Turnout
Verified attendance for recurring events

Don't just fill an event.
Build a crowd that comes back.

Turn RSVPs into verified attendance, understand who returns, and measure what actually improves your next event.

Event room

Community night · March

Interactive demo · Illustrative data

0 Verified attendeeof 90 seats · Checked in at the door
78 Registered, not in yetof 90 seats · Holds a seat; the door has not closed
0 Registered, never cameof 90 seats · Said yes, stayed home
12 Never registeredof 90 seats · A seat you paid for and did not fill
78 people said yes. 12 seats were never claimed at all — that is not a no-show yet, it is an unsold seat.
Explore interactive demoStart with one event

No card. Nothing reaches your guests without your approval. The first import takes about five minutes.

Interactive demo · Illustrative data — 90 seats, 78 registrations, 47 verified attendees.

  • Attendance rate60.3%47 ÷ 78 active registrationsCancellations leave the denominator; no-shows stay in it.
  • Registered no-shows31÷ 78 active registrationsPeople who said yes and did not come. Not an unsold ticket.
  • Capacity fill52.2%47 ÷ 90 seats paid forThis is the seat you paid for and did not fill.
  • Event-one attendees who returned70.2%33 ÷ 47 identified attendeesMeasured on the people who came to the first event, not on everyone who registered later.

Interactive demo · Interactive demo · Illustrative data

See what happens across two events

What the organizer starts with

Step 1 of 5: Event one

An organizer opens the season with 90 seats and 78 registrations. That is the number they will report to a sponsor — and it is not the number of people who will be in the room.

90Seats paid forthe room
78Registrationspromises on a list
47Verified attendancethrough the door
31Registered no-showssaid yes, stayed home
12Never registeredseats nobody claimed
Registered 100% of the room
Actually came 60.3% of registrations

47 ÷ 78 = 60.3% attendance rate · 47 ÷ 90 = 52.2% of the seats you paid for.

Step 1 of 5

Illustrative data, fixed in the page: Mar through Aug. Nothing here is a real organizer's roster, and no number on this page is read from a customer account. Real figures appear only inside the account that owns them.

The retention flywheel

A single event is a project. A community is a loop — and every turn of it is measurable.

1Invite2Register3Attend4Return5Improve6Next event
  1. 01InviteImport the list, open an RSVP page
  2. 02RegisterEvery response carries consent and source
  3. 03AttendQR or manual check-in at the door
  4. 04ReturnMatched by email across events
  5. 05ImproveReminder tests, risk bands, timing
  6. 06Next eventThe roster starts warmer than last time

What the product proves is measured, not promised: it tells you which stage leaks, and how many people came back. Whether your community returns is the organizer's work. Interactive demo · Illustrative data.

What does an empty room cost?

Your numbers, your assumptions, four quantities kept apart — and the sample size that would be needed before anyone called an improvement proven.

300
255
60%
$45
$2,000
+5pp

Starting attendance rate 60% is the rate measured on the demo event (47 ÷ 78, Interactive demo · Illustrative data). Move it to your own history — nobody else's average is your baseline.

Expected attendees153255 registrations × 60%
Expected no-shows102255 − 153 · registered and absent
Seats never registered45300 − 255 · unsold, not a no-show
Seats you pay for and do not fill147300 − 153 · no-shows plus never-registered
Conditional economic exposure$6,615147 unfilled seats × $45 per attended guest. This is exposure, not lost revenue: with prepaid tickets the ticket money is already yours, and an unsold seat never had a buyer.
Break-even attendance on fixed cost45$2,000 fixed ÷ $45 per guest · $13 of fixed cost per attended guest at the expected rate

Hypothetical scenario · +5pp attendance (not a Turnout result)

13 more people in the room, $585 more guest value per event.

Nobody has measured this uplift. It is the size of the prize, and the reason the pilot is worth running: proving a 5pp change at 60% baseline needs about 1,470 participants per arm — roughly 2,940 people randomised across two groups.

The formula, and what each line assumes
  • Expected attendees = registrations × expected attendance rate, rounded to a whole person.
  • Unfilled seats = capacity − expected attendees. It counts both registered no-shows and seats nobody ever claimed; the panel above keeps those two separate.
  • Conditional economic exposure = unfilled seats × net value of one attended guest. It assumes the value you entered is per attended guest and that it would have been realised; it is a scale, not a loss.
  • Break-even attendance = fixed cost ÷ value per guest. Below that number the event does not cover its fixed cost at the value you entered.
  • Hypothetical scenario = the same registrations at a better rate. It is arithmetic, not a measurement, and the sample size shown is what a real test would need.

Who comes back, and to which event

Each row is a cohort of first-time attendees. Each cell is that cohort in a later room. Denominator: the row's own size, never “everyone who ever registered”.

Cohort retention matrix. Each cell shows attendees from that cohort and their share of the cohort (Interactive demo · Illustrative data).
CohortSizeMarAprMayJunJulAug
First seen in March4747100% 47 of 47 returned3370% 33 of 47 returned1940% 19 of 47 returned1634% 16 of 47 returned1430% 14 of 47 returned1328% 13 of 47 returned
First seen in April23·23100% 23 of 23 returned1252% 12 of 23 returned1148% 11 of 23 returned1043% 10 of 23 returned939% 9 of 23 returned
First seen in May31··31100% 31 of 31 returned1961% 19 of 31 returned1755% 17 of 31 returned1548% 15 of 31 returned
First seen in June22···22100% 22 of 22 returned1359% 13 of 22 returned1255% 12 of 22 returned
First seen in July18····18100% 18 of 18 returned1161% 11 of 18 returned
First seen in August14·····14100% 14 of 14 returned
In the room475662687274
Registered788486888990

Reminders: the experiment, not the promise

Reminders are the part of this product most likely to be oversold. So they are shown as tests, including the one that went the wrong way.

Community night · March

Does one extra reminder 24h before the doors open move attendance?

NO DETECTABLE DIFFERENCE
Who was in the test
All 78 active registrations, randomized 1:1 at import.
What the treatment was
One SMS-shaped nudge, sent 24 hours before the start time.
Who sends it
Nothing is sent without an organizer approving the message plan first.
Control56.4% n=39

95% interval 41.0% – 70.7%

Treatment64.1% n=39

95% interval 48.4% – 77.3%

+7.7pp difference (treatment − control), p=0.49. Difference is not statistically significant at alpha=0.05.

At this baseline, detecting a 3pp change at 80% power needs roughly 4,250 participants per arm. Until an organizer runs that, the honest answer is “not proven” — and the product says so instead of shipping a claim.

Community night · July

Does a same-day reminder help the people who registered late?

INSUFFICIENT EVIDENCE
Who was in the test
The 16 late registrations of the July event only.
What the treatment was
Same-day reminder at 09:00.
Who sends it
Nothing is sent without an organizer approving the message plan first.
Control62.5% n=8

95% interval 30.6% – 86.3%

Treatment50.0% n=8

95% interval 21.5% – 78.5%

-12.5pp difference (treatment − control), p=0.61. Sample too small for a reliable test (control n=8, treatment n=8; need n>=30 per arm and >=5 expected in each cell).

At this baseline, detecting a 3pp change at 80% power needs roughly 4,020 participants per arm. Until an organizer runs that, the honest answer is “not proven” — and the product says so instead of shipping a claim.

Interactive demo · Illustrative data · experiment design shown as the product records it.

How an event runs

Four steps, in the order an organizer actually does them.

01

Import or collect RSVPs

CSV import with duplicate detection, or a public RSVP page for open events. Consent and source are stored per participant, so you can always answer where a list came from.

02

Approve a reminder plan

Rule-based risk bands decide who gets one, two or three touches. Nothing is sent until an organizer reviews and approves the plan — in this build, nothing is sent at all.

03

Check in at the door

QR or manual check-in, idempotent and audited, so a double scan cannot inflate the room. Walk-ins are recorded as their own category.

04

Measure what happened

Attendance rate, no-show rate, capacity fill and repeat attendance — four metrics, four denominators, plus a control-versus-treatment comparison for the reminders you tried.

Why attendance intelligence matters

The five questions anyone asks before writing a cheque, answered with what exists today.

01

What is the real problem?

Recurring event organizers run on registrations, because registrations are the only number their tools produce. The number that decides whether the event was worth holding is attendance — and the gap between the two is invisible until somebody stands at the door and counts.

02

What does Turnout do differently?

It treats the door as the source of truth. Registrations are imported, check-in is recorded, and every rate on the dashboard divides by a denominator that is printed next to it. Attendance, capacity fill, no-show and repeat attendance are kept as four separate metrics instead of one flattering number.

03

How does the product work?

Import a roster or open an RSVP page, let rule-based risk bands propose a reminder plan you approve before anything is sent, check people in by QR or manually, then read who came and who came back. The same roster carries into the next event, which is where repeat attendance becomes visible.

04

What is already proven?

The measurement pipeline: import, check-in, and the metric functions behind every figure on this page ship with the product and are covered by tests. The comparison framework runs control against treatment inside a single event and refuses to declare a result on a small sample. The reminder lift itself is not proven, and the page says so.

05

Why would an organizer come back?

Because the second event is where the tool pays: the roster is already there, the reminder plan is a two-minute approval, and the repeat-attendance number answers a question they have never been able to answer before. A one-off organizer churns; a community with a monthly cadence has a monthly reason to log in.

Why this is a subscription, structurally

  • Value compounds with the event count: one event gives a rate, three give a trend, six give a cohort matrix.
  • The roster is an asset that lives in the product, not in a spreadsheet that gets re-imported.
  • Reminder experiments can only conclude over months, which rewards an organizer who keeps the same tool running.
  • Recurring communities already pay for venues, catering and promotion on a cadence — the subscription rides an existing budget line rather than asking for a new one.

What this page does not claim

  • No market size, revenue, LTV, CAC or profitability figures — there is no such data yet.
  • No customer logos or testimonials: no signed organizer has agreed to be named.
  • No claimed attendance lift from reminders. The framework reports insufficient evidence, and that is what it reports here.
  • No autonomous sending in this build: reminders are queued for organizer review and approval.
  • No real organizer's data anywhere on this page. Every figure is the fixed illustrative dataset, labelled as such.

For a fuller picture — architecture, metric definitions, the test suite and the experiment design — the product itself is the document: the same numbers run inside /app on data the organizer owns.

What this build does not do

  • No payments, no subscriptions, no Stripe Connect.
  • No real email or SMS delivery — reminders are queued for review only.
  • No claim of a proven attendance lift. The experiment framework reports INSUFFICIENT EVIDENCE until the sample supports a conclusion, and the page repeats that verdict instead of rounding it up.
  • No integrations with Eventbrite, Meetup or Luma APIs.

Where the numbers come from

  • Every figure on this page is the fixed illustrative dataset in src/lib/demo/model.ts, labelled Interactive demo · Illustrative data.
  • The four rates are computed by the same pure functions the organizer dashboard uses (computeEventMetrics, computeRepeatStats, compareArms), and their arithmetic is covered by tests.
  • Real attendance appears only inside the account that owns it. This page never reads a customer's roster, and the hero is not wired to the latest production event.
  • Page interactions record counts, not people: five first-party events, no cookies, no third-party script, and Do Not Track is honoured.

Start with one recurring event

Import last month's list, approve the plan, check in once. If the numbers do not tell you something you did not already suspect, stop there.

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