Predicting Customer Wait Time in the Hospitality Space

Date:

Thursday, June 6, 2024

Time:

2:40 pm

Room:

Phoenix Ballroom A

Summary:

To stay competitive as technology evolves and user interactions become more direct, it is essential to find data-driven ways to continuously improve customers’ experiences. In this talk, we’ll showcase an example of how we helped a company in the hospitality industry employ machine learning models to generate real-time predictions for how long their customers would have to wait for an order. We’ll highlight the components of the solution, which utilizes gradient boosting quantile regression, as well as key data inputs, feature engineering and selection techniques, and model monitoring considerations.

Speakers:

Evan Wimpey

Beyond Bookings: Demand Forecasting for Hotel Success

Date:

Thursday, June 6, 2024

Time:

3:05 pm

Summary:

Maximize occupancy and minimize waste with advanced demand forecasting. This session presents a Python-based approach, incorporating broader economic variables and local events into predictive models for room supply, staff scheduling, and F&B services. We’ll showcase how machine learning goes beyond traditional demand indicators, providing hoteliers with the tools to anticipate fluctuations and make data-informed decisions for inventory and staffing, crucial to thriving in today’s competitive landscape.

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