Most are. Typical AI recommendation widgets cannot tell you why a specific product appeared in a specific slot, which means you cannot debug an embarrassing suggestion or steer the logic toward business goals like margin. The alternative is explainable ranking: recommendation logic written as rules you can open, read, and edit.
The Problem with Black Boxes
Opacity is not just a philosophical complaint; it has operating costs. When a customer sees a bizarre pairing, you cannot find out what produced it, so you cannot prevent the next one. When leadership asks why the cart row favors low-margin items, there is no answer. When you want the home page row to push clearance for two weeks, there is no lever. You are left A/B testing against a system you cannot interrogate, and taking on faith that its objective matches yours.
Explainable Recommendations
- The logic is a readable recipe: signals and weights you chose, so “why is this product here” always has an answer.
- Steerable by design. Want margin favored in the cart and discovery on the home page? Change the weights; the rows follow.
- Preview before shipping. See the exact cards any shopper will get for any seed product, before it goes live.
- Still data-driven. Explainable does not mean manual; rankings refresh automatically as sales, stock, and prices change.
Dynasort’s recommendation recipes work this way on every placement, product page to post-purchase.
Dynasort recommendations always answer “why this product?” Install it from the Shopify App Store or see explainable recommendations.