As summer interns here at Minitab (collectively grateful for this amazing opportunity!), we were challenged with solving a problem: “How do we harness our analytics skills to help our marketing team drive higher attendance to events, webinars, etc.?”
The Minitab team does a great job of creating webinars and events on different, engaging topics that drive significant interest. Compared to industry standards, Minitab does a stellar job of converting registrants for webinars and regularly has high turnouts at events. As part of its commitment to continuous improvement, we were tasked with helping the marketing team improve.
Under different circumstances, the most critical factors for attendance are content, speakers, and costs. As Minitab Exchanges are complimentary (and coming to a city near you!) - not to mention chock full of great content and speakers – we used a Mind Map from Minitab Workspace to brainstorm reasons why not every single registrant was turning up.
As weather is clearly out of event organizer’s control and time of day and location were presented at the time of registration, we decided to dig in to understand if the time a registrant signs up for an event affects that registrant’s likelihood of attending the event. Furthermore, how can such findings be used to ensure greater success and attendance at future events?
To answer this question, we employed CART® which is a simple and intuitive predictive analytics tool included within Minitab Statistical Software, which provides us with an explainable solution in the form of a decision tree diagram.
First, we prepared the data by creating a variable named “days” that numerically quantified the duration of time between date of sign-up and the event. After we combined the data from multiple locations, we simply let CART® do the rest and this is what we found.
Out of the 134 registrants, when someone signs up more than roughly 44 days (about 1 and a half months) before the event, the attendance rate is 16.7%. Compared to their counterparts who sign up less than 44 days before, we see that these attendees follow through at a much greater rate of 48.1%. The analysis illustrates that when a participant signs up, it does in fact impact the likelihood that they will attend the event. So how can our findings be used to improve attendance rates?
We wanted to come up with a tangible and practical solution for this attendance problem (that doesn’t just prohibit signing up more than 43.6 days prior!). How can we effectively increase the attendance rate of 16.7%?
To improve engagement, we propose marketing communicate more with participants who sign up over a month and a half prior to the event. This can be done via increased frequency of calls, texts, emails, or even through a raffle that occurs the day of the event to further solidify attendance.
We believe that these conclusions can be universally applied to those anywhere who are looking to guarantee greater attendance at events of any size. Thanks to predictive analytics tools within Minitab Statistical Software, we were able to create a concrete data driven solution to this problem!
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