Quotes go out and then go quiet. Following up by hand is easy to forget during the busy season, and generic reminder templates don't sound like you. Short answer: use Jobber (Copilot + AI Receptionist), ChatGPT. The workflow has 7 steps and 3 copy-paste prompt(s); expect two reusable follow-up templates in your voice, a personal-note prompt for big jobs, and a simple monthly check on what's working. Main caution: Vendor descriptions are the vendor's own claims; we have not tested the product.
The problem
Quotes go out and then go quiet. Following up by hand is easy to forget during the busy season, and generic reminder templates don't sound like you.
All tools mentioned
Step-by-step workflow
- Pull the list of quotes still waiting on a reply from your software, with the client's name, what you quoted, the date sent, and any note from the site visit.
- Gather three or four follow-up messages you have actually sent that got a good response. These are what the AI copies your tone from.
- Use the first prompt to write a short first follow-up and a second, later one. Keep each to a few sentences and give the client one easy next step (a call, a text back, or approving online).
- If you use Jobber, its own help docs describe two automatic quote follow-ups by email or text, sent a set number of days after the quote (up to 90), on the Connect plan and up. Paste your AI-written wording into those templates so the automatic reminders sound like you.
- On Jobber's Grow plan, its help docs describe a custom automation builder that can add more follow-ups or tailor messages, for example by tagging high-priority clients.
- For big or custom jobs, skip the template: use the second prompt to draft a personal note that mentions something specific from the site visit, then send it yourself.
- Once a month, look at which quotes were won after a follow-up and which went cold, and adjust timing and wording.
Copy-paste prompts
Here are 3 follow-up messages I've sent to landscaping clients that got good replies [paste]. Match their tone and length. Write two follow-ups for quotes that haven't been answered: one for [X] days after sending and one for [Y] days after. Each should be under 60 words, mention [service type], give one easy next step [call / text back / approve online], and not sound pushy. Use [client first name] and [quote name] as placeholders.
Write a short personal follow-up to [client] about the [project] quote I sent on [date]. From the site visit: [details, e.g. their worry about drainage by the patio]. Mention that detail, offer to walk through the quote by phone, and keep it under 80 words. No discounts or deadlines unless I add them: [ ].
Here are my quotes from last month with outcome and whether a follow-up was sent [paste]. Which follow-up timing and messages seem to go with won quotes? Treat this as a hunch to test, not a conclusion, since the sample is small.
What to expect
Two reusable follow-up templates in your voice, a personal-note prompt for big jobs, and a simple monthly check on what's working.
Limits & safety
- Vendor descriptions are the vendor's own claims; we have not tested the product.
- Read every AI-written follow-up before it goes into an automation; a template sends the same words to every client.
- Only send automatic reminders to clients who agreed to get them. Jobber's docs say follow-ups go only to clients who have outstanding quote follow-ups turned on in their communication settings.
- Don't let AI add discounts, deadlines, or promises you didn't approve.
Source / inspired by
- Automations: quote follow-ups — Jobber Help Center (vendor docs). Two automatic quote follow-ups, sent by the same method as the quote, up to 90 days after sending; Connect plan and up. Summarized in our own words.
- Custom Automation Builder — Jobber Help Center (vendor docs). Describes adding more quote follow-ups and tailoring messages for VIP clients. Summarized in our own words.
- Aspire 2027 Commercial Landscape Industry Report findings — Aspire (vendor survey), Oct 2026. Of operators who use AI, 52% use it for drafting content but only 16% for estimating; survey of 1,020 commercial landscape decision-makers. Summarized in our own words.