Our Vanilla Out-of-the-Box solution delivers a consistent data structure tailored for Social Gaming operations. Designed for marketers, it enables easy segmentation and personalized campaigns. Below, you will find detailed information on the output attributes for the Social Gaming vertical.
What Data Should You Send?
To unlock powerful segmentation, predictive insights, and personalized campaigns for your players, Optimove requires specific data about your customers and their activities. Providing accurate and complete data ensures you can leverage the full range of attributes—like demographic details, gaming 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.
- Games: Records of player activity, including session duration, bets, and wins, which are critical for understanding engagement patterns.
- Payments: Details of all in-app purchases and transactions, which drive insights into spending habits and help identify high-value players.
- Promotions: Data on the specific promotional offers and bonuses given to players.
- Promotion_Types: Details that categorize the different types of promotions available (e.g., 'Free Coins', 'Discount').
- Item_Catalog: Information about all the virtual items available for purchase within the game.
- Points_and_Ranking: Data related to player progression, such as levels, experience points (XP), and current status, used to reward loyalty and encourage continued play.
Properly preparing these data sets allows Optimove to deliver the actionable insights needed to convert Non-Spenders, retain Active Spenders, 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 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 progression, 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.
| Attribute Name | Description | Source Table |
|---|---|---|
| Player ID | A unique identifier for each player. | Customers |
| The player's email address. | Customers | |
| First Name | The player's first name. | Customers |
| Last Name | The player's last name. | Customers |
| Alias | The player's in-game name or nickname. | Customers |
| Mobile Number | The player's mobile phone number. | Customers |
| Date of Birth | The player's date of birth. | Customers |
| Age | The player's age, calculated from their date of birth. | Customers |
| Gender | The player's gender. | Customers |
| Country | The country where the player is located. | Customers |
| City | The city where the player is located. | Customers |
| Address | The player's physical address. | Customers |
| Language | The player's preferred language. | Customers |
| Registration Date | The date the player first registered for the game. | Customers |
| Balance | The player's current in-game currency or real money balance. | Customers |
| Currency | The currency used for the player's transactions. | Customers |
| Player Level | The player's current level or rank within the game. | Points and Ranking |
| Status | The player's current status or tier (e.g., VIP, Gold). | Points and Ranking |
| Affiliate Id | The ID of the affiliate partner who referred the player. | Customers |
| Casino Name | The name of the specific game or platform being played. | Customers |
| Referral Type | The method or channel through which the player was referred. | Customers |
| Registered Platform | The platform or device used by the player to register (e.g., iOS, Android, Web). | Customers |
Consent Attributes
The consent-related attributes track a customer's communication preferences and verification statuses, ensuring compliance and effective campaign delivery. For example:
- A company utilizes the ALLOW_EMAIL attribute to determine which players 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.
| Attribute Name | Description | Source Table |
|---|---|---|
| Allow Email | Indicates if the player has consented to receive marketing communications via email. | Customers |
| Allow Push | Indicates if the player has consented to receive push notifications. | Customers |
| Allow SMS | Indicates if the player has consented to receive marketing communications via SMS. | Customers |
| Is Blocked* | Indicates if the player's account is blocked or suspended from playing. | Customers |
| Is Email Verified | Indicates if the player has verified their email address. | Customers |
| Is Optin | A general indicator that the player has opted into at least one marketing channel. | Customers |
| Is SMS Verified | Indicates if the player has verified their mobile number. | Customers |
| Is Test* | Indicates if the player account is a test account used for internal purposes. | 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'.
Attributes marked with * are not specific to channel consent but can be used to exclude customers ineligible for marketing communications.
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’ gaming and financial behaviors, providing insights for targeting high-value players and optimizing campaigns. These attributes are 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 gaming company uses the AVERAGE_PAYMENT_AMOUNT to analyze player purchase behavior, helping them identify high-value "whale" customers who consistently purchase large amounts of virtual currency.
| Attribute Name | Description | Source Table | Snapshot Periods |
|---|---|---|---|
| Number of Activity Days | Num of activity days categorical | Internal Tables | 1 Month, 2 Weeks |
| Num of Payments Categorical | Num of payments categorical | Internal Tables | 2 Weeks |
| Number of Activity Days, Lifetime* | Number of activity days, lifetime | Internal Tables | 1 Month, 2 Weeks, 3 Months |
| Number of Coins Promotions, Lifetime* | Number of coins promotions, lifetime | Promotions | Lifetime |
| Number of Game Days, Lifetime* | Number of game days, lifetime | Games | 1 Month, 2 Weeks |
| Number of Games, Lifetime* | Number of games, lifetime | Games | Lifetime |
| Number of Mobile Games, Lifetime* | Number of mobile games, lifetime | Payments | Lifetime |
| Number of Mobile Payments, Lifetime* | Number of mobile payments, lifetime | Payments | Lifetime |
| Number of Other Promotions, Lifetime* | Number of other promotions, lifetime | Promotions | Lifetime |
| Number of Payment Days, Lifetime* | Number of payment days, lifetime | Payments | Lifetime |
| Number of Payments, Lifetime* | Number of payments, lifetime | Promotions | 2 Weeks |
| Number of Promotion Days, Lifetime* | Number of promotion days, lifetime | Promotions | Lifetime |
| Number of Promotions, Lifetime* | Number of promotions, lifetime | Internal Tables | 2 Weeks |
| Number of Times Churned Non Spender, Lifetime | Number of times churned non spender, lifetime | Internal Tables | Lifetime |
| Number of Times Churned Spender, Lifetime | Number of times churned spender, lifetime | Games | Lifetime |
| Number of Web Games, Lifetime* | Number of web games, lifetime | Games | Lifetime |
| Number of Web Payments, Lifetime* | Number of web payments, lifetime | Payments | Lifetime |
| Number of Winning Games, Lifetime* | Number of winning games, lifetime | Games | Lifetime |
| Num of Promotions Categorical | Num of promotions categorical | Internal Tables | 2 Weeks |
| Game Platform Preference | Game platform preference | Internal Tables | 1 Month |
| Payment Platform Preference | Payment platform preference | Internal Tables | 1 Month |
| Frequency, Last Month | Frequency, last month | Internal Tables | Lifetime |
| Game Activity Categorical, Last Month | Game activity categorical, last month | Internal Tables | Lifetime |
| Frequency Categorical, Last Three Months | Frequency categorical, last three months | Internal Tables | 3 Months |
| Attribute Name | Description | Source Table | Snapshot Periods |
|---|---|---|---|
| Average Bet Amount, Lifetime | Average bet amount, lifetime | Games | Lifetime |
| Average Coin Promotion Amount, Lifetime | Average coin promotion amount, lifetime | Promotions | Lifetime |
| Average Payment Amount, Lifetime | Average payment amount, lifetime | Payments | Lifetime |
| Coins Balance | Coins balance | Points and Ranking | Lifetime |
| Mobile Bet Amount, Lifetime* | Mobile bet amount, lifetime | Games | 1 Month |
| Mobile Payment Amount, Lifetime* | Mobile payment amount, lifetime | Payments | 1 Month |
| Percent of Mobile Game Amount, Lifetime | Percent of mobile game amount, lifetime | Internal Tables | 1 Month |
| Percent of Mobile Payment Amount, Lifetime | Percent of mobile payment amount, lifetime | Internal Tables | 1 Month |
| Percent of Web Game Amount, Lifetime | Percent of web game amount, lifetime | Internal Tables | 1 Month |
| Percent of Web Payment Amount, Lifetime | Percent of web payment amount, lifetime | Internal Tables | 1 Month |
| Total Bet Amount, Lifetime* | Total bet amount, lifetime | Games | 1 Month, 2 Weeks, 3 Months |
| Total Coins Purchased, Lifetime* | Total coins purchased, lifetime | Payments | Lifetime |
| Total Payment Amount, Lifetime* | Total payment amount, lifetime | Payments | 1 Month, 2 Weeks, 3 Months, 1 Year |
| Total Points Collected, Lifetime* | Total points collected, lifetime | Points and Ranking | Lifetime |
| Total Promotion Amount, Lifetime* | Total promotion amount, lifetime | Promotions | 1 Month, 2 Weeks, 3 Months |
| Total Session Duration, Lifetime* | Total session duration, lifetime | Games | 1 Month, 2 Weeks |
| Total Win Amount, Lifetime* | Total win amount, lifetime | Games | 1 Month |
| Web Bet Amount, Lifetime* | Web bet amount, lifetime | Games | 1 Month |
| Web Payment Amount, Lifetime* | Web payment amount, lifetime | Payments | 1 Month |
| Win Ratio, Lifetime | Win ratio, lifetime | Internal Tables | 1 Month |
| Xp Points, Lifetime | Xp points, lifetime | Games | Lifetime |
| Favorite Item Category | Favorite item category | Internal Tables | Lifetime |
| Favorite Item Name | Favorite item name | Internal Tables | Lifetime |
| First Payment Amount, Lifetime | First payment amount, lifetime | Internal Tables | Lifetime |
| Last Payment Amount, Lifetime | Last payment amount, lifetime | Payments | Lifetime |
| Attribute Name | Description | Source Table | Snapshot Periods |
|---|---|---|---|
| Days Since Last Login | Days since last login | Customers | Lifetime |
| Last Login Date | Last login date | Customers | Lifetime |
| Days Since First Activity | Days since first activity | Internal Tables | Lifetime |
| Days Since First Game | Days since first game | Internal Tables | Lifetime |
| Days Since First Payment | Days since first payment | Internal Tables | Lifetime |
| Days Since Last Activity | Days since last activity | Internal Tables | Lifetime |
| Days Since Last Game | Days since last game | Internal Tables | Lifetime |
| Days Since Last Payment | Days since last payment | Internal Tables | Lifetime |
| Days Since Last Reactivation | Days since last reactivation | Internal Tables | Lifetime |
| First Game Date | First game date | Internal Tables | Lifetime |
| First Payment Date | First payment date | Internal Tables | Lifetime |
| First Promotion Date | First promotion date | Internal Tables | Lifetime |
| Last Activity Date | Last activity date | Internal Tables | Lifetime |
| Last Game Date | Last game date | Games | Lifetime |
| Last Payment Date | Last payment date | Payments | Lifetime |
| Last Promotion Date | Last promotion date | Promotions | Lifetime |
| Time Since First Game | Time since first game | Games | Lifetime |
| Time Since First Payment | Time since first payment | Payments | 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 journey with your game, enabling tailored retention and engagement strategies. For example:
- A company uses the Lifecycle Stage attribute to identify high-risk "Active Gamers" (spenders who haven't paid recently) and targets them with special offers on virtual currency to encourage them to become "Active Spenders" again.
| Attribute Name | Description | Source Table | Snapshot Periods |
|---|---|---|---|
| Days Since Registration | Days since registration | Customers | Lifetime |
| Lifecycle Stage | Lifecycle stage | Internal Tables | Lifetime |
| Months Since Registration | Months since registration | Customers | Lifetime |
| Bet Percentile By Lcs | Bet percentile by lcs | Internal Tables | 1 Month, 2 Weeks, 3 Months |
| Days In Churn Non Spender, Lifetime | Days in churn non spender, lifetime | Internal Tables | Lifetime |
| Days In Churn Spender, Lifetime | Days in churn spender, lifetime | Internal Tables | Lifetime |
| Days In Reactivated Spender, Lifetime | Days in reactivated spender, lifetime | Internal Tables | Lifetime |
| Days Since Lifecycle Stage Change | Days since lifecycle stage change | Internal Tables | Lifetime |
| Lifecyclestage Before Churn Spender | Lifecyclestage before churn spender | Internal Tables | Lifetime |
| Payment Percentile By Lcs | Payment percentile by lcs | Internal Tables | 2 Weeks, 3 Months |
| Previous Lifecycle Stage | Previous lifecycle stage | Internal Tables | Lifetime |
| Promotion Percentile By Lcs | Promotion percentile by lcs | Internal Tables | 1 Month, 2 Weeks, 3 Months |
| Reactivation Action | Reactivation action | Internal Tables | Lifetime |
| Time Since Last Activity Active | Time since last activity active | Internal Tables | Lifetime |
| Time Since Last Activity Churn Ns | Time since last activity churn ns | Internal Tables | Lifetime |
| Time Since Last Activity Churn S | Time since last activity churn s | Internal Tables | Lifetime |
| Time Since Last Payment Active G | Time since last payment active g | Internal Tables | Lifetime |
| Time Since Last Payment Active S | Time since last payment active s | Internal Tables | Lifetime |
| Time Since Last Payment Churn S | Time since last payment churn s | Internal Tables | Lifetime |
| Time Since Registration | Time since registration | Customers | Lifetime |
| Time Since Registration Ns | Time since registration ns | Internal Tables | Lifetime |
Predictive Model Attributes
Predictive model attributes forecast player behaviors, helping you prioritize retention and conversion efforts for maximum impact. For example:
- A company uses the CONVERSION_PROBABILITY_SCORE to identify non-spending players who are most likely to make their first purchase, then targets them with a compelling starter-pack offer.
| 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 |
Product Attributes – Purchase History
Product attributes detail players’ purchasing preferences, allowing for tailored promotions based on their favorite items and offers. For example:
- A gaming company uses the ITEM_CATEGORY attribute to identify players who frequently purchase "power-up" items and sends them a special offer for a bundle of new, high-value power-ups.
| Attribute Name | Description | Source Table |
|---|---|---|
| Item Category | Item Category from Items Catalog | Product History |
| Item Name | Item Name from Items Catalog | Product History |
| Promotion Category | Promotion Category from Promotions Catalog | Product History |
| Promotion Type | Promotion Type from Promotions Catalog | Product History |
Out-of-the-box Campaign KPIs
Out-of-the-box (OOTB) Campaign KPIs measure the success of your game’s marketing campaigns by comparing the performance of targeted player groups against a control group. These metrics help you evaluate how campaigns drive engagement and spending, enabling data-driven optimization.
- Number of Activity Days: Counts the days a player was active in the game, showing a campaign's impact on engagement.
- Number of Payments: Tracks the total number of in-app purchases, indicating a campaign's success in driving monetization.
- Total Bet Amount: Measures the total amount of virtual currency wagered, reflecting a campaign's influence on gameplay depth.
- Total Payment Amount: Sums the total real-money value of all purchases, directly measuring a campaign's revenue impact.
Understanding Your Players: Grouping and Predicting Behavior (Segmentation Model)
To help you connect with your players in the best way, we organize them into groups based on their actions—like whether they’ve ever made a purchase, how often they play, or when they were last active. This process is called Segmentation. We also use these groups to predict what players might do next, like if they are likely to make their first purchase or stop playing. Let’s break it down into Player Groups and Behavior Predictions.
Player Groups: Organizing Players by Their Journey
Imagine you’re managing a vibrant online game. You’d want to group your players based on whether they're new, if they spend money, or if they've taken a break. We do the same with your players, organizing them into groups based on where they are in their journey with your game. We call these groups Lifecycle Stages (LCS), and we look at different details for each stage to understand them better.
Here’s how we group players at each stage of their journey:
1. New Non-Spenders
These are new players who registered in the last two weeks but have not made a purchase yet. We group them by their registration date and recent activity.
| Segmentation Layer | Details |
|---|---|
| Time Since Registration | 1 Day, 2 to 7 Days, Over 7 Days |
| Time Since Last Activity | 1 Day, 2 to 7 Days, Over 7 Days |
| Number of Activity Days | 1 Day, 2 to 7 Days, Over 7 Days |
Example: A player who registered yesterday and was last active on the same day could receive a push notification: "Your adventure awaits! Log back in for a special welcome gift of 100 free coins."
2. Active Non-Spenders
These are established players (registered over 14 days ago) who have played in the last 14 days but have never made a purchase. We group them by their activity levels and time with the game.
| Segmentation Layer | Details |
|---|---|
| Time Since Registration | Up to 1 Month, 1 to 3 Months, 3 to 6 Months, 6 to 12 Months, Over a Year |
| Time Since Last Activity | 1 Day, 2 to 7 Days, Over 7 Days |
| Frequency Last 3 Months | 1 Day, 2 to 7 Days, Over 7 Days |
Example: A highly engaged non-spender who plays almost daily could be targeted with a one-time "First Purchase Bonus" offering double the value on a popular starter pack.
3. Churn Non-Spenders
These are players who have never made a purchase and have been inactive for more than 14 days. We group them by how long they've been inactive and their previous engagement levels.
| Segmentation Layer | Details |
|---|---|
| Time Since Registration | Up to 1 Month, 1 to 3 Months, 3 to 6 Months, 6 to 12 Months, Over a Year |
| Time Since Last Activity | Up to 1 Month, 1 to 3 Months, Over 3 Months |
| Number of Activity Days | 1 Day, 2 to 7 Days, Over 7 Days |
Example: A player who was previously active for over 7 days but hasn't logged in for a month might receive an email: "We miss you! A new quest has begun. Here are 500 free coins to get you back in the action."
4. New Spenders
These are players who made their very first purchase within the last 14 days. We group them by their purchase behavior and recent activity to encourage their next purchase.
| Segmentation Layer | Details |
|---|---|
| Time Since First Payment | 1 Day, 2 to 7 Days, Over 7 Days |
| Time Since Last Activity | 1 Day, 2 to 7 Days, Over 7 Days |
| Number of Payments | 1 Payment, 2 Payments, 3 Payments or More |
| Payment Percentile | Top 10 Percent Payment Amount, 10 to 50 Percent Payment Amount, Bottom 50 Percent Payment Amount |
Example: A new spender who made one small purchase 3 days ago could receive an in-app message showcasing a limited-time bundle, encouraging them to make a second, higher-value purchase.
5. Active Spenders
These are valuable players who have made a purchase within the last 30 days. We group them by their spending habits and activity frequency to maintain their engagement and loyalty.
| Segmentation Layer | Details |
|---|---|
| Time Since Last Activity | 1 Day, 2 to 7 Days, 8 to 14 Days, Over 14 Days |
| Time Since Last Payment | 1 Day, 2 to 7 Days, 8 to 14 Days, Over 14 Days |
| Frequency Last 3 Months | 1 Day, 2 to 7 Days, Over 7 Days |
| Payment Percentile | Top 10 Percent Payment Amount, 10 to 50 Percent Payment Amount, Bottom 50 Percent Payment Amount |
Example: An active spender in the top 10% for payments could be given early access to a new feature or an exclusive VIP virtual item to reward their loyalty and encourage continued spending.
6. Active Gamers
These are players who have spent money in the past but not within the last 30 days; however, they have been active in the game recently. The goal is to re-engage them as spenders.
| Segmentation Layer | Details |
|---|---|
| Time Since Last Activity | 1 Day, 2 to 7 Days, 8 to 14 Days, Over 14 Days |
| Time Since Last Payment | 1 to 3 Months, 3 to 6 Months, 6 to 12 Months, Over a Year |
| Frequency Last 3 Months | 1 Day, 2 to 7 Days, Over 7 Days |
| Payment Percentile | Top 10 Percent Payment Amount, 10 to 50 Percent Payment Amount, Bottom 50 Percent Payment Amount |
Example: An active gamer who hasn't made a purchase in two months could be targeted with an offer specifically related to their gameplay, such as "Running low on energy? Refill for 50% off today only!"
7. Churn Spenders
These are valuable players who have spent money in the past but have not had any activity (login or play) in the last 30 days. The goal is to reactivate them.
| Segmentation Layer | Details |
|---|---|
| Time Since Last Activity | 1 to 3 Months, 3 to 6 Months, Over 6 Months |
| Time Since Last Payment | 1 to 3 Months, 3 to 6 Months, Over 6 Months |
| Number of Activity Days | 1 Day, 2 to 7 Days, Over 7 Days |
| Payment Percentile | Top 10 Percent Payment Amount, 10 to 50 Percent Payment Amount, Bottom 50 Percent Payment Amount |
Example: A high-value churned spender could receive an email highlighting a major new game update or event, coupled with a significant "Welcome Back" bonus on their next purchase.
8. Reactivated Spenders
These are previously churned spenders who have returned and shown activity in the last 14 days. We group them by their recent activity to solidify their return and encourage them to become Active Spenders.
| Segmentation Layer | Details |
|---|---|
| Time Since Last Activity | 1 Day, 2 to 7 Days, Over 7 Days |
| Number of Activity Days Last 2 Weeks | 1 Day, 2 to 7 Days, Over 7 Days |
| Number of Payments Last 2 Weeks | 1 Payment, 2 Payments or More, No Recent Payments |
| Payment Percentile | Top 10 Percent Payment Amount, 10 to 50 Percent Payment Amount, Bottom 50 Percent Payment Amount |
Example: A reactivated spender who has logged in several times but hasn't made a purchase yet could receive a personalized offer on an item they've previously purchased to make their first post-churn transaction seamless.
Please note that Non-Spenders are removed after 1 year of inactivity, and Spenders are removed after 2 years of inactivity.
Why This Matters for the Social Gaming Vertical
By grouping your players and predicting their behavior, you can create personalized experiences that make them feel valued. Whether it’s offering a welcome bonus to a new player, rewarding a loyal spender with exclusive content, 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 gaming platform.
Want to learn more? Check out this guide: The Optimove Model.