Clean the list
Remove bad records, suppress do-not-contact names, then segment the old estimates by age, service type, value, and last contact.
Explore a hypothetical old-estimate scenario. The prefilled numbers are examples, not a forecast or evidence that a follow-up campaign will work.
Actual results depend on list quality, customer timing, pricing, follow-up quality, service area, and owner follow-through. No passwords are needed for the first review; a CSV, spreadsheet copy, or small non-sensitive sample is enough to start.
Remove bad records, suppress do-not-contact names, then segment the old estimates by age, service type, value, and last contact.
Use small batches and plain language. The point is to reopen a conversation, not pressure people who have moved on.
Every reply needs a next step: booked, call needed, not interested, do not contact, or follow up later.
The $197 AI Leak Scan verifies whether the estimate list, consent boundaries, reply history, and follow-up gaps justify a larger recovery workflow.