- All e-commerce websites provides FAQs about specific products under the product description.
- Those 8-10 FAQ's sometimes doesn't answer all queries about the products or give very less information related to that product due to which buyer/user doesn't get satisfied.
- Else they provide us with millions of QNA and the website then tends to lose the users
- Answers unknown questions related to that product
- Answers right away instead of searching from a pile of thousands of questions
- Web scraps the entire product page and answers the questions relatively
- Even the rarest of the rarest questions are answered using AI and machine learning
- It is pretrained on products specifications
- Our solution uses an advanced Artificial Intelligence model GPT-2 to answer the questions and generate the output text
- Not many e-commerce website uses conversational AI as an alternative to FAQs
- Unlike other hardcoded chatbots our chatbot is trained using machine learning aspects
- We eliminate the time period of a user asking the question and the seller answering it within 2-3 days
- The AI chatbot seeks to answer rarest of the rarest question
- Our solution for most of the time answers the question related to the question itself so that we don't lose customer retention due to unsatisfying results
- It will be an extension and not an end product so that many e-commerce websites can use this similar approach to solve this problem
- In the future, the product will use Image Recognition so that after identifying the features it can search the feature of the product web scrap and answer it accordingly
- Expanding use cases with new features and capabilities
- Creating engaging experiences beyond simple QNAs
- We used Microsoft Machine Learning Studio to script and train the machine learning model using GPT-3
- Along with that we used Microsoft Azures Datastore to access the data stored in the containers
- Used Microsoft Azure Devops for integration of model and web application and used API calls using REST API with the help of Microsoft Azure
- Used Microsoft Cloud Server to deploy the product online
