Airbnb review analytics for multi-unit hosts
Spot recurring Airbnb issues early—check-in confusion, cleanliness drift, amenity complaints—using aspect trends, search filters, and unit-level comparisons.
Key Highlights
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Sentiment & trends
- See tone per review, then track it over time. Catch quiet drift before it becomes a pattern.
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Rental aspects
- Track cleanliness, check-in, communication, location accuracy, value, and amenities.
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Unit-level analysis
- One unit can drift while your overall rating looks fine. See patterns by property/unit.
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Search & filter
- Search for a phrase, filter to a unit, narrow to the last two weeks. Validate suspicions fast.
Example investigations
Check-in confusion rising
More mentions of "lockbox", "code", "keys", "couldn't get in". Filter last 30 days, search these terms, compare to previous period.
Cleanliness in one unit
One unit has a different cleanliness story. Filter to that unit, search "dirty", "smell", "hair", compare to similar units.
What Reviato extracts from Airbnb reviews
Sentiment
See the tone per review, then track it over time. A portfolio can hold its rating while sentiment quietly drifts.
Aspects
Cleanliness, check-in, communication, location accuracy, value, amenities. Separate "one-off" from "systemic."
Word maps & key terms
Make repetition obvious. If "lockbox" suddenly appears everywhere, something changed.
Entity extraction
What guests name directly—AC, Wi-Fi, parking, metro, "the cleaner"—so you track what gets mentioned.
Frequently Asked Questions
Related Pages
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Multi-platform review aggregation across Google, OTAs, and social
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Facebook review analytics and sentiment trends
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Catch patterns before they spread
Spot recurring issues early—by unit, by time window, and by theme.