Training the GPT to Handle Quotation Requests and Price Inquiries #S11E5

ChatGPT Masterclass - AI Skills for Business Success

This is season eleven, episode five. In this episode, we will focus on how to train a custom GPT to handle quotation requests and price inquiries accurately. You will learn how to structure pricing data, define rules for customized quotes, and ensure AI-generated responses are correct and reliable. By the end of this episode, you will know how to make your AI assistant generate pricing responses that are clear, professional, and aligned with your business policies.

So far, we have integrated product specifications and pricing data into our custom GPT. Now, we need to ensure that AI-generated quotations follow business rules and provide the right pricing information based on customer needs.

Let’s go step by step on how to structure pricing data, automate quotation requests, and prevent errors in AI-generated pricing responses.

---

Step One: Organizing Pricing Data for AI Use

Before training a custom GPT to provide quotations, we need to ensure that pricing information is structured in a way that AI can reference easily. Pricing data can include:

• Standard pricing for each product
• Bulk pricing discounts based on order volume
• Custom pricing for specific customer groups such as resellers or partners
• Additional costs like shipping fees or customization charges

If your pricing changes frequently, storing this data in a structured document allows the AI to pull the most up-to-date information. The key is to make sure that each product has a clear price listing along with any conditions that affect pricing.

For example, if your business offers different price tiers based on order quantity, AI should be trained to recognize volume-based discounts and apply the correct pricing level.

---

Step Two: Training AI to Recognize Different Pricing Scenarios

Customers request pricing in many different ways. Some might ask for a single product price, while others need a bulk order quotation. The AI must understand these differences and provide the correct response based on context.

Here are some common pricing scenarios and how AI should handle them:

1. Single product price inquiry – If a customer asks for the price of one specific product, the AI should respond with the standard unit price.
2. Bulk pricing inquiry – If a customer asks for pricing based on order quantity, the AI should reference the appropriate discount tier and provide a breakdown.
3. Custom quotes for large orders – If the order exceeds a certain value, the AI should request additional details before generating a quote.
4. International pricing – If pricing varies based on region, AI should confirm the customer’s location before providing an answer.
5. Shipping cost estimation – If the total price depends on shipping costs, AI should either provide an estimate or request additional location details.

By training the AI to recognize these different pricing scenarios, it can provide more relevant and accurate responses.

---

Step Three: Handling Custom Quotations and Special Pricing Requests

Not all price inquiries follow a fixed structure. Some customers may ask for personalized quotations based on their specific needs. AI should be trained to gather the necessary details before generating a response.

For example, if a customer requests a custom quote for a large order with custom branding, the AI should follow a structured response format, such as:

• Acknowledge the request and confirm the details.
• Ask follow-up questions if necessary, such as order quantity, delivery deadline, or customization options.
• Provide an estimated quote if the conditions are straightforward.
• If human review is required, let the customer know that a sales representative will follow up.

This approach ensures that AI responses remain professional and accurate without over-promising information that requires manual verification.

---

Step Four: Preventing Errors in AI-Generated Price Quotes

One of the biggest risks in automating pricing responses is incorrect or misleading quotations. If AI provides the wrong pricing, it can cause confusion and frustration for customers. To prevent this, you need to define safeguards and validation checks.

Here are some ways to prevent pricing errors:

• Set response limits – AI should not provide price quotes beyond a certain threshold without human approval.
• Include disclaimers where necessary – If prices fluctuate based on market conditions, AI responses should mention that final pricing will be confirmed by the sales team.
• Use fallback responses – If AI cannot confidently provide a price, it should say:
  “For a detailed quotation, our team will review your request and get back to you shortly.”

These measures ensure that AI remains a useful assistant rather than an independent decision-maker for critical pricing information.

---

Step Five: Training AI to Handle Follow-Up Questions on Pricing

Customers often have follow-up questions after receiving a price quote. AI should be trained to anticipate and handle these follow-ups efficiently.

Some common follow-up questions include:

• Is this the best price you can offer? – AI should clarify whether pricing is fixed or if discounts are available.
• Do you offer payment plans or financing? – If applicable, AI should provide basic payment options and direct customers to the sales team for further details.
• What is included in the price? – AI should clarify if additional costs, such as taxes or shipping, are included in the total.

By handling follow-up questions effectively, AI enhances the customer experience and ensures smoother sales interactions.

---

Key Takeaways from This Episode

• Pricing data should be structured clearly so AI can retrieve the correct information.
• AI must recognize different pricing scenarios, such as bulk discounts and custom quotations.
• AI should request additional details before generating a quote for complex orders.
• Safeguards must be in place to prevent AI from providing incorrect pricing information.
• AI should be trained to handle follow-up pricing questions to improve customer engagement.

---

Your Action Step for Today

Review your pricing structure and quotation process. Ask yourself:

• Is my pricing data organized in a way that AI can reference easily?
• Do I have clear rules for bulk pricing, international pricing, and custom quotations?
• What safeguards should I put in place to ensure AI does not generate incorrect price quotes?

If your pricing data is not yet structured for AI use, start consolidating it into a clear and organized format so that AI-generated quotations are always accurate.

---

What’s Next

In the next episode, we will focus on how to build product recommendation logic based on customer needs. You will learn how to classify products by application, train AI to suggest the best options, and use decision trees to guide customer choices.