The Booked vs. Stayed Upgrade Analysis in Insights identifies when a guest’s booked inventory differs from their most recent stayed inventory, and classifies whether that change was paid (with additional overnight accommodation revenue tied to the action) or complimentary (no additional revenue).
This FAQ addresses common questions about how the analysis works and how to interpret the results.
FAQs
What does “Booked vs. Stayed” mean?
It’s a comparison between the inventory originally booked and the most recent stayed inventory for the same booking. If they differ, we record a change and classify it as an upgrade (to higher-ranked inventory) or a downgrade (to lower-ranked inventory).
How do you decide whether it’s an upgrade or a downgrade?
We rank inventories using historical ADR at the property. Moving to higher-ranked inventory is an upgrade; moving to lower-ranked inventory is a downgrade. This avoids relying only on inventory names, which vary across properties.
How do you decide whether an upgrade is paid or complimentary?
For units, we compare the first confirmed booking to the most recent version. This shows whether a guest ended up in higher- or lower-ranked inventory.
For revenue, we isolate changes specifically tied to the inventory movement across booking versions:
If the change has additional overnight accommodation revenue directly tied to it, we classify it as a paid upgrade.
If the change does not have additional overnight accommodation revenue tied to it, it is a complimentary upgrade.
This approach avoids unrelated adjustments (like discounts or taxes) being misclassified as upgrade revenue.
Do you look at every intermediate change?
For units, no. We compare only the first confirmed booking and the most recent version, so the analysis stays clear and avoids noise.
For revenue, yes. We check across versions to isolate the specific change tied to the inventory movement. Other edits (e.g., discounts or taxes) are ignored.
Are upsell postings (like fixed charges, Nor1) included?
Not yet. At present, the analysis only reflects overnight accommodation revenue tied to inventory changes.
Other upsell postings are not currently included. This is why Insights upgrade revenue may differ from totals you see in PMS reports or end-of-month revenue summaries.
Future development may explore incorporating these additional transactions once data consistency across systems can be ensured.
Why might totals differ from what I see in my PMS?
You may notice differences for several reasons:
Only overnight accommodation revenue is included, not other postings such as fixed charges or upsells.
Optional or tentative bookings are excluded.
We always compare the first confirmed booking to the most recent version, which may differ from PMS views that show in-progress or intermediate states.
PMS-specific postings are not included today, but are on the roadmap to be supported.
What about virtual room types?
Virtual room types are not supported in Insights, and it is unlikely we will be able to support them in the near future. The way this data is structured across systems makes it extremely complex to reconcile reliably.
We recommend focusing upgrade analysis on supported inventories, as those will remain consistent across your data in Insights
Why are some upgrade paths blank or “undefined”?
In large or complex bookings (such as hostels or groups with many beds tied to one booking ID), inventories may shift in multiple directions over time. In those cases, it is not always possible to identify a single clear path. The analysis will still show that a change occurred and whether it was paid or complimentary, but the “from → to” path may be undefined.
What about downgrades?
Downgrades are recorded when the most recent stayed inventory is lower-ranked than the originally booked inventory. They follow the same classification process as upgrades: if there is revenue specifically tied to the downgrade action, it will be shown, though in most cases no additional revenue is collected and sometimes the recorded revenue is lower than the originally booked level.
Is this the same as “Booked vs. Paid”?
No. This is a Booked vs. Stayed analysis with an additional classification of paid vs. complimentary. That distinction means you can see both what inventory the guest ultimately stayed in and whether the change generated overnight accommodation revenue.
How are multi-night stays handled?
The analysis reflects changes over the stay period. If a booking moves between inventories for some nights only, those nights are counted in the underlying data so that upgrade frequency, mix, and value reflect the real booking pattern.
Does this depend on PMS-specific features like RTC?
No. The analysis is PMS-agnostic.
We don’t rely on PMS-specific fields like RTC.
Instead, we apply the same standardized logic across all systems: comparing originally booked to most recent stayed inventory, and using ADR-based ranking for the hierarchy.
This ensures results are consistent and comparable across your entire portfolio.
An added benefit of this approach is that it’s actually more resilient than RTC. RTC values in PMSs can sometimes be overridden by accident or subject to human error at the property, which can make them unreliable. By avoiding RTC altogether, Insights gives you a more stable and trustworthy view of upgrade and downgrade activity.
Do you track room number changes within the same inventory?
No. The analysis focuses on inventory changes (e.g., Standard → Deluxe). Room-to-room moves within the same inventory are not included.
If a rate changes but the inventory doesn’t, is that included here?
Yes, the booking still appears in the dataset.
However:
Because no inventory change occurred, there is no upgrade or downgrade activity.
In these cases, the booking shows no upgrade/downgrade units and no upgrade/downgrade revenue.
What if ADRs change over time — does the ranking stay accurate?
Yes. Inventory ranking is based on rolling 365-day ADR history, so it updates continuously. This ensures the upgrade/downgrade hierarchy reflects real pricing behavior rather than static assumptions.
Can I see who upgraded a guest or where the upgrade decision came from?
No. PMS data does not tell us who processed the change or what triggered it.
What the analysis shows is the outcome:
Whether the guest stayed in different inventory than originally booked.
Whether the change generated overnight accommodation revenue.
Context such as channel, segment, or company reflects the most recent booking information. This helps frame where upgrade activity occurred, but may not perfectly align to the moment when the change itself was made.
Still have questions?
If you’re unsure how to interpret a result or how this applies to your property, our Advisory team is here to help. Reach out through the in-app chat and we’ll be happy to walk through it with you.