As of 13 August 2026, AI can only partly decide when to raise your prices.

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 30 minutes until you can act on the result.

   How to actually do it

   1. Open your current price list, sales records and cost records, then copy the relevant figures into a single spreadsheet with dates, units, revenue, discounts and costs identified.
   2. Gather customer evidence from recent sales notes, cancellation reasons, renewal data and support messages, removing personal data that is not needed for the analysis.
   3. Collect dated competitor prices from the competitors' current websites or quotes, and mark each item as verified, incomplete or unavailable.
   4. Paste the prepared information into the prompt, replacing every bracketed section and stating clearly where you have no evidence.
   5. Ask the AI to compare the current price with at least one conservative and one higher proposed price, then check every calculation against your spreadsheet.
   6. Compare the recommendation with your capacity, contracts, customer commitments and cash requirements, and run a limited price test or discuss the decision with a colleague before changing the full price list.

   Prompt

   Help me decide whether and when to raise my prices. Use only the information I provide and clearly label assumptions, unknowns and calculations. Do not invent market data, competitor prices, customer reactions or financial figures.
   
   Business and offer: [describe the business, product or service, customer type and current price]
   Current price list: [paste prices, packages, discounts and billing terms]
   Costs: [paste relevant variable and fixed costs, with the period and currency]
   Sales history: [paste dates or periods, units sold, revenue, enquiries, conversions, cancellations and renewals if available]
   Capacity: [state delivery capacity, utilisation, staffing constraints and any waiting list]
   Customer evidence: [paste survey responses, objections, churn reasons, sales notes or support themes]
   Competitor evidence: [paste dated competitor prices and sources, or say that none is available]
   Objectives and constraints: [state target margin, growth or cash objective, minimum acceptable volume, contractual limits and the date by which you need to decide]
   
   Return:
   1. A concise diagnosis of whether the available evidence supports a price increase now, later or not yet.
   2. The strongest evidence for and against an increase.
   3. A table comparing the current price with each proposed price of [list proposed prices or ask me to suggest scenarios without inventing market evidence]. Show the arithmetic for revenue and cost effects using my figures only.
   4. The assumptions and missing information that could change the recommendation.
   5. A low-risk test plan, such as applying the change to a defined new-customer segment or package, without presenting it as guaranteed to work.
   6. A short list of questions I should answer before making the final decision.
   7. A final recommendation with a confidence rating based on evidence quality, not certainty about customer behaviour.
   Do not make the final decision for me. Keep the recommendation specific to my information and say when a small pilot or professional commercial advice would be more appropriate.

   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.