Zacchaeus Olabode's Work | ContraWork by Zacchaeus Olabode
Zacchaeus Olabode

Zacchaeus Olabode

AI Web Developer | ML Automation & Business Analytics

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Cover image for Customer Churn Prediction & Retention
Customer Churn Prediction & Retention Analytics: Helps subscription-based businesses lower their attrition rates, I developed a "Churn Warning System." The model analyzes user engagement signals to flag customers who are showing signs of leaving before they actually cancel. This gives the business a proactive window to reach out with retention offers and save the account. Key Result: Identified the top 3 drivers of customer loss, allowing for data-driven retention strategies that protect long-term revenue.
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Cover image for Automated Data Extraction & Invoice
Automated Data Extraction & Invoice Processing Built a custom automation pipeline to eliminate the "manual data entry" bottleneck in accounts payable. Using OCR (Optical Character Recognition) technology, the system "reads" scanned invoices and PDFs, extracts key financial data, and formats it into a structured database or Excel sheet automatically. Key Result: Replaced hours of manual typing with a 95% faster automated process, virtually eliminating human entry errors.
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Cover image for Retail Inventory & Sales Forecasting
Retail Inventory & Sales Forecasting Engine: This project involved building a predictive engine designed to solve the "stockout vs. overstock" issue. Using time-series analysis on past sales cycles, seasonality, and market trends, I created a model that predicts future inventory needs with high precision. It provides business owners with a clear "buying guide" for the upcoming quarter. Key Result: Reduced potential waste from overstocking while ensuring top-selling items never go out of stock, optimizing cash flow management.
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Cover image for Automated lead scoring :
Developed an
Automated lead scoring : Developed an intelligent lead-ranking system that automatically identifies high-value prospects for sales teams. By analyzing historical conversion data, the model assigns a "score" to every new inquiry. This allows businesses to stop wasting time on "window shoppers" and focus their energy on the leads most likely to close. Key Result: Streamlinimg the sales funnel by prioritizing high-intent leads, leading to a increase in conversion efficiency.
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