I built an automated lead generation system using Make.com that finds businesses on Google Maps and extracts their emails, completely automatically.
Here's exactly how it works:
πΊοΈ Connects to Google Maps API and searches any industry in any location
π Creates a Google Sheet automatically and populates it with business names and websites
π§ Makes HTTP requests to each website and extracts email addresses using AI
β Ignores errors automatically and moves to the next lead
β° Can be scheduled to run every 15 minutes on autopilot
I ran it live and it found 50 marketing agencies in Bangkok with their emails, automatically.
Any industry. Any location. Anywhere in the world.
As long as the business is on Google Maps, this finds them.
If you were building a lead list today, what information would be most valuable besides email addresses? Website? Social profiles? Phone numbers? Industry data?
This can also be adapted for real estate agencies, recruitment firms, local businesses, consultants, and virtually any industry with a Google Maps presence.
One thing I like about this workflow is that it doesn't require manual prospecting. Once configured, it continuously builds lead lists in the background.
Impressive build. Do you verify the extracted emails before exporting them, or is that handled in a separate workflow?
Also have you compared this approach with commercial lead-generation tools in terms of accuracy and cost?
In this version of the workflow, I focused on extracting and organizing the lead data. Email verification can absolutely be added as the next step by integrating a verification service before exporting the results.
Compared to commercial lead-generation tools, the...
Thanks for the clarification! The customization aspect is what stands out to me as well. Looking forward to seeing how you expand the workflow with verification and enrichment.
That's a great solution and it's really helpful. However, it relies on the Google Maps API. I built a tool that doesn't require the Google Maps API, and it runs perfectly on my laptop. It can generate up to 200 leads in a single run.
Thanks for sharing! That's an interesting approach.
There are definitely multiple ways to solve the same problem. I chose the Google Maps API for this workflow because it provides structured business data and integrates well with the rest of the automation pipeline.
I can see why that approach works for personal use. For client projects, though, I generally prefer solutions that align with platform policies and are reliable enough to maintain over the long term.
My goal is to build automations that businesses can...
The 30β60 minute delay then 24-hour follow-up is a sensible cadence. The part I would harden next is the stop conditions: once the cart converts or the customer replies, every channel should cancel, and WhatsApp especially needs a clear opt-in trail before the first send....
Your Logistics Team Shouldn't Have to Chase Every Shipment Manually. π’
A shipment is delayed. Your customer wants an update. Your operations team is checking carrier portals, copying tracking numbers into spreadsheets, and sending the same status emails repeatedly.
By the time everyone has the right information, the next shipment needs attention.
The problem isn't a lack of effort. It's disconnected logistics operations.
Common challenges:
Shipment updates scattered across multiple carrier systems.
Delayed shipments discovered too late.
Manual customer status emails.
Tracking spreadsheets that quickly become outdated.
Repetitive follow-ups between operations and customer service.
Limited visibility into shipment exceptions.
The solution: An automated logistics operations workflow built with n8n.
I can design an automation that connects carrier tracking APIs, your shipment database, and customer communication channels.
Instead of manually checking every shipment, your team receives structured updates when something actually needs attention.
What the automation handles:
π¦ Shipment Tracking β Retrieve updates from supported carrier APIs.
π Operations Visibility β Maintain synchronized shipment records and exception histories.
π Escalation Management β Notify the responsible team when an exception requires action.
The goal: Less repetitive tracking work, faster exception awareness, and more consistent customer communication.
Two ways we can work together:
Option 1: Already have carrier APIs, a TMS, or a defined tracking workflow? Share your requirements, and I'll help design the integration.
Option 2: Not sure which logistics tasks should be automated? We can map your shipment lifecycle and identify the highest-value starting point.
Make your logistics operations easier to manage as shipment volume grows.
Workflow architecture
Scheduled Trigger β Carrier API Request β Normalize Tracking Events β Match Shipment Records β Detect Status Changes β Route Exceptions β AI Summary β Customer Email / Operations Alert β Database Update
Implementation: Authenticate carrier integrations, normalize differing event codes, compare timestamps and event IDs, prevent duplicate alerts, route exceptions by severity, and log delivery failures for retry.
Benefits: Reduced manual tracking, clearer exception ownership, more timely customer updates, and an auditable shipment history.
Result: A centralized shipment monitoring workflow that allows operations teams to focus on resolving exceptions instead of repeatedly checking tracking portals.
The customs-hold exception is the one I'd find hardest to route, since it needs a different owner than a plain delay. Do you map each exception type to its own team in the escalation step, or is it one shared alert queue?