What time to scan tells you
Time to scan is how long it takes a person to go from noticing a QR code to completing a scan. It captures friction that raw scan counts hide, because people who give up never appear in your analytics.If people must hunt for the code, aim their camera carefully, or retry twice, many will simply walk away.
How to compute time to scan
Time to scan is usually reported as a median, not an average, so one very slow attempt does not distort the result. Median time to scan = the middle value when all timed attempts are sorted fastest to slowest.Illustrative example numbers, not real-world data: in a timed test with 20 volunteers, the middle attempt took 12 seconds. After enlarging the code and improving the lighting, a repeat test showed a median of 7 seconds, which is a useful before-and-after comparison even though the numbers come from a small test.
How to collect the data
Time volunteers with a stopwatch in the real location, or measure the gap between page-load signals if your tooling supports it. Test in the actual lighting and at the actual distance, not at a desk.Keep the raw counts, not just the final percentage. Raw counts let you recompute the metric if you later fix the definition, and they make it possible to spot a denominator problem, such as a week where exposures were estimated instead of counted. Store the counts in one place with the date range, the placements included, and the name of the person who pulled them. That small discipline turns a spreadsheet into an audit trail.
Reading the result
Never judge time to scan as a single number. Break it down by distance, lighting, code size, and phone type. A campaign that looks average overall may be strong in one segment and weak in another, and the fix is completely different in each case. Compare the same placement against its own past, and compare different placements only when their audiences and contexts are genuinely similar. A short trend over four or more comparable periods is worth far more than a single snapshot, because it separates a real shift from weekly noise.Also check the relationship between time to scan and the metrics around it. If scans rise while conversions fall, the new scanners may be less interested visitors, or the landing page may have changed. If cost rises while time to scan stays flat, you are paying more for the same outcome. Metrics make sense in groups, not in isolation, and the habit of reading two or three together prevents most misreadings.