As of 13 August 2026, AI can only partly adjust your holiday let prices for demand.

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 your booking platform and export the available booking history, including booking dates, stay dates, prices, stay length and cancellations, then remove guest names and contact details.
   2. Gather your current price list, blocked dates, minimum stays, changeover rules, platform fees, cleaning costs and lowest acceptable price.
   3. Collect dated observations of comparable local properties, plus known local events, school holidays and other reasons demand may change, and label anything you could not verify.
   4. Paste the property details and all gathered data into the prompt, asking the model to use only supplied information and to recommend prices without changing or publishing them.
   5. Compare the proposed prices and reasons with your current calendar, booking history, cost floor and dated competitor observations, and remove recommendations based on missing or stale evidence.
   6. Enter the approved changes manually in your booking platform, record the old and new prices, and compare later booking activity with the test plan before making further changes.

   Prompt

   Act as a cautious UK holiday-let pricing analyst. Use only the information I provide and do not invent demand, competitor rates, events, bookings or financial figures. Analyse the data below and recommend, but do not publish or change, prices in pounds for each relevant date or date range.
   
   Property and rules:
   - Location: [location]
   - Property type and guest capacity: [details]
   - Current prices and date ranges: [paste current price list]
   - Minimum stay, changeover and booking rules: [rules]
   - Costs, fees and minimum acceptable price: [figures or say unknown]
   - Dates already blocked or unavailable: [dates]
   
   Historical and current data:
   - Booking history with booking date, stay dates, nightly price, length of stay and cancellations: [paste data]
   - Current occupancy or bookings: [paste data]
   - Enquiries, views or search data: [paste data if available]
   - Comparable properties and observed prices: [paste dated observations, or say unavailable]
   - Local events, school holidays and other known demand factors: [paste information]
   
   Produce:
   1. A table of recommended prices by date or date range, with the current price, proposed price, reason and evidence used.
   2. A list of assumptions and missing information, separating facts from inferences.
   3. A low, standard and high-demand scenario where the data supports it, without inventing probabilities.
   4. A list of price floors, booking rules and dates that I should review myself before publishing.
   5. A practical test plan for changing prices gradually and comparing results.
   
   Do not claim to know live competitor prices or future demand. Flag any recommendation that depends on information I have not supplied. Do not give tax, legal or financial advice.

   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.