavior (Segmentation Model)

To help you connect with your sports betting players in the best way, we organize them into groups based on their actions—like how long since they last placed a bet on your site or app, how much they bet, or how often they deposit money. This process is called Segmentation. We also use these groups to predict what players might do next, like whether they’ll keep betting or take a break. Let’s break it down into two simple ideas: Player Groups and Behavior Predictions.

Player Groups: Organizing Players by Their Journey

Imagine you’re running a virtual betting club. You’d want to group your members based on things like whether they've ever deposited money, how actively they engage with your platform, or how recently they last placed a bet. We do the same with your sports betting players, organizing them into groups based on where they are in their journey with your brand. We call these stages Lifecycle Stages (LCS), and we look at different details for each stage to understand them better.

Predicting Behaviors

Using LCS, segmentation layers, and other demographical and behavioral attributes Optimove is able to create predictive metrics such as Future Value(FV), Risk of Churn(ROC), Conversion Rate, Reactivation Rate, and Top Spenders(TS) to enhance effective marketing strategies.

Here’s how we group players at each stage of their sports betting journey:

1. Non-Depositors: Players Who Signed Up but Haven’t Deposited

These players have signed up for your sports betting platform but haven’t added money to their account yet. We group them by how long it’s been since they joined.

Segmentation Layer	Details
Time Since Registration	1 Day, Up to 1 Week, Up to 1 Month, 1 to 3 Months, More than 3 Months

Example: A player who registered within the past week but hasn’t yet made a deposit could receive a “Get Started” email offering a bonus—such as a free bet—to encourage their first deposit and prompt them to start betting on your app as soon as possible.

2. New Players: Just Started Depositing and Betting

These are players who recently added money to their account and started betting on your platform. We group them by how much they bet, how many deposits they’ve made, how long since their first deposit, and their last activity.

Segmentation Layer	Details
Bet Percentile	Top 10 Percent Bet Amount, 10 to 50 Percent Bet Amount, Bottom 50 Percent Bet Amount
Deposit Activity	3 or More Deposits, 2 Deposits, 1 Deposit
Time Since First Deposit	1 Day, 2 to 7 Days, More than 7 Days
Time Since Last Activity	1 Day, 2 to 7 Days, More than 7 Days

Example: A new player with a high risk of churn—who made their first deposit over 7 days ago and has not deposited since—may receive a push notification offering a “Great Start” bonus, such as a deposit match, to encourage continued engagement on your site.

3. Active Players: Regular Bettors

These are players who regularly log in and bet on your platform. We group them by their recent activity, how much they’ve deposited and bet in the last 3 months, and how often they bet.

Segmentation Layer	Details
Time Since Last Activity	1 Day, 2 to 7 Days, 8 to 14 Days, More than 14 Days
Deposit Percentile Last 3 Months	Top 10 Percent Total Deposit Amount, 10 to 50 Percent Total Deposit Amount, Bottom 50 Percent Total Deposit Amount
Frequency Categorical Last 3 Months	1 to 2 Days, 2 to 7 Days, Over 7 Days
Bet Percentile Last 3 Months	Top 10 Percent Bet Amount, 10 to 50 Percent Bet Amount, Bottom 50 Percent Bet Amount

Example: An active player who logs in every 1 to 2 days and is in the top 10% for deposits might get an email with a loyalty reward, like enhanced odds on an upcoming match, to keep them engaged.

4. Churned Players: Stopped Betting

These are players who haven’t logged in or bet on your platform in a while and might have left. We group them by how long since their last activity, their past deposits and bets, and what stage they were in before they stopped.

Segmentation Layer	Details
Time Since Last Activity	Up to 1 Month, 1 to 3 Months, 3 to 6 Months, More than 6 Months
Deposit Percentile	Top 10 Percent Total Deposit Amount, 10 to 50 Percent Total Deposit Amount, Bottom 50 Percent Total Deposit Amount
Bet Percentile	Top 10 Percent Bet Amount, 10 to 50 Percent Bet Amount, Bottom 50 Percent Bet Amount
LCS Before Churn	New, Active, Reactivated

Example: A churned player in the top tier of both betting and deposit activity—who hasn’t bet in the last two months—may receive a “We Miss You” email offering a risk-free bet to incentivize re-engagement.

5. Reactivated Players: Came Back After a Break

These are players who stopped betting for a while but recently logged in and started betting again on your platform. We group them by their recent activity, deposits, bets, and how often they’ve deposited since returning.

Segmentation Layer	Details
Time Since Last Activity	1 Day, 2 to 7 Days, More than 7 Days
Deposit Percentile By LCS	Top 10 Percent Total Deposit Amount, 10 to 50 Percent Total Deposit Amount, Bottom 50 Percent Total Deposit Amount
Bet Percentile Last 2 Weeks	Top 10 Percent Bet Amount, 10 to 50 Percent Bet Amount, Bottom 50 Percent Bet Amount
Deposit Activity Last 2 Weeks	2 or More Deposits, 1 Deposit, No Recent Deposits

Example: A reactivated player who logged in 3 days ago and made 2 deposits might get a push notification with a “Welcome Back” offer, like a special odds boost, to keep them betting on your app.

6. Dormant Players: Inactive for a Long Time

These are players who haven’t logged in or bet on your platform in a very long time, whether they’ve deposited before or just signed up. We group them by their type.

Segmentation Layer	Details
Dormant Type	Depositor, Non-Depositor

Example: A dormant player who never deposited might get an email with a small free bet, like $5, to try a bet on an upcoming major sporting event on your site.

Please note that the out-of-the-box customer model excludes players who haven’t been active or registered for over 3 years.

Why This Matters for the Sport Vertical

By grouping your players and predicting their behavior, you can create personalized experiences that make them feel valued. Whether it’s offering a bonus to a new player, rewarding a loyal customer with a special bet offer, or winning back someone who hasn’t logged in for a while, these tools help you connect with your players in the right way at the right time—all through your sports betting platform.

Want to learn more? Check out this guide: The Optimove Model.