Cashback Platform Development & Research for Customer Rewards and Retail Success
Industry
Duration
Team
Technologies
Client Overview
ZipZero is a cashback app that allows users to collect funds from purchases to pay monthly household bills. Users earn rewards by sharing their shopping receipts or online shopping details. The platform rewards users for every purchase, with special premium offers for even more savings. The application, leveraging aggregated consumer data on their shopping habits, serves as a valuable source of information for retail networks, enabling them to effectively steer future marketing action based on data analysis. Zipzero developed a first-of-a-kind live first-party consumer data platform to give retailers access to every customer for attributable revenue-generating digital marketing. The app has been on the UK market for 4 years and is used by hundreds of thousands of users daily.
Client Needs
Technological Roadmap for MVP
Robust Transaction Processing System
Easy-to-use Administraion Panel
Machine Learning Solutions
Product Recognition System
User-Friendly Mobile Application
Scalable Microservices Architecture
Data Pipeline and Warehouse
ZipZero required a robust system capable of processing thousands of transactions daily, along with an easy-to-use mobile application and an administration panel for efficient system management. As our collaboration on the ZipZero app progressed, our team developed an algorithm for recognizing products from various store networks (merchants). We are responsible for creating our database of products and EANs for the application, including testing and optimizing product recognition algorithm configurations. Additionally, we implemented machine-learning solutions for fraud detection and data insights.
Services Provided
Technical Roadmap & Architecture Design: Planning and designing the MVP architecture.
Microservices Architecture Design: Implementing a scalable architecture was pivotal for enabling seamless collaboration among independent teams, ensuring agility and scalability as the platform grows.
Database & Data Pipeline Design: Crafting a system capable of efficiently storing millions of transactions and products from various stores across the United Kingdom.
Integration with External Networks: Connecting the platform with external affiliate networks.
Mobile Application Development: Building user-friendly mobile apps for Android.
Administration Panel Development: Creating a comprehensive panel for system management.
Product Recognition System: Development of a system capable of recognizing product abbreviations from receipts and translating them into their full names, along with extracting EAN codes from various.
Custom OCR: Creating a tool for proper conversion of receipt images into text.
Fraud Protection System: Implementing machine learning-based solutions for fraud detection.
Scope of Work
During planning and analysis sessions for domain and architecture, our team focuses on understanding and devising the best IT solutions and enhancements that can be implemented into the application.
Developing MVP technical roadmap and initial architecture.
Implementing the system architecture based on a microservices architecture to ensure scalability and the ability for independent teams of programmers to work on multiple parts of the system.
Designing a database, warehouse, and data pipeline that has the capacity to store millions of transactions, products, and purchases.
Develop tailored algorithms for product and merchant recognition, ensuring flexibility and modifiability, along with the creation and maintenance of a comprehensive database.
Creating user-friendly mobile applications.
Integrating with external affiliate networks.
Developing complex administration panel for system management.
Implementing fraud and abuse protection system using machine learning solutions.
Technologies Used
Java: Chosen for its reliability and scalability, Java serves as the backbone for the backend development of ZipZero's cashback app, ensuring robust transaction processing and seamless integration with various systems.
Spring: Leveraged to build a resilient and scalable application framework, Spring provides the necessary tools and libraries for developing complex backend functionalities, enabling ZipZero to handle thousands of transactions daily with ease.
Kubernetes: Employed for container orchestration, Kubernetes ensures efficient resource management and scalability for ZipZero's microservices architecture, allowing for seamless deployment and scaling of application components as demand fluctuates.
Redis: Utilized as an in-memory data store, Redis enhances the performance and responsiveness of ZipZero's cashback app by caching frequently accessed data, such as user preferences and session information, resulting in faster response times and improved user experience.
Elasticsearch: Integrated for its powerful search capabilities, Elasticsearch enables ZipZero to implement advanced search functionality within the app, allowing users to quickly find relevant products and offers based on their preferences and shopping history.
Angular: Chosen for its robustness and flexibility, Angular powers the frontend user interface of ZipZero's cashback app, providing a dynamic and interactive experience for users across various devices, while ensuring seamless navigation and intuitive user interactions.
Android: Used for developing the user-friendly mobile application of ZipZero, Android ensures compatibility with a wide range of devices, allowing users to conveniently access their cashback rewards and manage their accounts on the go, enhancing overall user engagement and satisfaction.
PostgreSql: Adopted as the relational database management system, PostgreSQL provides a robust and scalable solution for storing and managing transactional data, user profiles, and other critical information within ZipZero's cashback platform, ensuring data integrity and reliability.
Snowflake: Integrated Snowflake for cloud-based data warehousing, enabling scalable and efficient storage and analysis of data for business intelligence and analytics purposes.
Development Process
The beginning of the project started with hours of planning and analyzing sessions on the domain and architecture of the new system we were about to create. The main objectives of the system were to process thousands of transactions daily, an easy-to-use and transparent mobile application, and an administration panel that allows easy management of the entire system. With the growth of the platform, we introduced machine-learning solutions for fraud detection and a data insights panel based on Snowflake.
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