How to set up search synonyms on Shopify
In Shopify's Search & Discovery app, open Synonyms and create a group that links the words shoppers type to the words on your products, like "hoodie" with "sweatshirt." Each group teaches search that those words mean the same thing. Watch two native limits as you go: 20 terms per group and 1,000 synonyms per store.
A shopper searches "sweatshirt." Your product is titled "Hoodie." Native search reads those as two different words, returns nothing, and a ready buyer walks. A synonym's whole job is to stop that: to tell search the shopper's word and your word point at the same rack. Here's the native way, where it runs out of room, and what to do then.
What is a search synonym and why does it matter?
A synonym is a rule that links two or more words so a search for any of them returns the same products. "Hoodie" finds the sweatshirts; "couch" finds the sofas.
It matters because your shoppers do not use your catalog's vocabulary. You wrote "sweatshirt" in the title; half the country types "hoodie." Without a synonym, that search is a zero-result search, an empty page shown to someone ready to buy. One mapping fixes every future search of that word, which is why synonyms pay back more than almost anything else in a search bar. The shopper asks; the synonym translates.
How do you set up synonyms in Shopify's Search & Discovery app?
Install Shopify's free Search & Discovery app, open it, and find the Synonyms section. Create a group, type the words that should match each other, and save. Search starts treating them as equivalent.
Two kinds are worth knowing. A two-way (or bidirectional) synonym means each word finds the others: "hoodie" finds "sweatshirt" and "sweatshirt" finds "hoodie." A one-way synonym points in a single direction: "nike" finds your athletic shoes, but a search for "shoes" does not pull up only Nike. Use two-way for true equivalents, like regional words for the same item, and one-way to route a broad or brand term toward a category. Start with your zero-result list. Every term that returned nothing is a synonym waiting to be written.
Where do Shopify's native synonyms run out of room?
At two hard caps. Shopify's Search & Discovery limits you to 20 terms in a single synonym group and 1,000 synonyms across the whole store. For a small catalog with a handful of vocabulary gaps, that is plenty.
For a real catalog, it gets tight. A clothing store alone has "hoodie / sweatshirt / pullover / jumper," "sneakers / trainers / athletic shoes / kicks," "pants / trousers / bottoms," color words, fit words, fabric words. Add the brand routes and the misspellings shoppers repeat, and the 1,000-synonym counter starts filling. Publishers documenting Shopify search note its "weak synonym and typo handling," and the cap is part of why: past a point, every new mapping means deciding which existing one to delete. That is the enemy. Not synonyms, but a synonym list you ration and babysit, where teaching search a new word means forgetting an old one.
How does Sledge handle synonyms without the ceiling?
Sledge AI Search takes synonyms two ways, and neither asks you to ration. On the first run, AI builds a starting set from your own catalog vocabulary: product titles, vendors, product types, and tags, so you begin with mappings instead of a blank box to fill from memory. And you manage the whole set in bulk with a CSV: export what exists, edit the pairs in a spreadsheet, import them in one pass.
There is no hard 1,000-synonym ceiling, so a large catalog carries the vocabulary it needs without trading one mapping for another. Two layers also run before any synonym is needed. Typo tolerance catches "sweatshrit" and "snekers" on its own. Semantic matching catches phrasing that means the same thing without sharing a word, so "comfy top for the gym" reaches the right products before you write a single rule. Synonyms then exist for the gap a machine cannot infer: the regional word, the brand route, the in-house name only your shoppers use.
Will AI-generated synonyms get my products wrong?
Worth checking, because a bad synonym is worse than none: it pulls the wrong products into a search that used to be empty. The generated set is drawn from your own catalog vocabulary, not from words your store never uses, and every pair stays editable. Open the list, rewrite the ones that read wrong, delete the rest.
Growth Intelligence covers the other direction. It flags the searches coming back empty, with the lost sales attached, so you can see which word your catalog never learned and write that mapping yourself. You get the gaps found for you and keep the final say on every word, the part you would never hand to a black box anyway.
The synonym setup checklist
- Pull your zero-result search list; every empty term is a candidate synonym.
- Write two-way synonyms for true equivalents (hoodie, sweatshirt, pullover).
- Write one-way synonyms to route brand or broad terms toward a category.
- Watch the native caps as you add: 20 terms per group, 1,000 per store.
- For a large catalog, manage the full set in a CSV instead of one group at a time.
- Let typo tolerance and semantic matching cover misspellings and near-meanings first.
What is the synonym limit on Shopify?
Shopify's Search & Discovery app caps you at 20 terms per synonym group and 1,000 synonyms per store. A small catalog rarely hits the ceiling; a large one with many vocabulary, brand, and misspelling mappings can.
Why does my Shopify search return nothing for products I sell?
Usually vocabulary. The shopper's word for the product is not the word in your titles and tags, so search reads them as unrelated. A synonym links the two. Typo tolerance and semantic matching handle misspellings and near-meanings separately.
What is the difference between a one-way and a two-way synonym?
A two-way synonym means each word finds the others, for true equivalents like couch and sofa. A one-way synonym points in a single direction, useful for routing a brand or broad term toward a category without forcing the reverse.
Can I bulk-import synonyms on Shopify?
In Sledge, yes. You export the existing set as a CSV, edit the pairs in a spreadsheet, and import them in one pass, instead of building groups one at a time inside an app with a hard count limit.
Related reading
AI Search · What is semantic search? · What is AI search? · How to find and fix zero-result searches on Shopify
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