How it works
From an export you already have to a short list worth reviewing.
Pulse is deliberately narrow: it reads aggregate sales figures, compares them over time and explains every flag it raises.
- 01
Inputs
A per-session (per-performance) export in CSV or XLSX from your box office: session date and time, capacity, confirmed sold tickets and, where your system records them, reservations or holds. Aggregate counts only — Pulse does not need customer names, emails or payment data. Each import is previewed and validated row by row, and nothing is saved until you confirm it.
- 02
Dated snapshots
Each upload is stored as a snapshot with the date and time the export was taken. Comparing two snapshots shows what genuinely changed for each session, rather than a single static total.
- 03
Calculations
Paid occupancy = sold ÷ capacity. Apparent occupancy = (sold + reserved) ÷ capacity. Available = capacity − sold − reserved. Change = this snapshot minus the previous one. Every figure can be traced back to the source rows.
- 04
Sales and reservations, kept apart
Reservations can make a house look fuller than it is commercially. Pulse never merges them into “sold”: they are shown, counted and charted separately.
- 05
The attention queue
Upcoming sessions are ordered by transparent rules, and each flag states which rule triggered it and with which numbers. You can see why a session is on the list. An AI-assisted risk analysis adds a second read on the same evidence, always with the numbers shown.
- 06
Manual decisions
Pulse suggests what to review. Your team decides what, if anything, to do — and can note that decision against the session. Nothing is automated or sent anywhere.
- 07
No ticketing integration
There is no live connection to BOL or any other ticketing platform. Pulse only works with files you choose to export and upload.
Example rules used in the sample
- Near event, low paid sales: event within 10 days and paid occupancy below 40%.
- Occupancy mostly reservations: apparent occupancy at or above 80% with reservations making up 40% or more of it.
- Stale export: latest snapshot older than 7 days.
Thresholds are illustrative and would be agreed with each pilot team.
Data requirements
- One row per session
- Session date and start time
- Capacity (sellable seats)
- Confirmed sold tickets
- Reservations / holds, if recorded
- The date and time the export was produced