Merchandising strategies are often at odds with search results. There are an infinite number of possible searches, which always makes it a battle to match and rank products and remain relevant.
Searches can be long, they can be complex, they can use different terminology, or even vaguer terms to describe product features. It could be a search for ‘floral print’, ‘leopard print’, there could be spelling errors, there could be differences in syntax. Racing to optimise product rankings for each of these manually is a race a small merchandising team is always going to lose.
With AI, similar searches containing synonyms or similar search intents can be grouped together. Plus, with sorting rules, AI can figure out when these should be applied.
Products can be ranked based on ratings, sustainability attributes, inventory turnover, popularity or stocking rates. It puts merchandising teams in control over hundreds of thousands of search possibilities at scale, without the need to manually intervene – unless, of course, they want to.