The Booked vs. Stayed Upgrade Analysis in Insights identifies when a guest’s stayed inventory differs from their originally booked inventory. It classifies whether that change was paid (with additional overnight accommodation revenue tied to the action) or complimentary (no additional revenue).
This article explains the logic behind how the analysis works, along with the limitations to be aware of when interpreting the results.
How the Analysis Works
To ensure consistency across different PMS systems, the analysis applies a straightforward but reliable logic:
Start with the first confirmed booking
The originally booked inventory is set as the baseline for comparison.
While overnight accommodation revenue is also present at this stage, it is not used directly to classify upgrades. Instead, revenue linked specifically to room change actions is identified later in the process.
Compare to the most recent version
The most recent version of the booking reflects the inventory where the guest ultimately stayed.
Any difference between booked and stayed inventories is recorded as a change: an upgrade if the guest moved to higher-ranked inventory, or a downgrade if they moved to lower-ranked inventory.
Determine upgrade or downgrade direction
Because inventory names vary across properties, historical ADR data from a rolling 365 days is used to create a consistent hierarchy of inventories.
This ensures upgrades and downgrades are determined by pricing behavior rather than property-specific naming conventions.
Classify the change as paid or complimentary
Unit changes are identified by comparing the first confirmed booking to the most recent version.
For revenue, we don’t simply compare total values (which would capture unrelated adjustments). Instead, we look across booking versions to isolate the revenue tied specifically to the inventory movement.
If additional overnight accommodation revenue is linked to the change, it’s a paid upgrade. If not, it’s complimentary.
Downgrades are identified the same way. When a guest ends up in lower-ranked inventory, any associated revenue change is recorded. In most cases this results in no additional revenue, and sometimes a lower revenue than originally booked.
Why We Take This Approach
The data we receive from PMSs does not include a clear “upgrade flag.” By comparing the first confirmed booking against the most recent version and isolating revenue tied to inventory movements, we can consistently identify upgrade and downgrade behavior across all properties.
This method ensures:
Consistency across systems: the same logic applies regardless of PMS.
Resilience: unlike RTC, which can be prone to human error (such as being overridden on property), this approach avoids those pitfalls and provides a more reliable output.
Focus on meaningful changes: intermediate edits are ignored so only the final outcome is reflected.
Reliable outputs: combining booked vs. stayed inventories with paid vs. complimentary classification gives a structured view of upgrade activity.
Limitations to Be Aware Of
As with any analysis, there are caveats to keep in mind:
Overnight accommodation revenue only: Additional upsell postings (e.g., Upsell, Upgrade, Nor1) are not yet included. This means Insights totals may differ from PMS or end-of-month revenue summaries.
Virtual room types: These are not supported in Insights, and due to the way data is structured across systems, are unlikely to be supported in the near future.
Bookings with many units under one ID: In cases such as hostels or large groups, the exact upgrade path may not always be shown. The analysis still reflects the number of units changed and whether these were paid or complimentary.
Confirmed bookings only: Optional or tentative bookings are excluded so results reflect actual stayed activity.
While some individual cases may look different from what you see in PMS, overall patterns of upgrade activity — including volume, mix, and value — are captured consistently and reliably.
Key Takeaways
Booked vs. Stayed Upgrade Analysis compares a guest’s original booked inventory to the most recent stayed inventory.
Inventories are ranked using historical ADR to establish a consistent upgrade/downgrade hierarchy.
Changes are classified as paid when additional overnight accommodation revenue is collected, and complimentary when it is not.
Downgrades are also recorded when a guest ends up in lower-ranked inventory.
Need Help?
If you’d like support interpreting your results or have questions about how this analysis applies to your property, please reach out to our Advisory team through the in-app chat — we’re here to help.