Our ML app uses NLP to analyze e-commerce reviews and provide customers with a succinct overview, including top words, most positive / negative reviews, and more! Our Python web scrapers gather customer feedback from major e-commernce platforms, following which we utilize the Cohere toolkit to perform sentiment analysis.
Our inspiration for this project came from the realization that customers often spend hours searching through countless reviews before making a purchase. We wanted to create a tool that could automate this process and present the most useful information in an easy-to-understand format. We researched various machine-learning techniques and settled on using natural language processing algorithms to analyze customer reviews.
Stretch goals:
- Improving the accuracy and efficiency of our sentiment analysis algorithms
- Expanding the scope of our web-scraping capabilities to cover a wider range of e-commerce websites
- Incorporating more advanced natural language processing techniques, such as topic modelling and entity recognition, to provide users with even more valuable insights from customer reviews
We also aim to explore the possibility of integrating our app with popular e-commerce platforms, enabling users to access our insights directly from their favourite online stores. This will further streamline the product research process, making it even easier and more convenient for users to make informed purchase decisions.