Why reviews are the ultimate feedback loop

88 % of guests read at least three reviews before booking (AirDNA, 2025). Mining them manually is time‑sucking and error‑prone.

Pipeline breakdown

1. Data ingestion: pulls Airbnb reviews nightly via official API.
2. Sentiment engine: hospitality‑fine‑tuned BERT labels each sentence (positive/neutral/negative).
3. Topic clustering: BERTopic groups phrases into themes (cleanliness, noise, location).
4. Trend detection: STL decomposition surfaces abnormal spikes.
5. Action link: negative clusters ≥ 3 frequency auto‑spawn AI Tasks.

Case study: beachside duplex

Issue: recurring “musty smell.”
Analyzer flagged “smell” cluster ↑ 300 % week‑over‑week.
AI Task auto‑created HVAC filter replacement. Post‑fix, negative mentions dropped 95 % and occupancy rose 8 % in shoulder season.

SEO tip

Extract the “Top praise” list and paste into your listing description—instant conversion boost.

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