Intelligence · Component · hotel-campaign-spike-detection
Hotel campaign spike detection
What it does
Finds hotel/source segments with elevated orders against two prior windows, joins batched traffic metrics and partner attribution, and exports candidate evidence tables.
Core pattern
Current versus historical windows + anomaly candidate evidence
- Input
- Hotel orders and pageview metrics
- Output
- Candidate CSV and JSON summaries with baseline comparisons
Key parameters
| Name | Type | Default | Values |
|---|---|---|---|
| operation | string | detect | detect · enrich · export |
| windows | object | — | — |
| min_orders | integer | 15 | 1–1000000 |
| min_ratio | number | 1.5 | 0–1.5 |
| event_and_baseline_dates | — | — | — |
Maturity and limits
Parameterized thresholds, SQL builders, batched queries and exact-versus-rollup matching are implemented. Reclassified from Travel/Hotel after reading calculation/SQL code. Source inspected statically; tests and external integrations were not executed.
Selection bias, fallback scope and low baselines; campaign association is not a causal experiment.
1 sentence citing source paths or vendor names omitted for publication.
Used in pipelines
Industry tags
- Travel & hotelsSource-supported industry
For work involving destinations, room rates and bookings, use current versus historical windows followed by anomaly candidate evidence.
- Logistics & supply chainTransferable use
For weekly review of warehouse orders and delivery lead times, use current versus historical windows followed by anomaly candidate evidence.
Skills pack
Contract scaffold and deterministic mock
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