As of 13 August 2026, AI can price an online course.

What to actually do

1. Use a tool built for this

   The route this page recommends

2. Do it yourself

   Second choice

   A chat interface, chat-fluent skill, and roughly 1 hour until you can act on the result.

   How to actually do it

   1. Open a spreadsheet and create columns for each course price, expected sales, revenue, payment costs, delivery costs, marketing costs and contribution.
   2. Gather your course outline, access period, support offer, target customer, business objective and any limits on places or support time.
   3. Export or copy your relevant sales, enquiry, traffic, conversion and refund data, then record the period and source beside each figure.
   4. Collect current competitor course pages and record their prices, inclusions, access terms and links without filling gaps from memory.
   5. Paste the gathered information into the prompt and ask the AI to produce the three options, calculations and test plan.
   6. Compare every number in the response with your spreadsheet and source pages, remove unsupported assumptions, then choose a price test and publish only the option you can deliver profitably.
   7. Run the test through your normal checkout and compare enquiries, conversion, sales, refunds and support demand with the baseline before changing the price again.

   Prompt

   Act as a pricing analyst for an online course. Recommend a launch price and a small set of alternative prices using only the information I provide.
   
   Course: [course name and description]
   Target customer: [who buys it, their problem and relevant experience]
   What is included: [lessons, support, community, assessments and access period]
   Evidence of demand: [sales, enquiries, email list, audience size or other evidence, with dates if available]
   Current or planned sales data: [price, sales, conversion rate, refunds and traffic, if available]
   Competitor offers: [competitor names, prices, inclusions and links]
   Costs: [fixed costs, per-student costs, payment fees and marketing costs]
   Business objective: [profit, reach, validation, recurring revenue or another objective]
   Capacity or constraints: [support time, cohort size, launch date and any price limits]
   
   Give me:
   1. The strongest recommended price and a sensible price range.
   2. Three pricing options, labelled conservative, central and premium, with the assumptions and trade-offs for each.
   3. A simple calculation showing revenue and contribution after the costs I supplied. Do not invent missing figures. Mark missing inputs clearly.
   4. The evidence that supports each recommendation, separating facts from assumptions and judgement.
   5. The most important uncertainty and the smallest price test I can run to reduce it.
   6. The exact measures I should monitor, such as enquiries, checkout conversion, sales, refunds and support demand.
   
   Do not present competitor prices or market conditions as current unless they are in my supplied evidence. Do not claim to know what customers will pay. End with a short decision brief that states what I should do now, what would change the decision, and what I still need to verify.

   Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.

3. Hand it to a person

   The distant third

   A person who owns the outcome does this end to end, worth it when the failure is dear.