Where the data comes from
Every figure is computed at page-render time from the live TripQuest production database — quest definitions, quest runs, and venue check-ins. Nothing on this page is a hand-entered or snapshotted number. The page re-reads the database at most once an hour.
Check-ins
A check-in is recorded when an explorer confirms arrival at a partner venue during a quest, either by scanning the venue’s QR code or by confirming on location. Counts are of check-in events, not of people.
Quest runs and completion rate
A run is one explorer starting one quest. It counts as completed when all stops are finished and the run is closed out. Completion rate is completed runs divided by started runs; runs still open are counted in the denominator.
Engaged downtown time
Summed from the gaps between consecutive check-ins on the same walk. Gaps longer than 90 minutes are discarded, because a quest can be paused and resumed days later — counting the raw first-to-last span would book overnight hours as downtown engagement. This is the same definition the in-app business analytics use, with the pause rule added.
Times and days
All times are Central time (America/Chicago). The heatmap buckets each check-in by its local day of week and hour.
Beta cohort
This is early-stage field data. The activity shown was generated by a closed beta cohort of 14 explorers walking 48 quest runs between Jul 6 and Sep 23, 2026. Figures are reported as totals of activity, not as estimates of public demand, and should be read as evidence that the collection method works rather than as a measure of program reach.
What we deliberately do not publish
- Anything identifying. No name, account, email, device, photo, or GPS coordinate is read to build this page. The explorer count above is a cardinality — a count of distinct accounts — and is the only place any person-level figure appears.
- Per-venue visitor headcounts. Venue figures are check-in counts only. At this cohort size a per-venue headcount would frequently be a single person, which is an individual record wearing an aggregate’s clothes.
- A state-by-state explorer split. Most of the cohort walked in both states, so splitting the headcount by state would count the same people twice.
- Distance walked. Raw GPS path length is dominated by receiver jitter while standing still and by travel between sessions; summing it naively produces figures off by more than an order of magnitude. Until that pipeline is smoothed and validated, engaged time carries effort instead.
- Trail-derived dwell detection. Only a handful of runs recorded a dense enough GPS trail to support it, so a cross-city dwell figure would be built on two cities and presented as four.
Roadmap
Shielded computation with zero-knowledge-proven aggregates is on the roadmap and is not implemented today. This page protects privacy by never reading personal fields in the first place, not by cryptography.