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How to Preview Pricing Changes Before Applying Them

Learn how to simulate preference changes and see their impact on daily prices before saving anything to your listing.

Written by Ryo

Before committing to a preference change, you can preview exactly how it would affect your listing's daily prices — without saving anything. This is useful for building "what if" tools, showing users a price impact before they confirm, or validating changes programmatically.


Preview a preference change

Send the hypothetical preference values in the request body. The API returns the same price recommendation format as the standard recommendations endpoint — but calculated using your hypothetical settings, not the saved ones.

curl -X POST "https://api.usewheelhouse.com/ss_api/v1/preferences/12345678/preview?channel=airbnb" \
-H "X-Integration-Api-Key: your_api_key_here" \
-H "Content-Type: application/json" \
-d '{
"base_price": 200
}'

Reading the response

The response matches the daily price recommendations format — a data array with one entry per day, plus base price context. Note: min_stay is not included in preview responses.

{
"data": [
{ "stay_date": "2026-03-20", "price": 210, "currency": "USD" },
{ "stay_date": "2026-03-21", "price": 240, "currency": "USD" },
{ "stay_date": "2026-03-22", "price": 252, "currency": "USD" }
],
"base_price": 200,
"base_price_recommended": 175,
"base_price_conservative": 158,
"base_price_aggressive": 193
}

Nothing is saved. The listing's actual preferences remain unchanged until you explicitly call the update endpoint.


What you can preview

The request body accepts the same fields as the preferences update endpoint:

  • base_price — the anchor price to simulate

  • base_price_adjustment — percentage adjustment to Wheelhouse's recommended base price (used when base_price is not set)

  • last_minute_discount / far_future_premium — discount/premium config objects, same format as the preferences endpoint

  • weekly_discount / monthly_discount — long-stay discount percentages

  • price_model — the price model version to use: "current" or "opt_in"

Pass one or multiple fields in a single request to see their combined effect.

Next steps

How to pull reservation data

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