What is the Poshmark Algorithm?
The Poshmark algorithm is the computational system that determines which listings users see in search results, party feeds, and personalized discovery feeds. Like Google's search algorithm ranks websites, Poshmark's algorithm ranks listings based on hundreds of signals to predict which items users are most likely to purchase.
Unlike static catalogs where all items appear equally, algorithmic ranking creates winners and losers. Understanding how Poshmark evaluates listings transforms this from lottery to strategy. The algorithm isn't random—it's predictable if you understand its inputs and optimize accordingly.
Poshmark's algorithm serves two primary functions: search ranking (when users actively search for items) and discovery (when Poshmark suggests items users might like). Both use similar signals but weight them differently. Search prioritizes relevance; discovery prioritizes engagement potential and personalization.
How Search & Discovery Work
Poshmark operates two distinct algorithmic systems. Understanding their differences informs optimization strategy.
Search Algorithm Mechanics
When a user searches "vintage Nike sweatshirt," Poshmark's search algorithm executes in milliseconds through candidate retrieval, ranking calculation, personalization layer, and result display.