Audience & attendance

What audience signals are for

Ticket counts only tell half the story. You know how many tickets you sold, but a sold ticket is not the same as a face in the seat, and a named order is not the same as the stranger who paid cash at the door. This is the part of Fay that reconciles what you sold with what you actually counted, so the gap between the two stops being a mystery and becomes a to-do list, the guests who were plainly in the room but whom you cannot yet name.

It is not a page of its own. It is a set of computed signals that Fay works out from your real ticket history and one number you supply by hand, then scatters across the screens where they help most, the Events record, the People list, and your Today. This article is the one place they are all defined together.

Audience segments

Every person who has ever attended is placed in an audience segment, worked out entirely from their real ticket history, no-shows do not count, only events they actually came to. The rule runs in two steps. First, recency: if their most recent attended event was more than twelve months ago they are Lapsed, whatever the count. Otherwise the number of distinct events decides, three or more makes a Regular, exactly two a Returning, and a single event a First-timer.

• First-timer: has attended exactly one event.
• Returning: has attended a second distinct event.
• Regular: three or more distinct events.
• Lapsed: a former attendee whose last visit was over twelve months ago.

You will meet these badges on each person’s Attendance tab, and they are what the People list’s Audience filter narrows by, so “show me every First-timer from Saturday” or “who has lapsed?” is one click.

Where the headcount comes from

Almost every number here is derived; the one you supply by hand is the door count. On the event, the Headcount (manual) field is where you enter the number of bodies you counted at the door on the night, a clicker tally, a stub count, a steward’s best estimate. It is the ground truth the rest of the reconciliation leans on. Without it, Fay knows how many tickets you sold but has no idea how full the room really was, so walk-ups cannot be computed at all. Enter it as soon as you have it; even a rough count is worth far more than a blank.

The per-event math

With a headcount in hand, Fay breaks the event down into a handful of plain figures. Each one answers a different question about who was there:

• Ticketed quantity: how many tickets were sold for the event.
• Known attendees: the ticket-holders you can name, because their order is attached to a person.
• Anonymous quantity: ticket orders that sold but carry no person, so you have a seat filled and no name for it.
• Unaccounted: the door Headcount minus the Ticketed quantity, and never below zero: heads you counted beyond the tickets you sold.
• Anonymous walk-ups: the headline figure: anonymous ticket orders plus unaccounted heads, together the full count of people in the hall you have no name for.

Sitting over all of it is the identification rate, known attendees divided by the headcount (or by the ticketed quantity when you have not entered a headcount). It is the share of the room you can put a name to, and it is the number to watch: the higher it climbs, the more of your audience you can actually write to, thank, and invite back.

Where these numbers surface

Because these signals earn their keep in context, Fay shows them wherever the decision they inform gets made:

• The event’s Room tab carries the full breakdown, ticketed, known, anonymous, unaccounted, and walk-ups, topped by a plain-language flag such as “20% unidentified,” the identification rate turned inside out. Beneath it, First-timers at this event names the people for whom this was a first night, each with a Log contact button, because a segment you can only count is worth much less than one you can write to.
• The season page rolls the year up in its Audience card, average fill (counting only the events you produced yourself), New to you this season, and how many of those newcomers have since given, so the season-long picture sits beside the giving one.
• The People list uses the segments in its Audience filter, and each person’s Attendance tab shows their segment badge beside their event history.
• The events table has a Walk-ups column, with a Most flag pinned to the season’s worst offender, the night that let the most people slip through unnamed.

Why the identification rate matters

A low identification rate is not a vanity metric. It is money and goodwill walking out of the hall unremembered, every anonymous walk-up a person who might have become a subscriber, a volunteer, or a donor if only you had a name to write to. The point of the number is that you can move it.

You raise it the same two ways all season. Ticket imports attach names to orders that arrived anonymous, converting walk-ups into known attendees a batch at a time. And merges collapse duplicates, so a stranger’s later, named appearance folds back onto the first time they showed up. Neither changes what happened in the room; both change how much of it you can act on.