One of four · The audience pipeline

The half of your audience nobody has ever written down

Every other donor database starts the moment somebody gives you money. Fay starts one step earlier, at the door, because the people who will give you money next year are sitting in the room tonight, and right now you cannot name them.

A sold-out night at a small chorale looks like this on paper: three hundred people, two hundred and ninety-one tickets, and a hundred and forty-two names. The other hundred and fifty-eight bought at the door, or came on somebody else's booking, or were given a seat by a singer. They watched your concert, they clapped, and they went home without ever entering your records.

That is not a data problem. That is next season's donors, walking out unrecorded.

Fay puts the number on the page instead of quietly dropping it. Every event shows what it knows, what it does not, and the gap between them.

How it works

Upload, look, then commit

Five steps, one of which is you reading a page. Nothing reaches your database before that page.

The preview

Nothing is saved until you have seen what will happen

Export from Eventbrite, TicketTailor, TicketSource, Square, or any spreadsheet with a column mapper. Fay reads every row, sorts it, and shows you the outcome as a sentence you can check.

  • Matched, never duplicated

    A repeat buyer stacks under the name you already have. Their fourth concert joins their first three instead of creating a fourth Rebecca Alvarez.

  • Idempotent by design

    Upload the same file twice and the second one changes nothing. Every row keeps its original box-office order id, so a re-import is a no-op rather than a mess.

  • Anonymous rows counted, not invented

    A row with no usable name is skipped and reported, never turned into a ghost record with a blank surname. Rows are never half-imported.

Identity resolution

Aggressive suggestion, conservative action

Fay will look for every possible connection in your data. It will act on exactly one of them by itself.

The evidence is named, same address and same last name, and so is what each person is worth to you, because that is what makes the decision answerable in three seconds.

The one automatic case

An exact email match whose name also agrees is the same person, and Fay treats it as such. That is the entire list of things it decides without you.

The case it deliberately refuses

A shared family address like [email protected] with two different first names is exactly where naive matching destroys a donor record. Fay flags it and waits.

Merge and link are different things

One human recorded twice is a merge, leaving one survivor and a tombstone so old links still resolve. Two humans in one family is a household, where both survive and their giving rolls up.

A dismissal is permanent

Tell Fay two people are unrelated and it never asks again. A queue that re-suggests what you have already rejected is a queue you stop reading.

The result

One table of people, whatever hat they are wearing

A singer, a board member, a ticket buyer and a donor are constantly the same person. Fay keeps one record and hangs dated roles off it, so nobody has to remember which list somebody lives on, and the page remembers how they arrived in the first place.

  • Attendance becomes a lifecycle

    First-timer, returning, regular, lapsed, all worked out from real attendance every time you look, never from a field somebody forgot to update.

  • Consent travels with the record

    Marketing opt-in comes across from the ticketing platform with its source and timestamp attached, so you can always answer how you came to have permission.

Next: those newly-named people start giving you money, and the clock on saying thank you starts the moment they do.

Thanking every gift on time →See what it costs