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E-Commerce Auto-Fulfilment System — From Order to Label Without Touching a Spreadsheet
Built a fully automated order-to-fulfillment pipeline for a D2C brand selling across Shopify, Amazon, and their own store.
THE PROBLEM:
The operations team manually copied orders into spreadsheets, checked inventory against 3 separate sources, created shipping labels one by one, and updated tracking numbers by hand. 3 hours of daily grunt work. 8% error rate. Delayed shipments. Angry customers asking "where is my order?"
THE SYSTEM I BUILT:
→ CAPTURE: Shopify order webhook fires instantly on every purchase. Amazon SP-API pulls orders every 15 minutes into the same pipeline.
→ VALIDATE: Auto-check inventory in Google Sheets. Flag low-stock SKUs for reorder. Route expedited orders to priority queue.
→ PROCESS: Generate shipping label PDF automatically via Shiprocket API. Create invoice in Zoho Books. Update inventory count across all channels in real-time.
→ SYNC: Push order status, tracking number, revenue data, and shipping cost to master Google Sheets dashboard for ops visibility.
→ NOTIFY: Customer receives automated email/SMS with tracking link within 5 minutes of order confirmation.
→ ALERT: Operations manager gets daily summary + instant alert on failed orders with retry logic and error context.
THE RESULTS:
• Manual processing time: 3 hours/day → fully autonomous
• Order processing errors: 8% → 0.2%
• "Where is my order?" support tickets: -60%
• Scales to 10,000+ orders/month without adding staff
TECH STACK:
Make.com | Shopify | Amazon SP-API | Google Sheets | Shiprocket | Zoho Books | Twilio | PDF Generator
WHY THIS WORKS:
E-commerce margins are thin. Every minute of manual processing and every fulfillment error eats profit. This system runs 24/7 without breaks, mistakes, or overtime pay.
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Hi everyone!
A lead fills out a form on your website. What happens in the next 5 minutes
decides whether they become a customer — or forget you exist.
THE PROBLEM
Leads sit in a mailbox or a spreadsheet until someone notices them. By then,
78% of buyers have already contacted a competitor.
THE SOLUTION
Lead Machine — an n8n pipeline that handles every inbound lead automatically,
from form submission to follow-up email in about 30 seconds, 24/7:
webhook → validation → duplicate check → Google Sheets → welcome email
→ Telegram alert to the manager → automatic follow-up in 24h
Every step is plain n8n nodes: no AI keys, no token fees, no monthly SaaS.
Validation rules, email texts, follow-up delay — all editable in the n8n UI.
It runs on YOUR infrastructure: credentials stay with you.
LIVE DEMO — send a test lead and watch the pipeline:
https://dvc-shared.dvc-ai.workers.dev/t/leadmachine-demo
Full case study on my profile.
Amazing
𝗜’𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗲𝗱 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗦𝗵𝗼𝗽𝗶𝗳𝘆 𝘀𝘁𝗼𝗿𝗲𝘀: 𝗺𝗼𝗿𝗲 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗮𝗹𝘄𝗮𝘆𝘀 𝗺𝗲𝗮𝗻 𝗺𝗼𝗿𝗲 𝘀𝗮𝗹𝗲𝘀.
Your Shopify store may NOT need more traffic.
It might need a better reason for visitors to buy.
I see this all the time:
A store is getting visitors.
People are viewing products.
Some are even adding to cart.
But sales? Still low.
So the first thought is:
“We need more ads.”
Not always.
Before spending more money on traffic, check these 6 things:
→ Is your offer clear within 5 seconds?
→ Does your product page answer the buyer’s biggest questions?
→ Are reviews and trust signals easy to find?
→ Is the Add to Cart button obvious on mobile?
→ Are shipping and returns explained clearly?
→ Is there a strong reason to buy NOW instead of “maybe later”?
More traffic sent to a weak buying experience can simply mean paying for more people to leave.
Fix the leaks first. Then scale the traffic.
I’m curious:
What’s the biggest challenge with your Shopify store right now?
A) Traffic
B) Add to carts
C) Checkout abandonment
D) Low conversion rate
E) Not sure yet
Drop the letter below 👇
I’ll reply with one thing I’d check first.
Clean layout, and the star ratings sitting right under each product card in the grid is a good call, most templates bury that on the product page only. Is UrbanNest a live client build or a template piece? Curious whether those review counts are pulling from a real reviews app...