Mobile Commerce AI Chatbot using ChatGPT and Llama 3

Updated 9 May 2024

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Introducing the revolutionary Mobile Commerce AI Chatbot using ChatGPT and Llama 3, a virtual assistant for the e-commerce store’s mobile app.

The AI Chatbot is built with the latest Llama 3 Large Language Model.

Using a Mobile app AI chatbot helps your customers interact with the virtual assistant on their mobile phones for their related queries.

Customers can ask any queries to the ChatBot and it provides answers using NLP.

The AI Chatbot uses the Open Source LLM and Vector database.

It also supports multi-lingual language where the customers can ask queries to the Chatbot in multiple languages and get responses in the same language.

Introduction of Llama 3

It’s the most advanced Large Language Model made by Facebook. It can recognize the input and generate the matching data.

Llama 3 is capable and comparable to GPT 4 and Gemini. The best part is that it is an Open Source. You can host it anywhere for free.

Also, the chatbot can respond in natural language to the customer’s queries.

It has a huge number of parameters, which means that the AI model is more complex and powerful.

So, Llama 3 allows more interactions. It can handle more complex inputs than older versions, like Llama 2 or 1.

AI Chatbot Using ChatGPT and Llama 3 – Magento 2 Mobile App

Let’s see how we have incorporated the AI Chatbot that uses ChatGPT and Llama 3 with some use cases in the Magento 2 mobile app.

Firstly, the user will interact with a Chatbot icon on the homepage, where they can start the chat with the Magento 2 AI Chatbot.

Once clicking on the Chatbot icon, a page will open and the customer will find a message “Welcome to Chatbot” as shown in the snapshot below.

Let’s check and ask the AI chatbot some questions and see how it responds to them –

Product Based Responses

For example, the users can ask the mobile app’s AI Chatbot for a specific product available in the store.

Customers will get a quick NLP response with the specific product name in response to the question.

The users can also ask for the product page link and will get an accurate response.

You can ask about the customizable options for a product such as color, size, and more.

The customers can also ask for the price of a particular product to the AI Chatbot in the store.

The AI Chatbot quickly responds with the product price as you can see in the below image.

Attribute-Based Responses

If the customers ask for a particular product with its attributes, they can even get an accurate response to their queries.

In the below image, you can see the AI Chatbot quickly responded with a list of products with the particular attribute asked.

You can also ask for the other attributes of a particular product, and the AI chatbot will respond with the product along with the detailed attribute.

Multi-Lingual Support

Customers can ask queries to the AI Chatbot in multiple languages and they will receive the answer to their queries in the same language that they have requested.

You can check the same functionality of the AI Chatbot for the Magento 2 eCommerce store as well.

Industry Use Cases – eCommerce Hotel Chatbot

Booking Assistance :

Chatbot can help users search for and book hotel rooms as they provide real-time availability and rates.

Also, help with the hotel booking process.

Check-in and Check-out Assistance :

Chatbot can speed up the check-in and check-out processes by providing guests with essential info and collecting feedback after their stay.

Customer Support :

It can provide 24/7 customer support by quickly responding to all queries of the visiting customers.

Room Service :

Customers can use Chatbot to order room service like housekeeping, scheduled calls, etc.

Feedback and Surveys :

Hotel Commerce Chatbot can gather feedback from guests during or after their stay which helps hotels measure customer satisfaction.

That was about the Mobile Commerce AI Chatbot using ChatGpt and Llama 3.

For any queries or doubts drop us an email at [email protected] or raise a ticket at our HelpDesk system.

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