We do the science on how people pick seats.
Whether it's for events at concert halls, movie theaters, sports venues or on the plane, everyone has their particular way of choosing seats and maintaining sufficient personal space. We develop models psychology-based data science models to predict consumer preferences.
When reserved-seating venues reopen, they will need to enforce seatmaps to follow social-distance guidelines. Locational choice experiments conducted on nationally representative panels can allow you to understand how consumers will pick seats, and which room designs will lead to the highest occupancy.
Consumer preference for seats differ widely. We have developped data science models for recommending specific seats that lower non-purchase rates and maximize occupancy.
Our work on predicting locational choice benefited from a grant of the Marketing Science Institute. [Access Report]
Our research has also received a grant from Penn State.
We have also received the support of the Natural Sciences and Engineering Research Council of Canada (NSERC).
Ever wondered how consumers would react to fewer rows, blocked out seats or VIP pricing? Using our software backend, create and test ways to present seat maps with large representative panels. Configurations are customizable.
Consumer preference for seats differ widely. We have developped and compared models for recommending specific seats to consumers based on experimental and real ticket purchase data.
We have made available locational choice experiment datasets, R and Python codes for analysis (1) (2), and provided a sample interface for locational choice experiments. If you have questions or would like to know more about how we can help, send us an e-mail via the form below.