Hotel Conversion Scenario Calculator
Explore the arithmetic of a conversion-rate scenario using an assumption you set yourself. MisMatchMaker has not measured a conversion decline caused by listing mismatches, so this page ships with the assumed impact at zero.
Your scenario
Labels your own figures. Nothing is converted between currencies.
How many times your listing page was viewed in a month, taken from the analytics area of the partner extranet you are modelling. Use one platform at a time; view counts are not comparable between platforms.
Bookings divided by listing views over the same period, on the same platform. This is your current measured rate, not a target.
The proportion of your conversion rate you want to model losing. This is an assumption you are choosing to test, not a figure we have measured. A 10% relative decline on a 3.2% rate means 2.88%, not 3.1%.
Total revenue for a typical booking on this channel, including the full length of stay rather than a single night.
Baseline monthly bookings
1,600
Scenario booking difference per month
0.0
Scenario revenue difference per month
€0
Scenario revenue difference per year
€0
Check the content behind your channel mix
MisMatchMaker compares supported listing details. It does not predict revenue or compare rates.
Check my listingsHow to read the result
Baseline monthly bookings
What your entered views and conversion rate imply before any scenario is applied. If this is far from the bookings you actually see, one of the two inputs is measuring a different thing — usually views counted per session versus per page load.
Scenario booking difference per month
How many bookings the assumed relative decline corresponds to. Read it as the size of the bet you are testing, not as a loss you have incurred.
Scenario revenue difference per month
The booking difference priced at your average booking revenue. It is top-line revenue, not margin, so it overstates the effect on profit.
Scenario revenue difference per year
Twelve times the monthly figure. Use it to decide whether a fix is worth prioritising, and state the assumption alongside the number whenever you quote it internally.
A worked example
Testing whether a listing fix is worth a week of work. Figures are illustrative and are shown in EUR for readability; they are not measured research or a benchmark for your property.
Inputs
- Monthly OTA listing views
- 24,000
- Baseline conversion rate
- 2.5%
- Assumed relative conversion decline
- 4%
- Average revenue per booking
- 310
Result
- Baseline monthly bookings
- 600
- Scenario booking difference
- 24 per month
- Scenario revenue difference
- 7,440 per month
- Scenario revenue difference
- 89,280 per year
This does not say that mismatched content costs this hotel 89,280 a year. It says that if a 4% relative conversion decline were happening, it would be worth roughly that much — which is enough to justify a week spent auditing listings and then measuring whether conversion actually moves. Treat the output as a prioritisation aid and verify the real rate afterwards.
What each input means
Most disagreements between a calculator like this and a real statement come from putting the right number in the wrong box. These are the definitions this tool assumes.
- Monthly OTA listing views
- How many times your listing page was viewed in a month, taken from the analytics area of the partner extranet you are modelling. Use one platform at a time; view counts are not comparable between platforms.
- Baseline conversion rate (%)
- Bookings divided by listing views over the same period, on the same platform. This is your current measured rate, not a target.
- Assumed relative conversion decline (%)
- The proportion of your conversion rate you want to model losing. This is an assumption you are choosing to test, not a figure we have measured. A 10% relative decline on a 3.2% rate means 2.88%, not 3.1%.
- Average revenue per booking
- Total revenue for a typical booking on this channel, including the full length of stay rather than a single night.
Formula and limitations
Formula
Baseline bookings = listing views × baseline conversion rate. Scenario booking difference = baseline bookings × your assumed relative decline. Monthly revenue difference = scenario booking difference × average revenue per booking. Annual revenue difference = monthly revenue difference × 12.
What this calculation does not include
- The assumed decline is your input, not a measured or published effect. Nothing in this tool establishes that listing mismatches cause a conversion change of any size.
- There is no causation in the model. It converts an assumption into money; it does not test whether the assumption is true.
- Revenue is top line. Cancellations, length-of-stay variation, taxes, commission, and variable costs are excluded.
- Channel substitution is ignored. A guest who does not book on one platform may still book on another, or direct.
- View and conversion definitions differ between platforms, so figures from two extranets should not be combined.
- The annual figure assumes twelve equal months and steady demand.
Frequently asked questions
Does MisMatchMaker know how much listing mismatches reduce conversion?
No, and this page deliberately does not imply a figure. We have not run a study that measures it, and we have not found a published source that establishes a universal effect across properties and platforms. That is why the assumed decline starts at zero: the page produces a result of zero until you supply an assumption you are willing to own.
What is the difference between a relative and an absolute conversion decline?
A relative decline is a proportion of your current rate; an absolute decline is a change in percentage points. A 10% relative decline applied to a 3% conversion rate gives 2.7%. A 10 percentage-point absolute decline would give −7%, which is impossible. This calculator uses relative decline, which is why the input is capped at 100%.
Where do I find my listing views and conversion rate?
Both usually sit in the analytics or performance area of each partner extranet, reported per property and per period. Take them from the same platform and the same date range, and check how that platform defines a view before comparing it with anything else — the definitions are not standardised.
Can I use this figure in a business case?
Only if you quote the assumption with it. A number of this kind is defensible when it is presented as "if conversion fell by this much, it would be worth this much", and misleading when it is presented as a measured loss. The safer sequence is to fix what you can verify, then measure whether conversion actually moves.
Can I share a scenario with my team?
Yes. The inputs live in the page address, so the link reproduces the exact scenario, assumption included. That matters more here than on the other calculators, because the assumption is the part a reader most needs to see before trusting the result.