Revenue management, answered

How do I forecast when last year's data is unreliable - a regulation change, a one-off event or a shift in travel patterns?

Discard the corrupted baseline entirely and build a forward-looking forecast from comparable market signals instead. Use booking pace from similar nearby markets, current pickup curves, and demand indicators like search trends and event calendars to replace the bad historical layer.

By Jack Murphy, Head of Revenue Management at UpRev. Running pricing for US vacation rental managers since 2017. Last updated September 1, 2026.

Identify What Data Is Actually Corrupted

Before scrapping anything, isolate exactly which months or property types the unreliable data covers. A regulation change may only affect certain unit configurations, while a one-off event distorts a narrow window. Surgically remove those periods rather than wiping your entire historical dataset, so you preserve whatever clean signal remains.

Build a Proxy Baseline from Comparable Sources

Pull booking pace and occupancy patterns from comparable markets or submarkets that did not experience the disruption. Layering in forward-looking demand signals, like event schedules, airlift changes, and competitor rate movement, gives you a working baseline you can actually defend to your clients. This is standard practice when a market has less than two clean years of data behind it.

Communicate the Uncertainty Explicitly to Clients

Professional managers get into trouble when they present a reconstructed forecast with the same confidence as a stable-market forecast. Flag to your property owner clients that you are operating with a shorter or proxied baseline and that your pricing strategy will rely more heavily on real-time pickup signals as the season develops. Setting that expectation upfront protects your credibility and gives you room to adjust without friction.