When organizing free events (which require some kind of registration but visitors don’t have to pay for entry) there is always a number of people that register but does not show up for the event. This may cause some inconveniences for the organizers:
- They need to plan enough space to fit everybody in the room
- At the same time, they should ensure that they don’t book too big event space that they won’t be able to fill
- If there is catering (which is often the case) it should be ordered in advance, therefore it is important to have good estimation how many people will show up in order to ensure that nobody stays hungry but also that you won’t throw away a lot of food (Yeah, save the planet!!!)
- There are also other resources like security, permits, equipment, number of staff to help at the event, etc. that may depend on the number of people that will visit the event.
- As everybody knows, there is not a free lunch, so the costs for each free event are paid by somebody. These are usually the sponsors. The more visitors are planned for the event, the higher the costs are. If many people don’t show up, the money spend for them (catering, room capacity, any give away goodies, etc.) are kind of a loss that doesn’t make sponsors happy.
We may add few more points above, but let’s focus on the main topic.
It is clear that proper estimation of the number of visitors that will be present at the event is very important. Based on discussions with many event organizers and of course own experience, here are few tips for dealing with no-show rates.
Overage no-show rate
When it comes to no-show rate, there is one magic number – 40%. This means that if 100 people registered for your event, most probably only 60 of them will show up and 40 won’t come. This number may vary, depending on the size of the event, the location, other competing events and even the weather outside, but generally, you can expect 40-50% no show rate, in the general case for free events.
Therefore, if you are new to the event organization and don’t have other metrics, use the one above and you will be on the right way. Below are few tips that may help you to improve this number with few percent, but you shouldn’t expect miracles here.
Send a reminder before the event
If you have announced the event long in advance, there is a chance that few of the people forgot about their registration. Sending a reminder to the people the day before to change their RSVP if they don’t plan to come may help you to get more precise number and also remind about the event to those that forgot it.
Avoid collisions with similar events
Having another event on the same or very similar topic and at the same time as yours may compete with yours for the same audience. Keeping an eye on such events and avoid scheduling yours at the same time, will help you to avoid unexpected drops of visitors.
Ban of people after several no-shows
Not recommended since it won’t really work. Feedback from organizers experimenting with different approaches including this one, shows that warning people that they may be banned, doesn’t have significant effect on the no-show rates. On other hand, if you do ban people, you risk losing valuable members of your community simply because they missed your event due to unexpected circumstances.
Keep statistics about the visitor rate
Statistics are your best friend! Keeping track of the number of people visiting the events compared to the ones that registered for them is the best way to ensure good estimations in a long term. Tracking these numbers will give you a good idea about the no-show rate for your events and will allow you to plan accordingly.
This is probably the simplest and most efficient way for planning the number of visitors. It won’t change your no-show rate but will help you to predict it. The best thing is that it only takes few minutes to count the people in the room.
For those of you who like graphics, Mihael Ankerst did some analysis and created interesting visualization of the attendance record of Data visualization meetup in Munich. And in case you like to create similar visualizations, you can find the source code on GitHub.
