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5. Segmentation & Risk
Final section: where's the leak, and who's at risk right now?
Plan tier explains a 24-point spread in churn rate; region and industry barely register at under 3 points each the Starter tier is the real story. I closed the project by building a ranked watchlist: 1,948 currently active accounts matching the profile of customers who already churned, worth $3.1M in at-risk MRR.
Full breakdown, SQL, and the Power BI dashboard: github.com/MZT49/leaky-bucket-saas-churn
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Hello all!
Assembling a few sample performance and analytics dashboards, using randomized dummy data to keep client info private, to refine how reporting gets presented to design and brand partners.
When working on brand, web, or UI/UX projects, what metrics or visual insights do you actually find valuable in a report? Are you looking to see how visual changes impact user engagement and conversion paths, or do you prefer high-level ROI summaries to show clients the impact of your work?
Always open to connecting with designers, agencies, and growth strategists looking to partner on the performance and reporting side of client accounts.
I Created Microsoft Power BI Dashboard By using many of the Tools
🚀 Data Modelling
🧠 Data Visualization
🚀 Group By
🧠 Data Cleaning
AutoML Forge is an end-to-end AutoML platform designed to simplify the machine learning workflow by automating key stages from data preparation to model evaluation.
The platform allows users to upload their datasets and build machine learning models without manually handling every step of the traditional ML pipeline.
Key Features
Automated data preprocessing and cleaning
Automatic feature handling and transformation
Classification and regression workflows
Anomaly detection
Model comparison and evaluation
Automated model selection
Hyperparameter optimization
Performance metrics and visualizations
Model prediction and inference
Easy-to-use interactive interface
Tech Stack
Python · PyCaret · FastAI · Scikit-learn · Pandas · NumPy · Streamlit
The project focuses on making machine learning more accessible while reducing repetitive experimentation and development time. It demonstrates practical experience in machine learning automation, model evaluation, data preprocessing, and building AI-powered applications.
Role: AI/ML Developer
Project Type: Machine Learning / AutoML / Data Science
Impressive to see automated data preprocessing and cleaning built into AutoML Forge - eliminating that tedious step speeds up experimentation dramatically. The integrated model comparison and evaluation visualizations make it easy to spot the best performer quickly.