What tailgating looks like in practice
The typical form is two people entering on one card: a member badges in and opens the door, and a second person steps in before the door closes.
In GymPlus network data, around 97 percent of detected tailgating events are pairs like this. Larger groups happen but are rarer.
Tailgating is not always intentional. Sometimes a member holds the door open out of politeness, not realizing the situation is an unauthorized entry.
What it costs the gym
One person regularly tailgating in, for example twice a week without a membership, represents around 2,400 euros of lost membership revenue per year if the standard monthly fee is around 100 euros.
Ten such people per gym is already a meaningful sum, and based on network data this is the reality at a mid-size unstaffed gym.
How it is detected
Pure access control does not detect tailgating, because from the system's perspective one card was read, everything looks correct. Detection needs a second data source: camera surveillance combined with computer vision that can count people through the door and compare against the card-read events.
Modern systems validate detections with AI. The initial detection is filtered by a second model before an alert is raised, which cuts false alerts to a fraction.
In the GymPlus system, AI validation filters around 62 percent of preliminary events, and only confirmed events reach staff.
What to do after a detection
A single event rarely warrants a conclusion. What matters is per-member recurrence: if the same membership card is repeatedly the source of tailgating events, it is likely a deliberate pattern of unauthorized entry that can be acted on.
A good system keeps a per-member event history and flags when a threshold is exceeded. The response can be a reminder to the member, a conversation, or in the end a reassessment of the membership.