CashBharo: Your
Real-World
Cashback &
Affiliate
Data Playground
CashBharo is a ready-to-use synthetic dataset that mimics the experience of a real cashback and affiliate marketing platform. Ideal for campaign optimization, referral tracking, reward analytics, and user engagement analysis.
Overview
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.
Full Cashback Lifecycle
Simulates a complete cashback and affiliate experience, including user profiles, merchant partnerships, offers, transactions, referrals, wallets, and payouts.
Built for Development & Testing
Excellent for building and testing campaign optimization models, offer recommendation systems, referral tracking engines, and fraud detection pipelines.
Backend Feature Testing
Useful for developers working on transaction tracking, payment processing, referral program functionality, and wallet integration flows.
Rich Transaction Data
Supports use cases in user engagement analysis, offer redemption modeling, promotional campaign performance, and user segmentation studies.
Analytics & Research
Suitable for SQL training, time-series analysis, cohort analysis, ETL development, and A/B testing simulations of promotional strategies.
How it Works
AI-Generated & Fully Synthetic
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 — with zero real financial data.
Realistic Simulation with Privacy
It models cashback transactions, referral bonuses, wallet management, and promotional campaigns — without any real financial information or user identities, ensuring ethical use across all fintech applications.
High-Quality & Safe for Use
Built for developers and analysts to test affiliate management systems, reward analytics, and wallet integration features in a fully synthetic environment — 100% privacy-compliant and ready to use.
Dataset Schema
A comprehensive relational model representing a modern cashback and affiliate marketing platform engineered for deep analysis and complex querying.
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.
- CSV
- JSON
- Excel
- MySQL
- PostgreSQL
- SQL Server
- Snowflake