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FareTrack (Aggregate Intelligence, Inc.) — Continuous scraped/API-captured competitive travel pricing corpus: customer-facing airline fares across GDS, NDC and direct channels plus OTA/metasearch offer data, ancillary fee and fare-family breakdowns, tax/fee splits, historical fare curves (2+ years), 3.5M+ hotel rate series from 100+ sources, car rental rate/ancillary data, and a 10M+ event catalogue with AI demand estimates.. Mid-market specialist DaaS with enterprise-grade coverage: 700+ airlines, 60k+ OD pairs, 3.5M+ hotels, 10M+ events, 201-500 staff, ~10 years of operating history and ong…
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Continuous scraped/API-captured competitive travel pricing corpus: customer-facing airline fares across GDS, NDC and direct channels plus OTA/metasearch offer data, ancillary fee and fare-family breakdowns, tax/fee splits, historical fare curves (2+ years), 3.5M+ hotel rate series from 100+ sources, car rental rate/ancillary data, and a 10M+ event catalogue with AI demand estimates.
Scale Very high: 700+ airlines and 60From 2 yearsCoverage Industrials · Consumer Discretionary
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FareTrack (Aggregate Intelligence, Inc.) — Continuous scraped/API-captured competitive travel pricing corpus: customer-facing airline fares across GDS, NDC and direct channels plus OTA/metasearch offer data, ancillary fee and fare-family breakdowns, tax/fee splits, historical fare curves (2+ years), 3.5M+ hotel rate series from 100+ sources, car rental rate/ancillary data, and a 10M+ event catalogue with AI demand estimates.. Mid-market specialist DaaS with enterprise-grade coverage: 700+ airlines, 60k+ OD pairs, 3.5M+ hotels, 10M+ events, 201-500 staff, ~10 years of operating history and ong…
Faretrack offers (Alternative, Price, Supply Chain, Sentiment) — Very high: 700+ airlines and 60,000+ origin-destination pairs shopped continuously; 10M+ historical events with 70k+ new events weekly; hotel rate monitoring across 3.5M+ properties aggregated from 100+ sources; 2 years of historical fare history; vendor claims it analyses 'millions of data points' per behaviour model..
Airline revenue-management and dynamic-pricing model training; competitor-response and price-elasticity models; demand forecasting with event covariates; ancillary bundling/offer-optimization RL environments; parity-violation and channel-cannibalisation detection; hotel/car-rental revenue models; RLHF-style preference data for pricing agents; benchmark sets for time-series forecasting on volatile price series.
The data is with 2 years of history.
Coverage spans US, UK, Other; Passenger Airlines, Hotels; alternative, price, supply_chain, sentiment; equities.
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