Events are major catalysts of business. Even if you’re not tracking them and optimizing for them yet like our customers are, the huge surge in major event cancellations and postponements is hitting businesses worldwide.
PredictHQ aggregates and verifies millions of events worldwide, and ranks them by predicted impact. This means our customers know exactly which events are cancelled or postponed, when they are rescheduled as well as details about the thousands significant and major events that are still planned over the next three months.
Many assume all events have been cancelled. But this is not accurate – the vast majority have been postponed and will be rescheduled once the virus’s trajectory is clearer. For example, looking at one of our categories, of the major and significant Sports events cancelled or postponed in March to May 2020, fewer than 15% have been cancelled with around 85% postponed at the time of writing.
But how much does each event, cancellation and postponement impact locations where you operate? We recently launched our Aggregate Event Impact endpoint to enable teams to instantly see the combined impact of all events over a time period in their key areas. This week, we have updated it to enable you to quantify the impact of cancelled and postponed events.
When we launched this feature last month, it was focused purely on incremental demand so companies could identify their busiest days and weeks in advance. But as we worked closely with our customers as the impact of Covid-19 swept across the world, we realized we could turn it into a powerfully useful tool to track the impact of cancelled and postponed events.
How to use Aggregate Event Impact to understand the total event impact for a location
The Aggregate Event Impact graph allows customers to see the total event impact for a location, such as a city, for a given time period. Simply choose the location and time from the filters to see the data visualized.
For example, let’s take a look at Seattle last year. Here is the Aggregate Event Impact Graph for Seattle, USA, for April to June 2019:
This shows the total impact of all events happening in Seattle per day for this period. The impact figure is based on predicted attendance data, which is derived using many factors including venue capacity, historical attendance, the performers at an event and many other factors. It is not possible to rely simply on a listing of an event to identify the attendance. Using proxies such as the amount of tickets available or the venue capacity to get accurate predicted attendance numbers will be misleading.
The graph allows you to quickly identify peak days where many events are happening, as well as those days with lower demand. For example, on May 28, 2019 there were a number of events in Seattle such as:
- The Northwest Folklife Festival
- The Seattle International Film Festival
- A Texas Rangers vs Seattle Mariners baseball game
- The Annual Meeting of the Consortium of Multiple Sclerosis Centers and many more.
The Aggregate Event Impact value for the whole of Seattle using PHQ Rank™ on that day is around 97,000. This represents the total combined impact of all the events on that day. Please note this is an indicative number, not the exact total of expected attendees.
This value is designed to be used directly into your forecasting models once you have established correlation between your transactional data and our verified events data. Our customers use it to increase the accuracy of their demand forecasting, workforce optimization and dynamic pricing strategies. It will be a key tool for them to adapt their strategies week to week as the coronavirus impact continues, as well as to ensure their 2021 strategies have accounted for the coronavirus anomaly effectively.
How to use Aggregate Event Impact to understand the total impact of event cancellations and postponements
Our team made a series of updates to this tool over the last week, including a filter that allows you to choose cancelled or postponed events to see the total impact of the cancelled and postponed events in the selected time period. This shows the aggregate impact of those events for the original date they were scheduled on. For example, if a major event was cancelled on March the 2nd the AEI value for that day would be 10,000 plus the impact values of the other events. The total shown is the total impact of all cancelled or postponed events that were scheduled to happen on the selected days.
Choosing one of these options will show you the combined impact of all the cancelled and postponed events for the selected location and time period. For example you can see postponed events in Italy over the month of April 2020 at the country level.
Aggregate Event Impact enables you to filter by active, postponed or cancelled, as well as by time, locations as well as as by our rankings, which describe the predicted impact of events.
For example, the combined impact of event postponements in China in February to early March 2020 for events ranked significant i.e. PHQ Rank 60 to 80:
Here is combined impact of canceled significant events in the United States of America for February to early March 2020:
And here is the combined impact of cancellations for events ranked as important (PHQ Rank 40 to 60) in France for February to early March 2020:
Finding postponed and cancelled events with the PredictHQ API
We recently shared a post about how you can find cancelled events in our API. You can also find postponed events with the API too by using the deleted_reason parameter. If you set
deleted_reason=postponed in your query you will get all postponed events. If you choose
deleted_reason=cancelled,postponed then you get both cancelled and postponed events. See our API documentation for more details.
Did you know you can export AEI with our data exporter?
You can also export events into CSV or JSON format with our Data Exporter. In the Data Exporter choose “Deleted reason” of cancelled or postponed (or you can select both). Choose your standard criteria for the location you wish to see and the time period and then export your data.