Illustrative example. This case study describes a typical engagement to show how the work unfolds. It does not name a client and does not use real client figures. Specific results vary by property, market and season.
A European hotel group was setting room rates on instinct and last week's figures, while competitors adjusted nightly across multiple booking channels. A daily feed of competitor rates - across the properties and channels that mattered - gave the revenue team a live view of the market and turned rate-setting into an informed decision.
The group in this example operates several mid-sized properties across European cities, competing for the same guests as a cluster of nearby hotels. A large share of revenue depended on getting room rates right - high enough to protect margin, competitive enough to win the booking.
Their problem was visibility. Rates on booking channels change constantly, and the revenue team had no reliable way to see, each morning, where their prices sat against the competition across every channel and date range that mattered.
The problem: rate-setting without market context
Pricing a hotel room without seeing competitor rates is guesswork, and on booking channels the market moves every day. The group felt this in three concrete ways.
- Rates set blind. The team adjusted prices without knowing whether they were above or below competing properties on the same dates.
- Manual checks could not keep up. Checking competitor rates by hand across channels and date ranges was slow and quickly went stale.
- Demand events missed. When a local event or seasonal surge moved the market, the team often reacted late, leaving revenue on the table.
It was not only lost bookings from over-pricing. Under-pricing during a high-demand window quietly gave away margin the group could never recover. The rate data existed publicly across channels; the team simply could not capture it at the cadence the market demanded.
The solution: a daily competitor rate feed
The goal was a single daily view of competitor room rates across the properties, channels and date ranges that mattered to the group - so the revenue team could see their position at a glance and price with intent.
We set up a managed feed matched to their competitive set. Each day it captured publicly listed rates for competing properties across the relevant booking channels and stay dates, normalised into one clean dataset - the approach behind our Hotel Price Monitoring solution. Because rate data is non-personal commercial information, this fits the lower-risk, GDPR-aware approach we follow across Europe.
How the engagement worked
The project followed the same four-step path we use for most rate monitoring engagements, structured so the revenue team could trust the data before relying on it.
Scope the data
We confirm exactly what to track, which sources and which fields the team needs.
Pilot dataset in 3-7 days
We deliver a validated pilot on a sample, so the team can check accuracy before scaling.
Scale to full coverage
Once approved, we expand to the full scope on a daily refresh schedule.
Ongoing managed feed
We monitor and maintain the feed as sources change, so the team only works with finished data.
The outcome: rate-setting on evidence
The change was a new daily habit: instead of guessing, the revenue team began each day with a clear view of where their rates sat against the competitive set across key dates.
Rate decisions stayed firmly with the group - the feed never set a price. What changed was the input: every rate decision now started from a current view of the market instead of a guess.
"We were never short on pricing instinct. We were short on knowing what everyone around us was charging tonight. The feed gave us that."
Illustrative summary of the revenue team's perspective in this example engagement.The takeaway
The lesson applies to most hotels and groups competing on rate: pricing is only as good as your view of the market, and on booking channels that view goes stale within a day. Manual checking cannot keep pace.
A managed rate feed closes that gap. It does not set rates; it makes sure every rate decision is made with the current market in view - which is the difference between pricing on instinct and pricing on evidence.
Frequently asked questions
Hotel rate monitoring means regularly capturing publicly listed room rates for competing properties across booking channels and stay dates, so a revenue team can see where their own rates sit against the market.
Yes. A managed feed can track publicly listed rates across the channels and date ranges that matter to a property, normalised into one consistent dataset delivered on a daily schedule.
Room rate data is non-personal commercial information, which is the lower-risk category in the EU. We focus on publicly available, non-personal data and recommend clients confirm their specific use with appropriate legal review.
No. It is an illustrative example written to show a typical engagement. It does not name a client or use real client figures. Specific results vary by property, market and season.
WebDataScraping.us
We build and run managed rate and price monitoring feeds for European and US travel and hospitality teams - focused on publicly available, non-personal data.