If you provide customised services, creating every quote from scratch can become exhausting—and dangerously inconsistent.

One client gets one price.

Another client requests something similar but receives a completely different price.

Then you realise you forgot to include the planning time, revisions, software costs or profit margin. 😬

The solution is to build an internal AI-powered pricing engine.

This gives Claude or ChatGPT a structured pricing schedule it can use whenever you need to prepare a custom quote.

1️⃣ Break Every Service Into Smaller Deliverables

Start by listing every service your business provides.

Then break each service into the smaller tasks required to deliver it.

For example, “Build a sales funnel” might include:

✨ Strategy and planning
✨ Copywriting
✨ Page design
✨ Funnel development
✨ Form setup
✨ Payment integration
✨ Email automation
✨ Testing
✨ Revisions
✨ Project management

This becomes your internal menu of services from which clients can pick and mix to create a customised package.

2️⃣ Create Your Internal Rate Card

Record who may perform each type of work and the real cost of their time.

Your rate card might include:

✨ Your hourly cost or charge-out rate
✨ Employee wages
✨ Contractor rates
✨ Specialist rates
✨ Project-management time
✨ Software or platform costs
✨ Administrative overheads

Different team members have different costs, so the same number of hours will not always produce the same delivery cost.

3️⃣ Build Your Pricing Schedule

For every deliverable, record:

✨ Service category
✨ Deliverable name
✨ Description
✨ Estimated time required
✨ Person or role responsible
✨ Internal labour cost
✨ Additional expenses
✨ Total delivery cost
✨ Target profit margin
✨ Tax treatment
✨ Recommended selling price

You now have a consistent pricing matrix behind every custom quote.

And please remember: markup and profit margin are not the same calculation.

If you want a true target profit margin, make sure your formula is set up correctly and checked by your accountant or financial adviser.

4️⃣ Turn It Into an AI Pricing Skill

Once the pricing schedule has been created, add it to a dedicated Claude Project, skill or custom ChatGPT setup.

Give the AI clear instructions to:

✨ Use only the approved pricing schedule
✨ Match client requests to existing deliverables
✨ Calculate estimated hours and costs
✨ Apply your pricing and margin rules
✨ Add relevant taxes
✨ Identify missing information
✨ List assumptions and exclusions
✨ Flag anything requiring manual pricing
✨ Produce a client-ready quote

This means you won’t need to explain your entire pricing system every time you request a quote.

5️⃣ Give the AI the Client’s Requirements

The information could come from:

✨ A consultation-call transcript
✨ A discovery-call summary
✨ A client email
✨ A completed quote-request form
✨ Meeting notes
✨ A list of selected services

Upload or paste the information and ask:

“Using my approved pricing engine, identify the requested deliverables and prepare a detailed quote.”

The AI can analyse what the client wants, match it against your service matrix and calculate a proposed price.

6️⃣ Require a Complete Quote Breakdown

Ask the AI to produce:

✨ Project summary
✨ Scope of work
✨ Deliverables
✨ Estimated timeline
✨ Client investment
✨ Payment schedule
✨ Number of revisions
✨ Assumptions
✨ Exclusions
✨ Optional additions
✨ Quote expiry date
✨ Next steps

You can also ask it to prepare good, better and best package options using the same approved pricing data.

7️⃣ Connect It to Your Existing Systems

If your AI has authorised access to Google Sheets, it may be able to help create or reference your pricing schedule there.

If not, you can still build the matrix in Excel or another spreadsheet and upload the current version when needed.

You can eventually connect the process so that:

✨ A prospect completes your quote-request form
✨ Their answers are passed to your AI workflow
✨ The pricing engine matches the requested services
✨ A draft quote is generated
✨ Your team reviews and approves it
✨ The final proposal is sent to the client

See how it all starts coming together?

8️⃣ Always Review Before Sending

AI should prepare the draft—not make the final commercial decision without oversight.

Before sending any quote, confirm:

✨ The scope has been understood correctly
✨ All required work is included
✨ The estimated hours are realistic
✨ Current rates were used
✨ Taxes are correct
✨ Third-party costs are included
✨ The margin is acceptable
✨ The terms protect both parties
✨ Confidential internal costs are not shown to the client

Your pricing engine should make quoting faster and more consistent—not remove human judgement.

Build the pricing schedule once.

Turn it into an AI skill.

Add the client’s requirements.

Generate the quote.

Review it.

Send it.

Now every custom quote can follow the same pricing logic—without rebuilding the calculations from scratch every single time.

If you want practical training on using Claude, ChatGPT and automation to systemise your services, pricing and proposals, join us inside Legends Lab.

👉 https://sarahcordiner.com/legends

Sarah x

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