Hospitality industry benefits from prebuilt intelligence and features to extract value from event data faster as the US and other countries continue to recover
PredictHQ, the demand intelligence company, announced it has added Features API to its demand intelligence platform. Now, companies can use prebuilt intelligence and features to include intelligent event data directly in forecasting models. The tool reduces the time it takes to add intelligent event data in a user’s demand forecasting models from months to days. Features API eliminates the need to write code to download large volumes of events into a data lake while keeping the copy of events in the data lake updated. It also ends the step of manually adding features while data science teams spend weeks if not months testing.
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“Features API is a library of features for use in a company’s specific models,” said Campbell Brown, CEO at PredictHQ. “We provide our customers in the transportation, retail and hospitality industries with data fast to help them understand what’s happening in specific locations so they can be proactive and save millions. For example, take the global COVID recovery — as cities continue to work to get back to some form of normal, events are beginning to come back. With our data, we can assist venue customers in these cities. In fact, our data reveals that event volume across the US is on track to soar past the halfway mark this quarter, with event impact hitting 61 percent in August.”
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Additional real-world examples of how our customers use Features API:
- Transportation: Perhaps a ride sharing business finds it is heavily impacted by conferences. The company can use Features API to find the top 25 venues within each of their target cities with the most conferences and focus efforts on those locations.
- Retail: By understanding the ebbs and flows of non-attended, scheduled events such as religious holidays and school holidays by each location, businesses are able to integrate features to ensure sales and marketing are aligned for the potential footfall for each geographic store location. School holidays can cause sharp drops for some stores, and sudden spikes for others, even within the same city.
- Travel/Lodging: Knowing that almost all attended events have an impact on the demand for rooms in a particular city, a hotel is able to integrate the Features API attendance into its revenue management system to find the average attendance rate over the next 90 days.
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