Vanja S
Head of eCommerce & Digital
Stop manually sorting products. Let performance data do it.
Rank your products dynamically using product engagement, metafield signals, and newness. Layer your own conditions on top to influence rankings across collections, search, and recommendations.
Your store keeps adapting, while your team stays in control of the strategy.
Commitment
Built For
Speed
Integration
Value
Solution
Let newly launched products surface based on how similar products already perform
Give fresh stock visibility before it has built any engagement history
Keep rankings dynamic without rebuilding sort orders after every campaign
Ensure best-performing products lead every collection without daily maintenance
Trusted by fashion brands worldwide
Hear from our customers
Rocky Matsuura
eCom Trading Manager
Rafaelle C.
eCommerce Manager
Ryan R
Digitial Optimisation Manager
Maria M
E-Merchandiser & Content Manager
Alex Harley
Head of eCommerce
Natasha de Weerd
eCommerce CX Manager
Common questions
Everything you need to know
The Tagalys Trending Score is the intelligence layer that powers product ranking across every surface on your Shopify store, collections, search results, and recommendation widgets. It calculates a score for every product in your catalogue every 24 hours, using shopper engagement on that product, metafield signals inherited from similar products, and a freshness score for newly published products. Instead of manually sorting products or relying on static sort orders, the Trending Score keeps every page current automatically.
The Trending Score combines three signals. Product Score is built from direct shopper engagement, views, add-to-carts, and purchases. Metafield signals use the performance of products that share relevant metafield values to predict how new products may perform. Freshness Score is a newness signal that starts at 100 on the day a product is published and decays over 24 weeks, compensating for the fact that new products have no engagement history yet.
When shoppers engage with a product, Tagalys also learns how products with shared metafield values perform. A new product has no engagement history of its own, so these metafield signals help it earn an initial ranking based on how similar products have already performed in your store. A new round-neck mini dress can draw on the performance of existing products with the same relevant metafield values, so it can surface intelligently from day one rather than being buried at the bottom of every page.
Freshness Score is a boost built into the Trending Score. When a product is published, it receives a Date Score of 100. That score decays to 0 over 24 weeks as the product accumulates its own engagement history. Without Freshness Score, new products would always start at the bottom of every page and struggle to get visibility simply because they are new. It gives them a fair chance to surface and reduces your manual work. Once real engagement builds up, the Product Score takes over and the Date Score becomes less relevant.
Best Selling ranks by total units sold and does not change until someone manually updates it. Newest ranks purely by publish date with no consideration of engagement. The Tagalys Trending Score combines three signals simultaneously and recalculates every 24 hours. A product that was a bestseller months ago but has lost momentum will naturally move down. A new product with strong metafield signals can surface immediately. The sort order always reflects what is working right now.
Yes. The Trending Score is calculated at the product level, which means it applies wherever Tagalys ranks products. A product performing strongly across your store benefits from that score everywhere it appears.
It is recalculated for every product in your catalog once every 24 hours, based on the previous 30 days of engagement data. This means your sort orders across collections, search, and recommendations always reflect recent shopper behaviour rather than patterns that may no longer be relevant.
Yes. Tagalys supports Global or Local boosts that add a positive or negative value to the Trending Score for specific products or product groups. A Global Boost applies store-wide. A Local Boost applies within a specific collection. These let you layer merchandising decisions on top of the automated ranking without replacing the intelligence underneath.