Scope
Developed a scalable, no-code machine learning platform that enables marketers to profile and predict customer behavior through an intuitive graphical interface. Democratizes access to advanced ML capabilities without requiring programming skills.
Technology
- Platform: Web-based GUI for ML workflow orchestration, built on AWS infrastructure
- Capabilities: Customer profiling, behavior prediction, user modeling
- Scale: Designed for large-scale marketing data and operations
- User Experience: Point-and-click interface eliminating coding requirements
Key Innovation
Created a production-grade platform that bridges the gap between complex machine learning algorithms and business users, enabling marketing teams to leverage advanced customer analytics without technical expertise. The system handles end-to-end ML workflows from data ingestion to prediction through visual configuration.
Publication & Demo
- UMAP 2019: Zero-Coding UMAP in Marketing: A Scalable Platform for Profiling and Predicting Customer Behavior by Just Clicking on the Screen [Paper] [Poster] [Video]
Impacts
- Delivered the product feature in 3 months with a 5-person team. As an add-on feature of the enterprise SaaS, the system has been used by dozens of enterprise clients across Asia, Europe, and the Americas, where I took a pivotal role for stakeholder communication, user onboarding, and feature improvement.
- Demonstrated at the academic conference (UMAP 2019), showcasing how machine learning can be made accessible to non-technical users while maintaining scalability and sophistication in customer behavior modeling.
Author: Takuya Kitazawa
I am a product builder, mentor, and advocate for sustainable technology development with a decade of experience in AI/ML products, data systems, and digital transformation. Based in Canada and originally from Japan, I have lived and worked globally, including part-time residence in Malawi, Africa. Visit my portfolio to learn more about my work, or reach out to me at [email protected].