Follow-up playbook
Old leads should have a polite follow-up path instead of disappearing into memory.
People who requested prices last month may still need help, but most small teams do not have a consistent way to check back.
A light follow-up sequence can ask whether the customer still needs help and move the lead to booked, closed, or nurture.
Inputs the workflow needs.
Automation works best when the inputs are clean. These fields give the business enough context to respond quickly without overwhelming the customer.
- lead date
- service type
- last contact status
- customer preference
- approved follow-up wording
- stop conditions
Workflow steps.
The first version should be easy to understand, easy to test from a phone, and small enough to improve after launch.
- Open leads are reviewed by age.
- The system prepares a short follow-up.
- The owner approves or sends the message.
- Replies are logged.
- Booked leads move forward.
- Uninterested leads are closed respectfully.
Dashboard signals.
A dashboard does not need to be complicated. It should show which requests are new, which need attention, and which are already handled.
Track this in a sheet, CRM board, or internal dashboard so the workflow has a visible owner.
Track this in a sheet, CRM board, or internal dashboard so the workflow has a visible owner.
Track this in a sheet, CRM board, or internal dashboard so the workflow has a visible owner.
Track this in a sheet, CRM board, or internal dashboard so the workflow has a visible owner.
Message templates.
These short examples are starting points. Final wording should match the business tone and any provider compliance requirements.
- Just checking back. Do you still need help with {service_type}?
- We can still help if this is on your list. What timing works for you?
- No worries if the project changed. Should we close this request for now?
Implementation notes.
Most first versions can run through a website form, email or SMS provider, Google Sheet, CRM, or a small internal dashboard. The important part is not the tool name. The important part is that the workflow has a clear trigger, destination, status, and follow-up rule.
AI can support the workflow by summarizing requests, drafting replies, flagging missing details, and preparing next actions. Customer-facing messages should still use human approval where the subject is sensitive, high value, or easy to misunderstand.
Related ZartsAlgo guides.
Local service website design, Landing page design, Quote form automation, Missed-call text-back, AI automation guide.
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