We analyzed this app across 3 independent signals and corroborated nothing unfair. That is a signal, not an audit.
This analysis describes version 26.9.0 of the app, analyzed 2026-10-05 . The app may have changed since.
The store currently lists version 26.9.0, updated 2026-09-08.
What the analysis found
One source only — shown, not confirmed 2
A single kind of evidence. We publish these because withholding them would be the bigger distortion, and we do not treat any of them as a finding we stand behind.
What reviewers said
Verbatim excerpts from public store reviews, shown as corroborating user reports. They are not Appworthy audit evidence, and a quotation is not proof of the finding it sits under.
Reports that the ads misrepresent the app
It’s a scam — I just tried to book 3 hotels. For the first two, when I clicked the button to book it a dialogue popped up saying “the hotel has changed the price” and increased by >$100. but when I clicked back, the original price was…
Bait and switch platform — The platform offers non-cancellable rooms for 2 people but when showing up at the property the rooms are of different class (ex: full size bed instead of queen or king). There is no recourse or support being…
Bait and switch — It’s such a bait and switch. You click a room and every time it says rate has changed. Click to continue.
Reports of unexpected charges
Charged for a room I never got — support refused to help — Booked the Cambria Hotel Philadelphia through this app. Arrived with a confirmed reservation, was told no rooms were available. Never given a room — but charged in full. Then came…
HotelTonight turned an immediate mistake into an appalling customer-service experience — I contacted HotelTonight within minutes of making an accidental booking. Instead of helping, they spent days repeating policy, sending scripted…
Stranded no room — HotelTonight took my money but when I showed up to the hotel, they told me they were already oversold and had no rooms. The app has fraudulent listings and it will completely derail your trip to pay for a room that…
How the automated analysis works
This assessment is produced automatically. Three independent signals are read — user reviews, the store listing and the store privacy disclosure — and each candidate finding is filed under the sources that support it.
No charge stands on one kind of evidence — with one published exception. A finding is either a measured fact that anyone can reproduce (an ad SDK is in the package; every subscription bills weekly; the privacy label omits a tracker we can see), or it is an interpretation — and an interpretation needs independent sources to agree before it reaches the catch list. The exception is a harm only users can see: a charge may publish from reviews alone, as “Reported by N users”, once enough reviewers raise it to clear that charge’s own published bar. That agreement rule is what replaced the human reviewer, not a model’s confidence.
There is no overall score, on purpose. A 0–99 number was published here until 2026-09-15. It was withdrawn because it discriminated too weakly to be the instrument — 44.7% of every pair of apps tied — and because a single number is a verdict where a count is an observation. What publishes instead is a row of measurements, each of which says what was counted and, where we could not look, says that instead.
Findings under One source only are real reports we do not stand behind as findings. They are shown because withholding them entirely would hide a genuine complaint, and labelled because publishing them as charges would be an accusation off a single source.
Several measurements above say “Not assessed” because no artefact we hold can answer them. A human review is what resolves those — and it can remove a favourable band as easily as add one.
Hands-on inspections are not yet open.