More ways to access Predicted Event Spend figures in our platform
While still in its Beta phase, we’ve made Predicted Event Spend (PES) figures available via our Events API, Snowflake, and Amazon Data Exchange. If you are already using any of these in your own environment, you will start seeing PES figures straight away.
PES is a dollar figure that reflects the predicted amount of spend in a specific area as a result of a major event. It is a useful indicator for the consumer spend impact events can generate on nearby businesses. Currently, we cover three spend categories:
Transportation (ground-based only, rentals and parking are being considered separately)
What makes PES a useful indicator for consumer spend?
Predicted attendance numbers for events aren’t always created equally. For example, certain types of events may attract more out-of-state visitors than others, meaning the impact on accommodation demand may be higher.
An event with 50,000 attendees in the middle of a city will generate more spend for bars and restaurants nearby, than an event of equal attendance held in a small town where there are fewer amenities available.
Our Predicted Event Spend calculations factor all of this in, including having local price points for more than 7,000 locations worldwide – which provides an entirely different lens when it comes to event selection, relevance, and significance to your business.
We encourage you to check predicted event spend out and to please reach out to our team if you have any questions. In the meantime, we’re busy working on the next fully-featured release of Predicted Event Spend which will include:
Aggregation and contextual logic, allowing you to see the total spend across an entire city, state or country. This comes with built-in intelligence to factor in share of wallet – as consumers have a limited budget, and they aren’t going to spend it everywhere!
Historical pricing and inflation calculations
Additional improvements to the spend calculations, such as length of stay predictions, surge pricing, and more.
