Follow up after every job and catch unhappy customers early
Problems surface before they become 1-star reviews
Illustrative example — a composite of common setups, not a specific business's story.
- Difficulty
- Light setup
- Setup time
- 2 hours
- Monthly cost
- $20-$50
- Impact
- High
The short version
Two days after a job, an agent texts a one-question check-in. Happy replies get a review link; unhappy ones alert the owner.
What they did
Two days after a job, an agent texts a one-question check-in. Happy replies get a review link; unhappy ones alert the owner. The owner started with a small pilot: one workflow, a few days of supervised use where every output was reviewed before it went out, then gradually let routine cases run with lighter oversight.
Agent/tool used: Zapier AI step
How it went
In a typical rollout like this: problems surface before they become 1-star reviews. Most of the value comes from consistency, the task happens every time instead of when someone remembers. Expect a week or two of tuning the prompt and rules.
Worth knowing
AI drafts can be wrong or off-tone. Keep a human approving anything customer-facing at first, don't paste sensitive data (card numbers, health records, SSNs) into general chat tools, and check each tool's data and privacy terms.
Copy-paste prompt
Classify this customer reply as HAPPY, NEUTRAL, or UNHAPPY: [reply]. If HAPPY, write a short thank-you with our review link [link]. If UNHAPPY, write an internal alert for [owner name] summarizing the issue in one sentence.
Replace anything in [brackets] with your own details.
Step-by-step setup
- Write down how you handle this today, in 5-10 bullets.
- Connect or export data from Jobber, Slack, Zapier.
- Set up Zapier AI step and paste in the prompt, filling in the [placeholders].
- Test it on 5-10 real past examples and fix anything that's off.
- Run it with you approving every output for one to two weeks.
- Once you trust it, automate the routine cases and spot-check weekly.
Published 2026-10-06. Want help setting this up?