Quote follow-up gets missed when requests, estimates, site notes, customer replies, and timing all live in different places. The useful first step is not an autonomous sender; it is a clear queue of who is waiting and what needs review.
What the assistant prepares
- A queue of open quotes grouped by age, stage, and next action.
- The latest customer request, estimate note, or missing-info item beside each quote.
- Reminder drafts for quotes that are ready to nudge.
- Questions that need a person before follow-up, such as price, scope, timing, or availability.
- A simple daily or weekly review list so the owner can approve, edit, or hold.
What stays human-approved
Prices, discounts, availability promises, scope changes, customer-facing sends, and record changes stay approval-gated. The assistant prepares the work; the business owner or team lead decides what goes out.
Good first workflow
- Pick one source: quote tool, inbox, spreadsheet, CRM export, or form submissions.
- List open quotes and the latest known customer status.
- Mark what is ready to follow up and what needs more information.
- Prepare safe reminder drafts for the ready items.
- Review and approve the queue on a set cadence.
Common questions
Can an AI assistant follow up on quotes?
Yes. The safest first version prepares a queue, source context, and draft reminders so a person can approve follow-up before it is sent.
Should quote follow-up be fully automated?
Usually not at first. Pricing, scope, availability, and customer-facing promises should stay human-approved until the workflow is narrow and trusted.
Next step
Bring one real example of the workflow. Durable Assistant will map what can be prepared, what source information matters, and what approval boundary keeps it safe before anything customer-facing changes.