Multi - Sports & Casino Vertical
Our Vanilla Out-of-the-Box solution delivers a consistent data structure tailored for multi-product (Sport and Casino) operations. Designed for marketers, it enables easy segmentation and personalized campaigns across player activities. Below, you will find detailed information on the output attributes for the Multi - Sport and Casino vertical.
What Data Should You Send?
To unlock powerful segmentation, predictive insights, and personalized campaigns for your multi-product platform, Optimove requires specific data about your players and their activities across both sports betting and casino gaming. Providing accurate and complete data ensures you can leverage the full range of attributes—like demographic details, engagement behaviors across products, 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 and identifying high-value players.
- Bets: Details of player sports betting activity.
- Bets Details: Granular data on individual sports bets.
- Games: Details of player casino gaming activity, including bets and wins.
- Game Types and Categories: Data on casino game names and categories (e.g., slots, table games).
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 across all your product offerings. 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 multi-product 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 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 across both sport and casino.
Demographic Attributes
| Attribute Name | Description | Source Table |
|---|---|---|
| Player ID | The PLAYER_ID from CUSTOMERS table | Customers |
| The EMAIL from CUSTOMERS table | Customers | |
| First Name | The FIRST_NAME from CUSTOMERS table | Customers |
| Last Name | The LAST_NAME from CUSTOMERS table | Customers |
| Mobile Number | The MOBILE_NUMBER from CUSTOMERS table | Customers |
| Date of Birth | The DATE_OF_BIRTH from CUSTOMERS table | Customers |
| Age | Calculated from the DATEOFBIRTH column in the CUSTOMERS table | Customers |
| Gender | The GENDER from CUSTOMERS table | Customers |
| Country | The COUNTRY from CUSTOMERS table | Customers |
| City | The CITY from CUSTOMERS table | Customers |
| Language | The LANGUAGE from CUSTOMERS table | Customers |
| Registration Date | The REGISTRATION_DATE from CUSTOMERS table | Customers |
| Address | The ADDRESS from CUSTOMERS table | Customers |
| Affiliate Id | The Affiliate Id field from CUSTOMERS table | Customers |
| Alias | The Alias field from CUSTOMERS table | Customers |
| Balance | The BALANCE from CUSTOMERS table | Customers |
| Name | The Casino Name field from CUSTOMERS table | Customers |
| Currency | The Currency field from CUSTOMERS table | Customers |
| Referral Type | The Referral Type field from CUSTOMERS table | Customers |
| Registered Platform | The Registered Platform field from CUSTOMERS table | Customers |
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.
Consent Related Attributes
| Attribute Name | Description | Source Table |
|---|---|---|
| Allow Email | Allow communication via email | Customers |
| Allow Push | Allow communication via push notifications/messages | Customers |
| Allow SMS | Allow communication via SMS | Customers |
| Allow WhatsApp | Allow communication via WhatsApp | Customers |
| Is Blocked | The IS_BLOCKED from CUSTOMERS table | Customers |
| Is Email Verified | Customers email is verified | Customers |
| Is Optin | The IS_OPTIN from CUSTOMERS table | Customers |
| Is SMS Verified | Customers phone number is verified | Customers |
| Is Test | The IS_TEST from CUSTOMERS table | Customers |
Please Note: The Is_OptIn attribute acts as a general consent indicator for receiving marketing messages. It is used to query or segment customers who have opted into at least one communication channel, enabling flexible targeting of those with active marketing consent. For example, if a customer opts into email but not push notifications, their attributes would show Allow_Push = 'No', Allow_Email = 'Yes', and Is_OptIn = 'Yes'.
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’ engagement and financial behaviors across both sport and casino, providing insights for targeting high-value players and optimizing cross-product 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. This allows them to tailor personalized offers, reward programs, or exclusive services to improve customer retention and encourage more frequent deposits across their preferred products.
Frequency Attributes
| Attribute Name | Description | Source Table | Snapshot Periods |
|---|---|---|---|
| Number of Activity Days, Lifetime* | Number of activity days, lifetime | Transactions, Games | Lifetime, 2 Weeks, 3 Months |
| Number of Bonus Casino Games, Lifetime* | Number of bonus casino games, lifetime | Games | Lifetime |
| Number of Bonus Casino Winning Games, Lifetime* | Number of bonus casino winning games, lifetime | Games | Lifetime |
| Number of Bonus Sport Bets, Lifetime* | Number of bonus sport bets, lifetime | Bets | Lifetime |
| Number of Casino Game Days, Lifetime* | Number of casino game days, lifetime | Games | Lifetime |
| Number of Casino Games, Lifetime* | Number of casino games, lifetime | Games | Lifetime |
| Number of Casino Mobile Games, Lifetime* | Number of casino mobile games, lifetime | Games | Lifetime |
| Number of Casino Web Games, Lifetime* | Number of casino web games, lifetime | Games | Lifetime |
| Number of Casino Winning Games, Lifetime* | Number of casino winning games, lifetime | Games | Lifetime |
| Number of Deposit Days, Lifetime* | Number of deposit days, lifetime | Transactions | Lifetime, 2 Weeks, 3 Months |
| Number of Deposits, Lifetime* | Number of deposits, lifetime | Transactions | Lifetime, 2 Weeks, 3 Months |
| Number of Real Casino Games, Lifetime* | Number of real casino games, lifetime | Games | Lifetime |
| Number of Real Casino Winning Games, Lifetime* | Number of real casino winning games, lifetime | Games | Lifetime |
| Number of Real Sport Bets, Lifetime* | Number of real sport bets, lifetime | Bets | Lifetime |
| Number of Sport Bet Days, Lifetime* | Number of sport bet days, lifetime | Bets | Lifetime |
| Number of Sport Bets, Lifetime* | Number of sport bets, lifetime | Bets | Lifetime |
| Number of Sport Live Bets, Lifetime* | Number of sport live bets, lifetime | Bets | Lifetime, 3 Months |
| Number of Sport Mobile Bets, Lifetime* | Number of sport mobile bets, lifetime | Bets | Lifetime, 3 Months |
| Number of Sport Multi Bets, Lifetime* | Number of sport multi bets, lifetime | Bets | Lifetime, 3 Months |
| Number of Sport Prematch Bets, Lifetime* | Number of sport prematch bets, lifetime | Bets | Lifetime, 3 Months |
| Number of Sport Single Bets, Lifetime* | Number of sport single bets, lifetime | Bets | Lifetime, 3 Months |
| Number of Sport System Bets, Lifetime* | Number of sport system bets, lifetime | Bets | Lifetime, 3 Months |
| Number of Sport Web Bets, Lifetime* | Number of sport web bets, lifetime | Bets | Lifetime |
| Number of Withdrawals, Lifetime* | Number of withdrawals, lifetime | Transactions | Lifetime |
| Days In Reactivated, Lifetime | Days in reactivated, lifetime | Internal Tables | Lifetime |
| Favorite Casino Game | Favorite casino game | Internal Tables | Lifetime |
| Favorite Sport Type Preference | Favorite sport type preference | Bets, Bets_Details | Lifetime |
| Frequency | Number of days between first and last activity divided by number of activity days | Customers, Bets, Games, Transactions | Lifetime, 3 Months |
| Norm Bet Percentile | Norm bet percentile | Internal Tables | Lifetime, 2 Weeks, 3 Months |
| Product Preference | Product preference | Internal Tables | Lifetime, 3 Months |
Monetary Attributes
| Attribute Name | Description | Source Table | Snapshot Periods |
|---|---|---|---|
| Average Casino Bet Amount, Lifetime | Average casino bet amount, lifetime | Games | Lifetime |
| Average Deposit Amount, Lifetime | Average deposit amount, lifetime | Transactions | Lifetime, 1 Month, 3 Months |
| Average Sport Bet Amount, Lifetime | Average sport bet amount, lifetime | Bets | Lifetime |
| Cashout Ratio, Lifetime | Cashout ratio, lifetime | Internal Tables | Lifetime, 1 Month, 3 Months |
| Casino Bonus Ratio, Lifetime | Casino bonus ratio, lifetime | Games | Lifetime |
| Casino Win Ratio, Lifetime | Casino win ratio, lifetime | Games | Lifetime |
| Net Cash, Lifetime* | Net cash, lifetime | Internal Tables | Lifetime, 2 Weeks |
| Percent of Casino Normalized Bet Amount | Percent of casino normalized bet amount | Internal Tables | Lifetime, 3 Months |
| Percent of Sport Normalized Bet Amount | Percent of sport normalized bet amount | Internal Tables | Lifetime, 3 Months |
| Sport Bonus Ratio, Lifetime | Sport bonus ratio, lifetime | Bets | Lifetime, 3 Months |
| Sport Win Ratio, Lifetime | Sport win ratio, lifetime | Bets | Lifetime, 3 Months |
| Total Average Bet Amount, Lifetime | Total average bet amount, lifetime | Games, Bets | Lifetime |
| Total Bet Amount, Lifetime* | Total bet amount, lifetime | Games, Bets | Lifetime |
| Total Casino Bet Amount, Lifetime* | Total casino bet amount, lifetime | Games | Lifetime |
| Total Casino Net Gaming Revenue, Lifetime* | Total casino net gaming revenue, lifetime | Games | Lifetime, 2 Weeks |
| Total Deposit Amount, Lifetime* | Total deposit amount, lifetime | Transactions | Lifetime, 2 Weeks, 3 Months |
| Total Net Revenue, Lifetime* | Total net revenue, lifetime | Games, Bets | Lifetime, 2 Weeks |
| Total Number of Bets, Lifetime* | Total number of bets, lifetime | Games, Bets | Lifetime |
| Total Real Bet Amount, Lifetime* | Total real bet amount, lifetime | Games | Lifetime, 2 Weeks |
| Total Real Casino Bet Amount, Lifetime* | Total real casino bet amount, lifetime | Bets | Lifetime, 2 Weeks |
| Total Real Sport Bet Amount, Lifetime* | Total real sport bet amount, lifetime | Bets | Lifetime |
| Total Sport Bet Amount, Lifetime* | Total sport bet amount, lifetime | Bets | Lifetime |
| Total Sport Net Gaming Revenue, Lifetime* | Total sport net gaming revenue, lifetime | Bets | Lifetime |
| Total Withdrawal Amount, Lifetime* | Total withdrawal amount, lifetime | Transactions | Lifetime, 2 Weeks, 3 Months |
| Deposit Percentile By LCS | Deposit percentile by lifecycle stage | Internal Tables | Lifetime, 2 Weeks, 3 Months |
| Deposit Activity New | Deposit activity new | Internal Tables | Lifetime, 2 Weeks |
Recency Attributes
| Attribute Name | Description | Source Table | Snapshot Periods |
|---|---|---|---|
| Days Since Lifecycle Stage Change | Days since lifecycle stage change | Internal Tables | Lifetime |
| Days Since Registration | Days since registration | Customers | Lifetime |
| Months Since Registration | Months since registration | Internal Tables | Lifetime |
| Time Since Registration | Flex time since registration | Customers | Lifetime |
| Time Since Last Activity Active | Time since last activity active | Internal Tables | Lifetime |
| Time Since Last Activity Churn | Time since last activity churn | Internal Tables | Lifetime |
| Days Since Last Login | Days since last login | Customers | Lifetime |
| First Deposit Date | First deposit date | Customers | Lifetime |
| Last Login Date | Last login date | Customers | Lifetime |
| Days Since First Activity | Days since first activity | Bets | Lifetime, 3 Months |
| Days Since First Deposit | Days since first deposit | Transactions | Lifetime |
| Days Since Last Activity | Days since last activity | Games | Lifetime |
| Days Since Last Casino Game | Days since last casino game | Games | Lifetime |
| Days Since Last Deposit | Days since last deposit | Transactions | Lifetime |
| Days Since Last Reactivation | Days since last reactivation | Internal Tables | Lifetime |
| Days Since Last Sport Bet | Days since last sport bet | Bets | Lifetime |
| Days Since Last Withdrawal | Days since last withdrawal | Transactions | Lifetime |
| First Deposit Amount, Lifetime | First deposit amount, lifetime | Transactions | Lifetime |
| Last Activity Date | Last activity date | Bets, Transactions | Lifetime |
| Last Deposit Amount, Lifetime | Last deposit amount, lifetime | Transactions | Lifetime |
| Last Deposit Date | Last deposit date | Transactions | Lifetime |
| Time Since First Deposit | Time since first deposit | Internal Tables | Lifetime |
| Time Since Last Activity | Time since last activity | Internal Tables | Lifetime |
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 platform, enabling tailored retention and engagement strategies across products. 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. This enables the marketing and customer success teams to take proactive steps like offering personalized retention offers (e.g., a sports bonus or free casino spins), improving engagement strategies, or reactivating dormant customers before they fully churn.
Lifecycle Stage (LCS) Attributes
| Attribute Name | Description | Source Table | Snapshot Periods |
|---|---|---|---|
| Lifecycle Stage | Lifecycle stage | Internal Tables | Lifetime |
| Dormant Type | Dormant type | Internal Tables | Lifetime |
| Lifecycle Stage Before Churn | Lifecycle stage before churn | Internal Tables | Lifetime |
| Previous Lifecycle Stage | Previous lifecycle stage | Internal Tables | Lifetime |
| Reactivation Action | Reactivation action | Internal Tables | Lifetime |
| Churn Factor | Churn factor | Internal Tables | Lifetime |
Predictive Model Attributes
Predictive model attributes forecast player behaviors, helping you prioritize retention and conversion efforts for maximum impact across your offerings.
Predictive Model Attributes
| Attribute Name | Description | Source Table |
|---|---|---|
| Churn Probability Score | Probability of this customer to migrate into Churn within the next 2 periods | Internal Tables |
| Rank in Churn Probability | Rank among all live customers by Churn probability. On a scale of 1 (lowest) to 100 (highest) | Internal Tables |
| Rank in LCS - Churn Probability | Rank among same lifecycle stage customers by Churn probability | Internal Tables |
| Conversion Probability Score | Probability of this customer to convert within the next 2 periods | Internal Tables |
| Rank in Conversion Probability | Rank among all not-converted by Conversion Probability Score. On a scale of 1 (lowest) to 100 (highest) | Internal Tables |
| Is Top Spender? | Indicates a customer being currently a top spender | Internal Tables |
| Becoming Top Spender Score | Probability of this customer to become a top spender within the next 6 periods | Internal Tables |
| Random Customer Percentage | Random Customer Percentage | Internal Tables |
| Reactivation Probability Score | Probability of this customer to be reactivated within the next 2 periods | Internal Tables |
| Rank in Reactivation Probability | Rank among all churned customers by Reactivation Probability Score. On a scale of 1 (lowest) to 100 (highest) | Internal Tables |
| Rank in Becoming Top Spender | Rank among all customers by Becoming Top Spender Score. On a scale of 1 (lowest) to 100 (highest) | Internal Tables |
| Rank by LCS Becoming Top Spender | Rank among same lifecycle stage by Becoming Top Spender Score. On a scale of 1 (lowest) to 100 (highest) | Internal Tables |
For more information regarding predictive metrics available within the Optimove instance, see the following articles:
Product Attributes - Game History
Product attributes detail players’ gaming and betting preferences across both casino and sports, allowing for tailored cross-promotions based on their favorite games or sports. With the purchase history feature, you can combine the product attributes listed below with transactional attributes to effectively segment your users for multi-product engagement. For example:
- A company with both Sport and Casino offerings uses the DISCIPLINE attribute (e.g., 'Football') from Bets_Details and the GAME_CATEGORY attribute (e.g., 'Slots') from GAME_TYPES_AND_CATEGORIES. This allows them to identify players who primarily bet on football but also play slots. They can then cross-promote by offering football-themed slot games or sending a 'free spins' offer after a major football match to encourage engagement across both verticals.
Product Attributes – Game History
| Attribute Name | Description | Source Table |
|---|---|---|
| Game Category | Game_Category from GAME_TYPES_AND_CATEGORIES table | Product History |
| Game Name | Game_Name from GAME_TYPES_AND_CATEGORIES table | Product History |
| A Team | A team from Bets_Details | Product History |
| B Team | B team from Bets_Details | Product History |
| Bet Type | Bet type from Bets_Details | Product History |
| Discipline | Discipline from Bets_Details | Product History |
| Event | Event event from Bets_Details | Product History |
| Is Live | Is live from Bets_Details | Product History |
| Meeting | Meeting meeting from Bets_Details | Product History |
| Selection | Selection from Bets_Details | Product History |
Out-of-the-Box Campaign KPIs
Out-of-the-box (OOTB) Campaign KPIs measure the success of your marketing campaigns by comparing the performance of targeted Player Groups against a control group, across both sport and casino activities. These metrics help you evaluate how campaigns drive overall engagement, deposits, and revenue.
- Number of Activity Days: Counts days with player activity (e.g., deposits, sports bets, or casino game play), showing campaign impact on overall platform engagement.
- Number of Deposits: Tracks deposit frequency across the platform, indicating campaign success in encouraging financial commitment from players.
- Total Bet Amount (across Sport and Casino): Measures the total value of wagers placed by players on both sports and casino games, reflecting campaign influence on overall betting and gaming volume.
- Total Deposit Amount: Sums all deposits made by players into their accounts, reflecting campaign effectiveness in driving financial contributions.
- Total Net Revenue (across Sport and Casino): Calculates the total net revenue generated from players across both sports betting and casino gaming activities, highlighting overall campaign profitability.
Understanding Your Multi-Product Players: Grouping and Predicting Behavior (Segmentation Model)
To help you connect with your players across both sport and casino in the best way, we organize them into groups based on their actions—like how long since they last engaged with your site or app, how much they bet or play, 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 continue playing/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
We group your players based on where they are in their journey with your brand, using Lifecycle Stages (LCS). For each stage, we look at different behavioral details using Segmentation Layers to understand them better and tailor engagement strategies.
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 and bettors at each stage of their journey:
1. Non-Depositors: Players Who Signed Up but Haven’t Deposited
These players have signed up 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 a week ago but hasn’t deposited might receive a welcome offer for a small free bet on an upcoming sports event or a few free spins on a popular casino game to encourage their first deposit and engagement.
2. New Players: Just Started Depositing and Engaging
These are players who recently made their first deposit and started engaging with sports betting or casino games. We group them by their recent betting/gaming value, deposit activity, and time since first deposit/last activity.
| Segmentation Layer | Details |
|---|---|
| Normalized 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 | 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 who made one deposit 5 days ago and is in the bottom 50% for bet amount might receive a follow-up offer, like a deposit match for their second deposit, to encourage further engagement on either sport or casino.
3. Active Players: Regular Engagement
These are players who regularly log in and engage with your sports betting or casino products. We group them by their recent activity, deposit value, betting/gaming frequency, and overall betting/gaming value.
| 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 |
| Normalized 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 engages 2-7 days per week and is in the top 10% for deposit amounts might receive exclusive VIP offers, such as cashback on sports bets or entry into a high-roller casino tournament, to maintain their loyalty and high level of activity.
4. Churned Players: Stopped Engaging
These are players who haven’t logged in or engaged with sport or casino in a while and might have left. We group them by how long since their last activity, their past deposit and betting/gaming value, and their lifecycle stage before churning.
| 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 |
| Normalized 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 who was previously 'Active' and in the top 50% for deposit amounts, but hasn’t engaged for 2 months, might receive a “We Miss You” campaign with a significant bonus offer applicable to either sports or casino, based on their past product preference, to incentivize re-engagement.
5. Reactivated Players: Came Back After a Break
These are players who stopped engaging for a while but recently returned and started betting or playing again. We group them by their recent activity, deposit value, and betting/gaming value 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 |
| Normalized 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, made a deposit, and placed a few sports bets might receive a “Welcome Back” offer for bonus loyalty points on their next casino play session to encourage cross-product engagement.
6. Dormant Players: Inactive for a Long Time
These are players who haven’t logged in or engaged in a very long time, whether they’ve deposited before or just signed up. We group them by their depositor status.
| Segmentation Layer | Details |
|---|---|
| Dormant Type | Depositor, Non-Depositor |
Example: A dormant player who had previously deposited might get an email with a special offer tailored to their last played game category or last bet sport, like “A $10 free bet on your favorite team is waiting!” or “50 Free Spins on us for the game you loved!”
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 Multi - Sport and Casino Vertical
By grouping your players based on their cross-product behavior and predicting their future actions, you can create truly personalized experiences that make them feel valued across all your offerings. Whether it’s offering a sports bonus to a casino player showing interest in sports, rewarding a loyal multi-product customer with exclusive benefits, or winning back someone who hasn’t engaged for a while with an offer on their preferred product, these tools help you connect with your players in the right way, at the right time, and on the right product—all through your platform.
Want to learn more? Check out this guide: The Optimove Model.
Updated about 18 hours ago