Local taxi service providers

Overview

A local taxi provider had built a survey form just to understand the kinds of problems the customers facing in terms of their transportation. The business owner hired a data scientist to help them enable their decision making.

Challenge

The major challenge was that the data was manually input by the users, there was no effective way to track the sentiment per say as a few used one word, one liner or one paragraph to express their concerns.

Implementation

The data scientist firstly brought in APIs to bring in the data of the surveys conducted. The data was prepared to fit the requirements of the algorithm, meaning a grid search machine learning technique was used, where the selection becomes the first decision and parameters become secondary. This allowed the model to permutations and combinations to generate better accuracy.

Benefits Achieved

• Risk free process
• 16% increase in P&L
• Performance up by 70%