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Built an n8n automation that recovers missed customer calls, starts an AI conversation, checks CRM context, routes urgent requests, and tracks callback SLAs until the customer is handled.
I'd record separate timestamps for 'alert sent', 'owner accepted' and 'customer reached' so a delivered Slack alert can't count as a completed callback. Which event stops the SLA timer in your workflow?
Good point. Right now the SLA stops when Callback Completed At is recorded. I agree the workflow should separate Alert Sent At, Owner Accepted At, and Customer Reached At, and only Customer Reached At should stop the SLA timer. I’ll add that distinction.
Nice build, and Kapil's point about the SLA timer is a good one. One more case I'd test: very short missed calls, like a 2-second hang-up or a wrong number. Do you filter those by ring time before the AI conversation starts, so nobody gets a follow-up they never asked for?
nice that it tracks the callback until someone actually handles it. which businesses is this built for, trades or more like clinics
I built it for HVAC agencies but it can apply for every businesses who loose their leads because of missed calls.
hvac makes sense, one missed call there can be a whole job gone. are you selling it to the agencies or straight to the hvac companies?
true, a missed call costs pretty much any trade. are you selling it to the hvac agencies yourself right now, or still lining up the first ones
One failure case I would add to the callback-SLA tests: a delayed retry arriving after a person has already reached the customer.
Test sequence: ingest the missed-call event twice, accept the callback, record Customer Reached At, then replay the older event and run the escalation...
That’s a strong test case. My current flow excludes completed records from the open-callback lookup, but I haven’t yet tested replaying an older event after Customer Reached At is recorded. I’ll add this acceptance test and recheck the latest callback state immediately before...
Pulling CRM context before the AI says anything is the right order. Otherwise the first message to a returning customer sounds like it's meeting them for the first time.
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The problem: Most B2B companies lose leads because follow-ups are slow. By the time a rep reaches out, the lead has already talked to competitors.
The solution: An AI agent that handles the entire lead nurturing workflow:
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Tech Stack: n8n | OpenAI | Google Sheets | Gmail | Telegram
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This is like having an AI SDR that never sleeps — for $300/month.
Want this for your sales team? Let's talk.
#AIAutomation #LeadNurturing #B2BSales #SalesOps #n8n #PropTech
The bit about auto booking meetings into calendars looks like it will eliminate a lot of scheduling back and forth.
Automated Review Requests for Local Service Businesses
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Google reviews help local businesses get found, and every HVAC company, salon, cleaner and contractor knows it. Most of them ask for reviews inconsistently. The reason isn’t that they don’t care. Asking every customer, right after every job, depends on someone remembering at the exact moment the business is busiest. Happy customers never get asked, and the review count grows slower than it should.
The Solution
I built an n8n system that sends the review request automatically, once, at the right time, and tracks what happens next. Nobody gets asked twice and nobody gets forgotten.
How the System Works
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2. Sends the request. Two hours after a job is marked complete, the customer gets an email with a review link.
3. Tracks the click. The link goes through a tracking step that records “clicked” in the sheet, then sends the customer to Google.
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I'd test the tracking link with email security scanners before using clicks to suppress reminders. How do you distinguish an automated link check from a customer opening the review page?
hopify-style store dashboard, AI workflow connections, product cards and automation icons
Nice concept. Connecting store data with AI workflows can make e-commerce operations much more efficient.