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ChatGPT Masterclass - AI Skills for Business Success

ChatGPT Masterclass - AI Skills for Business Success

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 ChatGPT Masterclass - AI Skills for Business Success ❔ Struggling to figure out how to use ChatGPT effectively for your business? ❔ Wasting time on repetitive tasks that AI could automate in seconds? ❔ Want a structured, step-by-step way to master AI and 10x your productivity? ✅ You’re in the right place. ChatGPT Masterclass AI Skills for Business Success is a structured, step-by-step guide to mastering AI for business—without fluff, confusion, or wasted time. This is not just another AI podcast. It’s a free masterclass designed to take you from total beginner to expert-level AI workflows with clear, actionable strategies you can apply immediately. Each episode follows a simple, effective structure 🎯 Goal of the episode – What you’ll achieve by the end 🛠 Practical tools and techniques – How to apply AI in your business 🚀 Real-world examples – See AI in action ✅ Action task for you – A small, practical step to apply immediately With frequent new episodes every second day, you’ll keep learning, improving, and applying AI to your work. What You’ll Learn in This Masterclass Season 1 – Getting Started with ChatGPT Learn the basics, from prompts to structuring responses effectively. Season 2 – Practical Applications for Everyday Business Tasks Use ChatGPT for emails, customer support, documentation, and content creation. Season 3 – Marketing with ChatGPT Master AI-powered content creation, SEO, and social media strategy. Season 4 – Sales and Customer Support with ChatGPT Automate sales, generate leads, and optimize customer interactions. Season 5 – Advanced Industry-Specific Applications Learn how AI is used in industries like retail, healthcare, education, and real estate. Season 6 – Custom GPTs – Building Tailored AI Assistants Discover how to create and train custom AI assistants for your needs. Season 7 – Advanced Prompt Chaining – Using GPT for Multi-Step Workflows Build AI-driven workflows to enhance automation and efficiency. Season 8 – AI + Human Collaboration – Mastering the Art of Working with AI Learn how to combine AI with human skills for better decision-making and creativity. Season 9 – The AI-Enhanced Entrepreneur – Leveraging AI to Scale a Business Automate, optimize, and grow your business with AI-powered strategies. Season 10 – AI and Productivity Mastery – Optimizing Workflows with AI Assistants Use AI to improve efficiency, automate tasks, and streamline workflows. This long-term masterclass is packed with 100+ episodes, designed to help you integrate AI into your business step by step. Start listening now and take action to stay ahead in the AI revolution. 🔊 Staying true to the topic, this podcast is created with AI-generated voice technology.
Episodios
  • Creating a Custom GPT – First Steps to Training an AI Assistant #S11E3

    Creating a Custom GPT – First Steps to Training an AI Assistant #S11E3
    Jun 13 2025
    This is season eleven, episode three. In this episode, we will walk through how to create a custom GPT for customer queries. You will learn how to set up a custom GPT using OpenAI’s tools, define its scope, structure its responses, and implement rules to ensure accuracy and professionalism. By the end of this episode, you will have a clear roadmap for setting up your AI assistant and preparing it to generate accurate email drafts, chat responses, and quotation replies. So far, we have collected and structured past customer inquiries and created clean, standardized responses. Now it is time to train a custom GPT to use this data effectively. A well-trained AI assistant can reduce response time, improve consistency, and scale customer support without losing quality. Let’s go step by step on how to create a custom GPT that understands your business and communicates effectively. Step One: Setting Up a Custom GPT Using OpenAI’s Platform To create a custom GPT, we will use OpenAI’s platform. OpenAI allows you to fine-tune an AI assistant by customizing its instructions, training it with additional context, and providing a structured knowledge base. To begin: Go to OpenAI’s GPT customization page. If you do not have an OpenAI account, create one first.Click on "Create a custom GPT". This will open an interface where you can define your AI assistant’s behavior.Choose a name and purpose for your AI. Make it clear that this GPT is meant for customer support, sales inquiries, and quotation requests. Step Two: Defining the Scope and Personality of Your Custom GPT A custom GPT needs clear guidelines on what it should and should not do. This helps ensure it generates responses that match your brand’s voice and style. In the GPT settings, define: What the AI should focus on: Example: "This AI is designed to assist customers by answering product-related questions, providing specifications, and generating price quotations."What the AI should avoid: Example: "Do not generate speculative answers. If unsure, ask for human review."The tone of communication: Example: "Use professional, friendly, and concise language." By setting these rules, your AI assistant will stay on-brand and provide consistent responses. Step Three: Feeding Structured Knowledge to Your Custom GPT Now that the GPT knows its role, we need to train it with the structured data we prepared in the last episode. OpenAI allows you to upload reference documents or connect the AI to a knowledge base that it can use when generating responses. Here is how to integrate structured data: Upload FAQ documents, customer support guidelines, and product sheets. These documents should contain accurate, verified information that the AI can use.Use structured data formats like JSON or CSV for product specifications. Example: json CopyEdit { "Product": "XYZ Model 2000", "Battery Life": "10 hours", "Weight": "1.2 kg", "Charging Time": "90 minutes" } This allows the AI to pull product details in a structured way when a customer asks for specifications. Define fallback responses. Example: If the AI does not have an answer, it should say: "I will need to check with our team to provide the most accurate response.""Can I confirm your requirements before providing a quotation?" By structuring information correctly, your AI assistant can respond faster and more accurately. Step Four: Testing and Refining AI Responses Once your custom GPT is set up, it is time to test its responses and fine-tune its accuracy. Ask sample customer questions and analyze the AI’s replies. Example: Question: What are the specifications of the XYZ Model 2000?AI Response: The XYZ Model 2000 has a battery life of 10 hours, a weight of 1.2 kg, and a charging time of 90 minutes. Check for accuracy and completeness. If responses are incorrect or vague, adjust the training data.Refine prompt engineering to improve quality. Example: Instead of: What is the price of XYZ Model 2000?Try: Provide a price for XYZ Model 2000, including available discounts and shipping details. Better prompts lead to better AI responses. Step Five: Setting Rules for Human Review Even with well-trained AI, some responses will still need human review. To prevent errors, set rules for when AI drafts should be reviewed before sending. Examples of human review triggers: High-value orders or custom quotations: If a price exceeds a certain amount, require manual approval.Unclear customer questions: If a question is vague, AI should flag it for clarification.Complaints or disputes: AI should not attempt to resolve complaints without human input. Having these AI-human collaboration rules ensures the AI remains an assistive tool rather than a fully automated system. Key Takeaways from This Episode A custom GPT can be created using OpenAI’s customization tools.Defining clear instructions helps control AI responses.Structured data, such as FAQ documents and product sheets, improves AI ...
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    5 m
  • Preparing Data – Collecting and Structuring Past Customer Replies #S11E2

    Preparing Data – Collecting and Structuring Past Customer Replies #S11E2
    Jun 12 2025
    This is season eleven, episode two. In this episode, we will focus on how to collect and structure past customer replies to train a custom GPT. You will learn how to gather historical email responses, identify common patterns, clean the data, and organize it into a structured format that an AI model can use. By the end of this episode, you will have a clear understanding of how to prepare your customer support data for automation. If you want your custom GPT to generate accurate and helpful responses, it needs a strong foundation of real-world data. AI learns best when it has examples to reference. If your business has been handling customer inquiries for a while, you already have valuable training material in the form of emails, chat logs, and past responses. Instead of starting from scratch, you can use this data to make your AI assistant more effective from the beginning. Let’s go through the step-by-step process of preparing this data for training a custom GPT. Step One: Collecting Past Customer Replies The first step is to gather all existing customer interactions. These could be: Emails from customers and your repliesLive chat logs from customer support systemsFrequently asked questions and answers from your websiteInternal documents with product explanations or troubleshooting guides To start, go through your email inbox and export past customer conversations. If you use a customer support system like Zendesk, Intercom, or HubSpot, download chat logs or support ticket responses. Look for conversations where the same types of questions appear repeatedly. Step Two: Identifying Common Questions and Patterns Once you have gathered the data, it is time to analyze and categorize the most frequent types of customer inquiries. Some common categories include: Product specifications – Customers asking for size, weight, features, compatibility, or technical details.Pricing and quotations – Requests for price estimates, bulk discounts, or payment terms.Product recommendations – Customers asking which product is best for a specific use case.Shipping and policies – Questions about delivery times, returns, and refunds.Troubleshooting and support – Requests for help with installation, setup, or fixing issues. Go through at least fifty past customer inquiries and group them into categories. You will start to see patterns in the way customers ask questions and how your business responds. This will help you structure your AI training data more effectively. Step Three: Cleaning and Standardizing Your Responses AI performs best when training data is clean and consistent. To make your responses useful for training, follow these steps: Remove any sensitive customer information like names, emails, or order numbers.Rephrase repetitive responses to maintain clarity. AI does not need identical responses copied multiple times.Ensure uniform tone and style so that all AI-generated replies feel professional and consistent with your brand.Simplify language where needed. AI should generate responses that are easy for customers to understand. For example, if your previous email replies vary in tone, like: One email says: "Thank you for reaching out! Our product has a battery life of ten hours and charges in ninety minutes."Another email says: "The battery lasts ten hours, and charging time is one and a half hours." Standardizing responses ensures that AI learns a clear and professional way to reply. You might rewrite both responses into one consistent format: Final training response: "Our product features a battery life of ten hours and fully charges in ninety minutes." Step Four: Structuring the Data for AI Training Once your responses are cleaned and categorized, they need to be formatted in a structured way that AI can understand. The best format depends on how you plan to use your custom GPT. One effective format is a question-answer pair system, such as: Customer Question: What are the dimensions of your product? AI Response: The dimensions of our product are 15 cm by 10 cm by 5 cm. Customer Question: Can I get a discount if I buy in bulk? AI Response: Yes, we offer discounts for bulk orders. Please contact our sales team for a custom quote. This structured format allows AI to match new customer queries with the correct response. For more complex use cases, you might store product information in a structured database, such as: Product Name: XYZ Model 2000 Battery Life: 10 hours Charging Time: 90 minutes Weight: 1.2 kg When a customer asks for details about this product, the AI pulls the information from the structured database rather than relying on pre-written answers. Step Five: Storing and Organizing Data for Future Updates Your custom GPT should always have access to up-to-date information. This means storing your training data in a centralized document or database that can be updated regularly. Here are a few ways to organize your data for long-term use: Spreadsheets – Use Google Sheets or Excel to store...
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    6 m
  • Why Automate Customer Queries with Custom GPTs #S11E1

    Why Automate Customer Queries with Custom GPTs #S11E1
    Jun 11 2025

    This is season eleven, episode one. In this episode, we will talk about why automating customer queries with custom GPTs can save time, improve efficiency, and enhance customer experience. You will learn how a custom GPT can generate email drafts, respond to chat questions, and assist with quotation requests. By the end of this episode, you will understand the benefits of using AI for customer communication and when human input is still needed.

    Many businesses spend hours each week responding to emails and customer inquiries. Questions about pricing, product specifications, and recommendations take up valuable time. Instead of answering the same questions manually, a custom GPT can draft responses based on previous email replies, product data, and structured knowledge. This does not mean removing human interaction. Instead, it allows your team to focus on more complex tasks while AI handles repetitive queries.

    ChatGPT can be trained to recognize patterns in customer questions. If a potential customer asks for specifications, the AI can generate an answer based on structured product data. If they request a price quote, the AI can pull the latest pricing information and format it into a professional email. If they need help choosing the right product, the AI can analyze customer needs and recommend the best option.

    There are three key reasons why businesses should consider automating customer replies. The first reason is consistency. A custom GPT ensures that every response is accurate, professional, and aligned with company guidelines. The second reason is efficiency. Instead of spending time writing individual replies, AI can generate drafts that only require minor human adjustments. The third reason is scalability. As your business grows, handling customer inquiries manually becomes overwhelming. AI allows your support system to scale without adding significant costs.

    Now let’s talk about when human input is still necessary. AI works best when responding to common and structured inquiries, but complex cases still need a human touch. A well-designed AI system should include escalation rules. If the AI detects uncertainty, it can flag the request for human review. This way, businesses get the best of both worlds. AI provides fast and accurate responses, while humans handle exceptions.

    Let’s summarize the key points from this episode. Automating customer queries with a custom GPT saves time, ensures consistency, and allows businesses to scale. AI can generate accurate email drafts, answer chat queries, and provide price quotes based on structured data. However, human oversight is important for handling complex situations and maintaining quality.

    Your action step for today is simple. Think about the most common customer questions you receive. Start making a list of repeated queries and how you usually respond. This list will be the foundation for training your custom GPT.

    In the next episode, we will focus on how to prepare data for training a custom GPT, including collecting past customer emails and structuring responses effectively.
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    3 m
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