Problem

An oil manufacturing company was struggling to keep up with the demand for their products. They were experiencing a high volume of orders and needed a way to streamline their notification process to ensure timely delivery. The company was manually sending SMS notifications to customers about order status updates, but this was time-consuming and prone to errors.

The company needed a solution that would automate the notification process and provide accurate predictions of delivery times.

Solution

We built a complete machine learning pipeline for predictive SMS notifications. The pipeline consisted of several components, including data collection, data preprocessing, model training, and deployment.

We used historical order data to train our machine learning models to predict delivery times accurately. We also integrated the pipeline with the company's existing systems so that notifications could be sent automatically when an order status changed.

Impact

Reduced manual effort required for sending SMS notifications by X%
Improved accuracy of delivery time predictions by X%
Increase in customer satisfaction due to timely and accurate notifications

Team

Team Member #1 - Data Scientist
- Collected and preprocessed historical order data
- Built and trained machine learning models for predicting delivery times
Team Member #2 - Software Engineer
- Built the complete machine learning pipeline from data collection to deployment
- Integrated the pipeline with the company's existing systems for automated notifications

Automated Predictive SMS Notifications for Timely Delivery