Step-by-step Guide to Developing a Custom GPT for Quote Generation

In this detailed guide, we’ll see how to create a custom GPT within ChatGPT, specialized in automated quote generation. We’ll follow a step-by-step approach, from problem definition to integrating the chatbot into your company website. Each section will provide practical advice, examples, and tips to get the most out of your custom GPT.

1. Problem Identification: Why a Custom GPT for Quotes?

Before starting, it’s important to understand why developing a tailored GPT for quotes offers advantages over using “traditional” ChatGPT. Standard ChatGPT is trained on general knowledge and has a versatile approach, but it’s not specialized in your business domain. A custom GPT, on the other hand, is optimized for a specific task (in this case creating quotes) and can be trained on your company’s data.

Advantages of a custom GPT for quotes:

• More relevant and accurate responses: Unlike a generic model, a custom GPT is refined for your industry. This means it can provide more precise and relevant responses to quote requests in your field (Custom GPTs: guide to creating virtual assistants). For example, it will know your products, price lists, and technical terms, avoiding errors or irrelevant information.
• Consistency and custom style: You can set up the GPT to follow your brand’s communication style (formal/informal tone, way of addressing the customer) and use the correct company terminology. This ensures quotes consistent with your image and commercial policies.
• Efficiency and time savings: A specialized virtual assistant can generate quotes 24/7, speeding up the process. This reduces the manual workload for your team, who will only need to verify the results instead of preparing each quote from scratch.
• Use of updated internal data: With a custom GPT, you can include your internal data (updated prices, discounts, product details). Standard ChatGPT, by default, doesn’t have access to this proprietary information and might only provide generic answers (How to train ChatGPT on your data?). A model trained on your data avoids problems of obsolete or invented data.

In summary, a custom GPT represents a “quality leap” because it combines the power of ChatGPT with in-depth knowledge of your domain. The result is automatically generated quotes that are more precise and tailored, compared to what you would get with requests to a generic ChatGPT.

2. Effective Prompt Engineering: Limitations of ChatGPT Without Customization

Before building your dedicated GPT, let’s see how ChatGPT would behave without customizations. This helps highlight the limitations of the traditional approach and understand what problems we’re going to solve. A good starting point is to try a well-crafted prompt asking for a detailed quote from “base” ChatGPT and observe the result.

Example prompt (without custom GPT):

User: “Hi! I need a quote for 5 XYZ model phones and 3 ABC model laptops. The XYZ phone costs €300 each and the ABC laptop €800 each. Include in the quote a brief description of each product and the final total with 22% VAT. Thanks.”

In this prompt, we provide ChatGPT with the necessary details (quantities, models, unit prices, and VAT) and ask for a formatted quote. A generic ChatGPT will likely be able to formulate a sensible response, for example:

ChatGPT (generic response):
XYZ model phones (5 units) – Latest generation smartphone with 6" screen and 128GB memory. Unit price: €300; Total: €1,500