Features
Up to five venues side by side
Knowing a competitor sits at 4.7 against your 4.4 tells you nothing. Knowing that waiting complaints are 4% of their reviews and 19% of yours tells you where to go.
What we compare
Up to five venues you name, in the same categories and on the same scale. The comparison runs on the share of reviews mentioning a topic, not on counts and not on ratings. Averages are compared only within the same platform — setting Google and Booking.com ratings side by side would be meaningless.
Categories, not ratings
A category comparison shows what specifically someone does better. An average comparison only shows that they do — and suggests no move at all.
No recommendations
We do not tell you what to do about a competitor. The commentary comes from metrics alone, because advice built on someone else's reviews is guessing at someone else's strategy.
Cost shown before you run it
Every competitor is a separate fetch and a separate classification — one credit each. You see the price before clicking, not after.
Step by step
How the comparison runs
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1
You name the venues
Up to five competitors, each by profile link. You choose them — we do not suggest who your competition is, because that depends on things reviews cannot show.
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2
Fetching and classification
Each venue goes through the same fetch and the same classification as yours. Without that, the comparison would compare two methods rather than two venues.
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3
Setting them side by side on categories
For each category we compute the share of reviews mentioning the topic, per venue. We compare shares, not counts — a busier venue always has more reviews.
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4
Commentary from the metrics
The comparison comes with a description of the differences derived from the numbers alone. No recommendations, because advice built on someone else's reviews is guessing at someone else's strategy.
In practice
The difference the rating cannot show
Two hotels in the same city: 4.4 and 4.5 stars. The category comparison showed that complaints about waiting at reception were 19% of reviews at the first and 4% at the second. Breakfast complaints: 3% and 17%. Almost identical averages, entirely different problems — and entirely different task lists.
19% / 4%
share of complaints on the same topic at two venues with near-identical ratings. The average will not show this, because it averages every topic at once.
Why it works this way
A comparison that points at a move
We set venues side by side on categories and shares, within one platform and on one scale. That way the result says what specifically someone does better rather than merely that they do. "Waiting complaints are 4% of their reviews and 19% of yours" gives you the area and the size of the gap at once. That is a number you can take into a management meeting.
Common questions
Where does competitor data come from?
The same public sources as yours: Google Maps, Booking.com, TripAdvisor, Facebook. We have access to nothing that any visitor to their profile cannot see.
Will the competitor know I am analysing them?
No. We pull publicly available reviews and contact no venue. We leave no trace on their profile either.
How many competitors can I compare at once?
Up to five in one analysis. Above that the comparison stops fitting on a screen and in a head, and differences start disappearing into noise.
See also
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Join the waitlist. We'll write once, on launch day, with a link to create your account.