Project IV: Customer Support Bot using Azure

We’ll build a chatbot Customer Support Bot using Azure that handles common customer queries like:

• Checking order status

• Providing information about return and refund policies

• Answering product-related questions

  
  
  
  

  

  Customer Support Bot using Azure

  
  
  
  

We’ll use Microsoft Bot Framework or Power Virtual Agents along with Microsoft Azure for hosting and deployment.

Step 1: Plan the Customer Support Bot using Azure Bot’s Functionality

Key Features:

1. Order Tracking: Users can check the status of their order by providing an order number.

2. Return/Refund Policies: The bot explains the return and refund policies based on user queries.

3. Product Information: Users can ask questions about product details.

4. Dynamic Responses with Generative AI: Personalized responses based on user inputs.

   
   

Step 2: Set Up the Tools

Tools We’ll Use:

1. Microsoft Bot Framework SDK (for chatbot development)

2. Azure Bot Service (for deployment)

3. QnA Maker or Azure Cognitive Services (to create a knowledge base for FAQs)

4. Frontend Integration: JavaScript or React for embedding the bot on your website

   
   
   
   

Step 3: Develop the Chatbot

A. Create the Knowledge Base

Use Azure QnA Maker or Power Virtual Agents to set up your bot’s knowledge base:

• Add FAQs for return/refund policies and product-related questions.

• Train the bot to answer queries dynamically.

B. Code the Chatbot Logic

If using the Microsoft Bot Framework SDK, follow these steps:

1. Initialize a Bot Project

2. Install the Bot Framework SDK:

bash
npm install -g yo generator-botbuilder yo botbuilder

• Add Intent Recognition with LUIS (Language Understanding)

• 
  

  • Create intents for:

    • Order tracking

    • Refund queries

    • Product details

• Handle Dynamic Inputs Use Azure Cognitive Services for extracting entities like Order Number or Product Name.

  
  

• Integrate Generative AI Add OpenAI or Azure OpenAI for generating personalized responses.

javascript
const { Configuration, OpenAIApi } = require("openai"); const configuration = new Configuration({ apiKey: process.env.OPENAI_API_KEY, }); 
const openai = new OpenAIApi(configuration); async function generateResponse(userQuery) 
{ 
const response = await openai.createCompletion({ model: "text-davinci-003", prompt: `Respond to customer query: ${userQuery}`, max_tokens: 100, }); 
return response.data.choices[0].text.trim(); 
}

Step 4: Deploy the Chatbot

A. Host the Bot on Azure

1. Create an Azure Bot Service instance.

2. Deploy your bot using Azure Web App or Azure Functions.

   
   

B. Integrate with Your Website

Use the Direct Line API to connect your bot to a web frontend. Embed the bot on your website with a chat widget.

Example:

html
<script> window.WebChat.renderWebChat({ directLine: window.WebChat.createDirectLine({ secret: 'YOUR_DIRECT_LINE_SECRET' }), userID: 'user1', username: 'Customer', locale: 'en-US' }, document.getElementById('webchat'));
</script> 
<div id="webchat" style="height: 400px; width: 100%;"></div>

Step 5: Test the Chatbot

• Test on the Azure Bot Service Emulator for end-to-end functionality.

• Check edge cases like invalid order numbers or unsupported queries.

  
  

Step 6: Scale and Improve

• Analytics: Use Azure Application Insights to track bot performance.

• Add Features: Expand the bot to handle multilingual queries or integrate it with your CRM.

  
  

A fully functional chatbot embedded into your website, ready to streamline customer support and enhance user experience.