Automated E-Commerce Data Architecture for Oz Golden RushAutomated E-Commerce Data Architecture for Oz Golden Rush
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Can you build a fully automated e-commerce platform with zero monthly SaaS costs? Yes. 🛠️
I just dropped my new case study detailing how I engineered a self-sustaining data architecture for Oz Golden Rush. By combining Framer, Make.com, and Airtable, I automated their entire inventory, dynamic pricing, and social feeds—all wrapped in a custom vector UI.
Take a look at the project to see how I bridged the gap between zero-code automation and frontend engineering! https://contra.com/p/cEbebMRL-automated-data-architecture-for-oz-golden-rush
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Johnson's avatar
Linking inventory changes straight to dynamic pricing removes the manual lag and keeps the storefront responsive.
Ivan's avatar
Spot on, Johnson! Eliminating that manual bottleneck was the main goal. It completely changes how the business operates and scales. Thanks for checking it out!
Andrei's avatar
Read through the case study—the supplier having no API makes the inventory sync particularly interesting. How do you distinguish a watch actually going out of stock from a failed scrape or a change in the supplier's page layout?
Ivan's avatar
Great question, Andrei! Since we orchestrated this whole pipeline using Make, Airtable, and Byteline, we built a fail-safe validation step directly within Make.
Before pushing data to Airtable, a Filter module in Make inspects the scraped payload to ensure key DOM selectors...
Andrei's avatar
Keeping the existing inventory when the scrape looks wrong was exactly what I was wondering about. Thanks for taking the time to explain the setup!
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