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

What Data Should You Send?

To unlock powerful segmentation, predictive insights, and personalized campaigns for your traders, 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, trading behaviors, and predictive scores—described in this article. The following data types are essential:

• Customers: Information about your traders, 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 traders.
• Assets: Details about the financial instruments available for trading, such as currency pairs or commodities, enabling promotions based on traders' preferences.
• Positions: Data on traders' trading activity, including invested amounts and leverage, which drives insights into trading patterns and engagement levels.

Properly preparing these data sets allows Optimove to deliver the actionable insights needed to engage New Traders, retain Active Traders, and reactivate Churned Traders 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 traders effectively. Below, each category of attributes is detailed with practical use cases and comprehensive tables.

Demographic Attributes

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

• A trading company uses the AGE attribute from the Customers table to segment traders into different age groups and tailor targeted educational content that increases engagement and retention.

 

Consent 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 traders’ financial and trading behaviors, providing insights for targeting high-value customers 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 traders through different phases of their relationship with your platform, enabling tailored retention and engagement strategies. For example:

• A company uses the Lifecycle Stage Before Churn attribute to analyze behavior patterns of previously valuable traders, enabling targeted reactivation campaigns with compelling offers to bring them back.

Predictive Model Attributes

Predictive model attributes forecast trader behaviors, helping you prioritize retention and conversion efforts for maximum impact. For example:

• A company uses the CHURN_PROBABILITY_SCORE attribute to prioritize high-risk Active traders for retention campaigns, like offering bonus leverage or educational webinars, to prevent churn.

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 – Purchase History

Product attributes detail traders' preferences for specific assets, allowing for tailored promotions and content based on their trading history. For example:

• The brokerage uses the ASSET_CATEGORY attribute to identify traders who prefer trading cryptocurrencies and sends them targeted analysis and news on that market, increasing trading volume.

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 trader groups against a control group. These metrics help you evaluate how campaigns drive engagement, deposits, and revenue, enabling data-driven optimization.

• Number of Activity Days: Counts days with trader activity (e.g., deposits or trades), showing campaign impact on engagement.
• Number of Deposits: Tracks deposit frequency, indicating campaign success in encouraging financial commitment.
• Total Volume: Measures the total invested amount, reflecting campaign influence on trading volume.
• Total Deposit Amount: Sums all deposits made by traders, reflecting campaign effectiveness in driving financial activity.
• Net Revenue: Calculates net revenue from trading activities, highlighting campaign profitability.

Understanding Your Traders: Grouping and Predicting Behavior (Segmentation Model)

To help you connect with your traders in the best way, we organize them into groups based on their actions—like how long it’s been since they last traded, how much they deposit, or their total trading volume. This process is called Segmentation. We also use these groups to predict what traders might do next, like whether they’ll keep trading or become inactive. Let’s break it down into two simple ideas: Trader Groups and Behavior Predictions.

Trader Groups: Organizing Traders by Their Journey

Imagine you’re running an exclusive trading club. You’d want to group your members based on whether they've ever deposited funds, how actively they trade, or how recently they last opened a position. We do the same with your traders, organizing them into groups based on where they are in their journey with your platform. We call these stages Lifecycle Stages (LCS), and we look at different details for each stage to understand them better.

Here’s how we group traders at each stage of their journey:

1. Non-Depositors: Traders Who Registered but Haven’t Deposited

These traders have signed up for your 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, 2 to 7 Days, 1 Week to 1 Month, 1 to 3 Months, More than 3 Months

Example: A trader who registered yesterday but hasn't deposited could receive a "Get Started Trading" email offering a guide to the platform to encourage their first deposit.

2. New: Just Started Depositing and Trading

These are traders who recently added money to their account and started trading. We group them by their trading volume, deposit activity, and time since their first deposit and last activity.

Segmentation Layer	Details
Volume Percentile Last 2 Weeks	Top 10 Percent Trade Amount, 10 to 50 Percent Trade Amount, Bottom 50 Percent Trade Amount
Deposit Activity Last 2 Weeks	2 or More 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 trader in the bottom 50% for trade volume might receive a push notification with a link to a webinar on basic trading strategies to build their confidence.

3. Active: Regular Traders

These are traders who regularly log in and trade on your platform. We group them by their recent activity, deposit and trading volume in the last 3 months, and how often they trade.

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 10 Days, Over 10 Days
Volume Percentile Last 3 Months	Top 10 Percent Trade Amount, 10 to 50 Percent Trade Amount, Bottom 50 Percent Trade Amount

Example: An active trader who is in the top 10% for deposits might get an email inviting them to an exclusive Q&A with a market analyst to reward their loyalty.

4. Churn: Stopped Trading

These are traders who haven’t logged in or traded in a while. We group them by how long it’s been since their last activity, their past deposit and trade volumes, 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
Volume Percentile	Top 10 Percent Trade Amount, 10 to 50 Percent Trade Amount, Bottom 50 Percent Trade Amount
LCS Before Churn	New, Active, Reactivated

Example: A churned trader who was previously in the top tier for deposits—and who hasn’t been active in two months—may receive a “Market Opportunities You're Missing” email with a bonus on their next deposit.

5. Reactivated: Came Back After a Break

These are traders who stopped trading for a while but recently returned. We group them by their recent activity, deposits, and trade volume since coming back.

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
Volume Percentile Last 2 Weeks	Top 10 Percent Trade Amount, 10 to 50 Percent Trade Amount, Bottom 50 Percent Trade Amount
Deposit Activity Last 2 Weeks	2 or More Deposits, 1 Deposit, No Recent Deposits

Example: A reactivated trader who made a deposit three days ago might get a push notification with a “Welcome Back” bonus to encourage their next trade.

6. Dormant: Inactive for a Long Time

These are traders who haven’t been active in a very long time, whether they’ve deposited before or just signed up. We group them by whether they have ever deposited.

Segmentation Layer	Details
Dormant Type	Depositor, Non-Depositor

Example: A dormant trader who previously deposited might get an email about a major market event, like an interest rate decision, with a special offer to get them trading again.

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 Forex Vertical

By grouping your traders and predicting their behavior, you can create personalized experiences that make them feel valued. Whether it’s offering a trading guide to a new customer, rewarding a loyal trader with exclusive market insights, or winning back someone who has been inactive, these tools help you connect with your traders in the right way at the right time—all through your platform.

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