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AI Customer Request Automation — an n8n workflow that processes customer requests, detects duplicates, uses AI to classify and analyze inquiries, stores structured data, sends notifications, and handles workflow errors.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Just finished building a Salon Booking Management System!
The goal was simple: make appointment management easier for salon owners and reduce the manual work involved in handling bookings and reminders.
The system connects the complete workflow in one place:
1 Customer makes a booking
2 Booking gets confirmed
3 Owner sees it on the dashboard
4 Upcoming appointments are organized clearly
5 Reminders help the owner stay on top of appointments
One of the key things I focused on was making the experience simple, clean, and easy to understand, while keeping the workflow practical for a real business.
This project helped me think beyond just building screens — and focus more on the actual business problem, user flow, and overall product experience.
Excited to keep improving it and turn it into an even more polished product.
#BuildInPublic #SaaS #WebApp #BookingSystem #SalonManagement #ProductDesign #MVP #NoCode #Entrepreneurship
Good work
Ai workflow, Ai automation, jotform automation?
Let's get it done.
Just finished building a Salon Booking Management System!
The goal was simple: make appointment management easier for salon owners and reduce the manual work involved in handling bookings and reminders.
The system connects the complete workflow in one place:
1 Customer makes a...
The bot once scored “just browsing” as hot.
Early scoring leaned too hard on page visits alone someone reading the pricing page out of curiosity got flagged as ready to buy. Rebuilt the scoring around actual answers, not just clicks.
→ A page visit is curiosity. An answer is intent. They're not the same signal.
Switching the model to weight answers over page views really separates curiosity from intent, so you catch the buyers before they slip through.