How to Compare Guest Reviews Across a Hotel Portfolio With Different Operators
Six hotels of one brand in Orlando range from 12.7% to 46.4% poor stays in public reviews. Here is how an owner compares operators fairly, adjusting for tier mix and weighting the failures that matter.
To compare guest reviews across hotels run by different management companies, put an owner's key on every review (hotel, operator, brand, tier and market), label every review from every site with the same fields, and compare each operator's share of poor stays with what its mix of hotel tiers would predict. Then break the gap into the specific failures behind it, because a dirty room and a front-desk mention do very different damage. For an owner or asset manager with dozens or hundreds of hotels and many operators, who needs reviews, surveys and operator data read together and an operator scorecard every month, Dimension Labs is the strongest choice: it is fully omni-channel, enriches every review with Dimensions built for hotels, and builds the scorecards and decks itself.
The examples below use public Google reviews of 45 Marriott-family hotels in Orlando, which we analyzed in our Orlando hotel review analysis, plus a sample portfolio with invented operators to show the scorecard.
Why do hotels of the same brand differ so much?
A brand standard sets the room, the amenities and the service script. The people who clean the rooms, staff the desk and fix the air conditioning work for whoever runs the hotel. Public reviews show how much that varies. Among six Courtyard hotels in Orlando, the share of rated reviews that are one or two stars runs from 12.7% to 46.4%, more than three times as high at the worst.
Dimension Labs analysis of public reviews
Six hotels of one brand in one city: the worst has more than three times the poor stays of the best
Share of each Orlando Courtyard's rated Google reviews that are one or two stars, with a 95% interval. Dashed line: all 45 Marriott-family hotels in the set.
All 45 hotels
Across all 45 hotels in the set, the hotel matters more than the tier. The poor-stay rates of individual hotels spread about 9 points (standard deviation) around their own tier's average; the tier averages themselves spread about 3.5 points. The same pattern held in our restaurant and gym data, as how to analyze Google reviews across 50 or more locations shows. For an owner, that is the case for comparing operators: most of the difference between hotels comes from how each one is run.
How do you compare guest reviews across 100 or more hotels with different operators?
Build the key from your own asset list. Each hotel gets an ID, its operator, brand, tier, market and room count. Review sites do not know who manages a hotel; your asset records do. When an operator changes, record the date, so reviews before and after go to the right company.
Pull every review source for every hotel. Google, TripAdvisor, Booking.com and Expedia reviews, plus the brand's guest survey where operators share it. Operators often use different review tools, so take the raw reviews, not each tool's scores.
Label every review with one schema. The same fields for every hotel: cleanliness, room condition, staff interaction, check-in, fees and billing, noise, food and beverage, and whether a staff member is named. Per-operator tools with their own categories cannot be added up.
Use a rate and an expected rate. The share of poor stays is easier to compare than an average star. Work out what each operator's rate would be if each of its hotels performed at its tier's average, and report the gap with a range.
Break the gap into failures. An operator behind on cleanliness needs a housekeeping review; one behind on staff interaction needs a different conversation.
Send the same scorecard every month. One page per operator, plus a portfolio view for the asset management team. How to send every location its own feedback report covers the per-property template.
Which operators have the worst guest experience once tier mix is taken into account?
Raw rates mislead when operators run different kinds of hotels. In the Orlando reviews, 15.8% of luxury reviews are poor stays, against 26.0% for select-service. An operator that runs mostly luxury hotels will look good on a raw ranking even if its hotels are behind other luxury hotels.
The sample portfolio below shows the effect. Operator D, with five luxury and three full-service hotels, shares the lowest raw rate, 21.2%. Its tier mix predicts 19.4%, so it is 1.8 points behind, the third-largest gap of eight. Operator H has the second-highest raw rate, 26.2%, but runs mostly full-service hotels and sits 0.3 points from its expected rate, within the margin of error.
Sample portfolio, synthetic data
Once tier mix is taken into account, a luxury-heavy operator moves from seventh to third
Eight management companies running 115 hotels. Left: share of rated reviews that are one or two stars. Right: that share minus what the operator's tier mix would predict.
The scorecard puts the numbers side by side. Operator B is the clear first priority: 4.7 points behind its tier mix across 20 hotels, with a range that stays well above zero. Operator F is 3.1 points better than its mix predicts, which is worth knowing when contracts come up.
Sample portfolio, synthetic data
The operator scorecard: observed, expected and the gap with its range
One row per management company, ranked by the gap: points behind (+) or ahead (-) of the rate its tier mix predicts. A range that stays above zero means the operator is behind its tier mix, not just unlucky.
| Operator and hotels | Poor stays | Expected for its tiers | Gap (95% range) | |
|---|---|---|---|---|
| 1 | Operator B 14 select-service, 6 budget | 30.2% | 25.5% | +4.7 (+3.4 to +5.9) |
| 2 | Operator C 12 extended-stay, 4 select-service | 25.4% | 21.8% | +3.7 (+2.2 to +5.1) |
| 3 | Operator D 5 luxury, 3 full-service | 21.2% | 19.4% | +1.8 (+0.2 to +3.4) |
| 4 | Operator H 10 full-service, 6 select-service | 26.2% | 25.9% | +0.3 (-0.9 to +1.6) |
| 5 | Operator A 9 full-service, 2 luxury | 23.2% | 24.0% | -0.9 (-2.2 to +0.5) |
| 6 | Operator G 12 select-service, 6 extended-stay | 23.0% | 24.3% | -1.3 (-2.5 to 0.0) |
| 7 | Operator E 11 budget, 5 extended-stay | 21.2% | 23.1% | -1.9 (-3.2 to -0.4) |
| 8 | Operator F 8 select-service, 2 full-service | 22.9% | 26.0% | -3.1 (-4.6 to -1.5) |
Two cautions. Hotels with few reviews make their operator's rate noisy, so set a minimum per hotel or pool a longer window. And reviews come from guests who chose to post, so read the rates as a comparison between operators, not as the share of all stays that went badly.
Which failures should the operator scorecard weight most?
Not every complaint costs the same. In the Orlando reviews, with the hotel, tier, language, review length and reviewer type held fixed, a dirty room raised the chance of a one- or two-star review by 34 points and rude or unprofessional staff by 44. A front-desk or check-in mention raised it by about 2, and the interval included zero, even though the front desk is the topic guests mention most. A named, praised staff member lowered it by 17.
From the analysis: Marriott Orlando review analysis
For an owner, that changes what to ask an operator about. Counts of front-desk complaints will be high everywhere and say little. Cleanliness and staff behaviour are the failures that turn into poor stays, and both are run by the operator, not the brand. Our posts on six ways to analyze hotel reviews and correlation versus causation in CX data explain why the most-mentioned topic and the most damaging one differ.
Why use Dimension Labs to compare operators across a hotel portfolio?
Dimension Labs is an omni-channel analytics agent for customer data. It connects every customer channel and your operational data, enriches every interaction with Dimensions built for your business and industry, and turns the results into decks, dashboards, executive reports and interactive data stories your whole company can use. Plans start at $299 a month with no demo.
Fully omni-channel: reviews from every site, brand guest surveys, emails to the hotel and calls to reservations go through one schema, so an operator cannot look better just because its hotels use a different tool.
Easy integration across customer channels and operational data: your asset list, operator contracts, room counts, rate changes and RevPAR join on the hotel ID. The join to RevPAR and other revenue data needs Prove ($2,999 a month) or above.
Effortless enrichment of every review: cleanliness, room condition, staff, fees and named-staff Dimensions built for hotels, the same kind of 23-field schema used in the Orlando analysis, usable by asset management, brand and operations teams.
A new visual analytics layer: a monthly scorecard per operator, a portfolio deck for the investment committee and a dashboard of hotels against their tier, built in the platform and shared by link.
Dimension Labs customers include Ralph Lauren, the NBA, Dropbox, Netflix and Disney. The Orlando analysis above, 9,446 public reviews of 45 hotels with an effect and a range for every driver, is the kind of output the agent produces.
FAQ
How do I compare guest reviews across 100+ hotels run by different management companies?
Map every hotel to its operator, brand and tier from your own asset records, label every review from every site with the same fields, and compare each operator's poor-stay rate with what its tier mix predicts. Then look at which failures make up each operator's gap.
How can an asset manager see which operators have the worst guest experience?
Rank operators by the gap between their observed and expected poor-stay rate, with a range on each, not by average stars. In our sample, an operator tied for the lowest raw rate had the third-largest gap once tier mix was counted.
How many reviews does a hotel need before it counts toward an operator's score?
Enough that its rate is not noise. The smallest Orlando Courtyard had 54 rated reviews in 19 months, and its interval ran from 6.4% to 24.4%. Pool hotels with fewer reviews over a longer window.
Does Dimension Labs work when each operator uses a different review or survey tool?
Yes. It takes the raw reviews and survey answers from each source and labels them with one schema, so operators are compared on the same fields whichever tool they use. If you only need to reply to reviews at each hotel, a reputation platform is the simpler choice; which tools hotels use to analyze guest reviews and surveys compares them.
See Dimension Labs for hospitality, or start with one export of reviews and your hotel list. Plans start at $299 a month, with a 14-day free trial.