AI that shapes the order of a Shopify collection
Sales signals, stock levels and merchant rules help decide which products shoppers encounter first.
Daphnis built the Shopify application, its React merchant interface and Python backend. The AI engineering scope includes RFM algorithms and a self-hosted MegaBeam-Mistral-7B deployment.
Product screens published in the official Shopify app listing.
AI Sort ranks products using store sales and inventory signals. Merchants select it within a collection's sorting settings; other strategies support specific priorities such as new arrivals, bestsellers or available stock.
Explore this page (opens in a new tab)Collection sorting changes product placement within the browsing grid. This sample illustrates a pinned item holding the first position while the remaining products follow the selected sorting strategy.
Pinning keeps a selected item at the top regardless of the strategy used for the rest of the collection. The merchant can synchronise products and apply the selection from the same workspace.
Advanced configuration lets merchants boost or bury products by tag and combine sorting rules. These controls give campaigns and catalogue priorities a place alongside automated ranking.
The project's RFM algorithms analyse purchasing behaviour across three dimensions.
How recently a customer has purchased.
How often a customer returns to purchase.
The value associated with those purchases.
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