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Methodology
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Hopper is mobile travel app that uses machine learning and artificial intelligence along with a historical archive of more than 65 trillion historical flight searches and prices, to predict hotel and airfare prices, then notifies users when it's the best time to book.
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The data utilized for this study comes from Hopper's real-time "shadow traffic" containing the results of consumer airfare searches. Hopper collects, from several Global Distribution System partners, 25 to 30 billion airfare price quotes every day from searches happening all across the web
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The prices reflected in this analysis are Hopper’s “good deal price” which represents what a typical leisure traveler should expect to pay, measured using a “tenth percentile.”
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The spread of the Coronavirus became global news in mid to late January of 2020. To track how demand has changed in the immediate aftermath of the start of this virus, we compare all pricing and search demand trends to the first week in January 2020.
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