AI merchandising is software deciding product placement from data instead of a person dragging tiles. On Shopify that means ranking what shows first across the surfaces shoppers actually use: collection pages, product option swatches, search results, and recommendation rows, all updated continuously as sales, stock, and prices change.
What It Covers
Merchandising used to mean collection pages. A shopper’s real path runs wider: they browse collections, type searches, and follow recommendation rows, and each surface has an ordering someone or something chose. AI merchandising treats those as one problem with one set of rules. The gains compound: the same signals that float a bestseller in a collection also rank it first in search and earn it a slot in the cart row.
Questions to Ask a Vendor
- Is it explainable? If nobody can say why a product ranked first, you cannot steer it or debug it. Prefer systems whose logic reads as rules with weights.
- Which surfaces? Collections only? Search? Recommendations? Post-purchase? Partial coverage means the surfaces left behind still run on defaults.
- Is it measured honestly? Look for per-surface conversion tracking and A/B testing against your current setup, with conservative attribution.
- What happens with thin data? Good systems fall back to sensible defaults on new stores and improve gradually, no cliff.
Dynasort answers those four the way you would hope: readable recipes across all four surfaces, measured conservatively, with relevance fallbacks from day one.
Dynasort is AI merchandising with logic you can read. Install it from the Shopify App Store or see how Dynasort approaches it.