Staff segmentation
Staff segmentation is the process of separating employees from customers in the count by training the AI to recognise a distinctive visual cue — typically a uniform, polo, apron or lanyard.
Staff segmentation is the process of separating employees from customers in the count, so that footfall, conversion, dwell and area metrics reflect only genuine shoppers. Aura Vision does this by training the AI to recognise a distinctive visual cue worn by the team — typically a branded uniform, polo shirt, apron or lanyard.
How the cue is set
During onboarding, the setup team fine-tunes the model on sample images of your team wearing the chosen cue at the store. From that point on, anyone in view wearing the cue is classified as staff and excluded from customer-facing metrics; anyone without it is counted as a customer.
The cue is tuned per store, so a brand running different uniforms across regions can have each location calibrated independently. It works best when it contrasts clearly with everyday clothing — a white lanyard against a white shirt is harder for the model to lock onto than a coloured one.
If the uniform changes, or staff are temporarily out of uniform, the model needs a re-tune to maintain accuracy. See How accurate is Staff recognition? for the 99% accuracy figure and the conditions it depends on.