CashBharo is a synthetic dataset built to replicate how a cashback and affiliate marketing platform works. It captures realistic interactions like users browsing cashback deals, making purchases, referring friends, and engaging with promotions. Whether you're testing affiliate tracking systems, optimizing campaign performance, or analyzing customer engagement, CashBharo offers a privacy-safe playground full of rich, structured data.
It includes detailed mock data on users, merchants, transactions, offers, referrals, and payouts — making it perfect for building models around redemption behavior, user segmentation, and fraud detection. Developers and analysts can simulate real-world workflows like payment processing or referral tracking, while learners can dive into SQL, transformation logic, or campaign analysis with hands-on examples.
Highlights:
- Simulates a complete cashback and affiliate marketing platform with users, transactions, offers, and referrals.
- Perfect for building models for campaign optimization, user engagement analysis, and offer recommendations.
- Supports backend testing for transaction tracking, payment processing, and referral program functionality.
- Provides insights into promotional campaign performance, user segmentation, and offer redemption patterns.
- Great for SQL training, time-series analysis, cohort analysis, and A/B testing of promotional strategies.
The Cashbharo schema facilitates cashback, referral bonuses, and user transactions. It tracks user wallets, offers from merchants, cashback requests, and payment processing. The platform also allows users to earn cashback through offers and referrals, and manage their funds through various payment methods.
Key tables in the dataset include:
- Users: Stores user data (login, contact, role) linked to transactions and referrals.
- Wallets: Manages user wallet balances, cashback, and referral bonuses.
- Merchants: Represents merchants offering cashback deals with details like name and website.
- Offers: Contains cashback offer details, including percentage, dates, and status (active/expired).
- Transactions: Records cashback and referral transactions, including type, amount, status, and related offer.
- Referrals: Tracks user referrals, bonuses, status (pending/credited), and referral date.
- Payments: Stores user deposit payment details, including amount, method, status, and transaction reference.
- Cashback Requests: Tracks users' cashback withdrawal requests, including amount, status, and processing details.
- Notifications: Stores notifications about offers, payments, and account activities with read status.
- User Activity: Logs user actions (viewing offers, referrals, purchases, cashback withdrawals) to track engagement.
The CashBharo dataset was generated using AI-driven simulations to reflect a reward-based cashback and affiliate ecosystem. It models user interactions like offer redemptions, referrals, cashback accrual, wallet balances, and merchant partnerships. The data structure mirrors real-world promotional platforms where users earn rewards by transacting through partner deals. All data is entirely synthetic, containing no real financial information or user identities. It’s tailored for testing affiliate management systems, reward analytics, and wallet integration features in a secure and ethical development environment.
Built to simulate cashback platforms and affiliate behaviors, the CashBharo dataset is well-suited for financial modeling, reward calculations, and user activity tracking. It offers seamless integration into both developer and data science workflows with full compatibility across modern databases and cloud platforms.
- Available file formats: CSV, JSON, Excel
- Available databases: MySQL, PostgreSQL, SQL Server
- Cloud database access: Snowflake
