A heatmap is a visualisation that shows where activity concentrates in a space over time, by overlaying a colour gradient — hot where people spend time or pass often, cool where they don't — on the camera view or a floor plan. It aggregates many people's movement into one picture of how a space is actually used, which is why it is a staple of retail and facility analytics rather than a real-time alerting tool.
Its value is in patterns, not individuals. A retailer uses heatmaps to see which displays draw attention, which aisles are dead, and how a layout change shifts traffic; a venue uses them to understand flow and dwell. Because it is built by accumulating movement or dwell over hours or days, a heatmap is inherently aggregate and anonymous — it shows where people went, not who they were — which keeps basic heatmapping on the lighter side of the privacy line, akin to anonymous counting.
The pitfalls are misreading the data and assuming anonymity is automatic. A heatmap shows correlation, not cause — a hot spot might be a popular product or just the only path to the exit — so it informs decisions rather than dictating them, and camera placement and perspective distort it if ignored. And while aggregate heatmaps are anonymous, generating them from individually tracked or re-identified paths means the underlying processing is still personal data even if the output is a blur, so the privacy assessment follows the pipeline, not just the final image. Use heatmaps for layout and flow insight, keep the underlying processing minimised and anonymous, and interpret the colours with the camera geometry in mind. This is engineering guidance, not legal advice.
