The findings above come from thousands of real conversations at service
businesses that take enquiries through messengers and social media — across several years of
inbox history, including the period before any automation was in place.
One enquiryA message from a person after a day of silence, not the endless
thread as a whole. Before and after are counted by the same rule on the same account.
Speed is measured to a real answerAutomatic templates are filtered out. We show
the unfiltered version alongside, so the difference is visible.
Speed is read in fullThe typical case, the average and the slowest ten percent.
The losses live in the tail, and the typical case hides them.
Money comes from non-overlapping groupsEach conversation belongs to exactly one
cause, so nothing is double counted. Conversations that went fine are not counted as losses.
Three scenarios, not one numberConservative, base and optimistic, with the
assumptions on conversion and attendance stated openly.
Every figure is labelledMeasured from data, estimated from assumptions, or a
hypothesis. Different kinds are never added into one sum.
Evidence scopeThe conversation findings use anonymised aggregates from roughly
3,500 enquiries across five service businesses, including inbox history from before
automation. The advertising findings use a separate 90-day analysis from 15 May to
13 August 2026 across three service businesses running Meta campaigns optimised for messages.
LimitationsRanges differ by business and period. Bookings are outcomes marked by
the business, so they are a measured floor, not a guarantee. The calculator is an estimate;
your audit uses your own conversations, prices and outcomes.