How to search clothing across multiple retailers in one place

Most fashion shoppers already do multi-retailer search by hand. You see a coat in a photo, you check Nordstrom, then SSENSE, then the brand's own site, then maybe Mytheresa if it is European. Twenty minutes later you have four browser tabs open and a rough sense of who has the cheapest in-stock listing. The whole exercise exists because there is no Google Shopping equivalent that actually works well for fashion: clean, accurate, retailer-neutral, and broad enough to be worth using.

This piece covers the three real approaches to one-stop fashion search, what each one trades off, and how to pick the right one for the question you are actually asking. The short version: aggregators are best for price comparison, dedicated retailers are best for service and returns, and Google Shopping is best for raw catalog breadth on a specific known item. Most people end up using two of the three for the same purchase.

Why one-stop shopping for fashion does not really exist (yet)#

The reason there is no Amazon-equivalent for fashion is that fashion inventory is fragmented across thousands of retailers, brands run direct-to-consumer channels in parallel to wholesale, sizes and fits vary brand to brand, and the editorial layer matters in a way it does not for, say, electronics. A consolidated catalog would have to handle all of that without losing the data that makes a fashion purchase good (the cut, the lining, the country of make, the return policy).

Amazon Fashion has tried for years and the result is the catalog you know: counterfeits, mis-sized listings, inaccurate brand attribution. The aggregator model gets closer but has its own trade-offs. The retailer-direct model is the cleanest experience per-store but requires you to check several stores manually. The right answer depends on whether you care more about breadth, accuracy, or service.

Three approaches and what they cost you#

First approach: aggregator search. Tools like Fetchi, Lyst, and ShopStyle index across many retailers, surface a single search bar, and route clicks out to the retailer who actually fulfills. The trade-off is that the listings are only as fresh as the aggregator's re-price cadence (hourly for Fetchi, less clear for the others), and inventory can be stale at the moment of click. The upside is genuine cross-retailer price comparison and a broader catalog than any single retailer holds.

Second approach: retailer-direct, but smart about which retailers to check. For most luxury and contemporary fashion, you can cover 80% of the market by checking four sites: Nordstrom, SSENSE, Mytheresa, and the brand's own site. The trade-off is time spent across tabs; the upside is that prices and stock are accurate at the moment you check, returns and customer service are cleaner, and you build a relationship with the retailer (which matters for resale and authentication).

Third approach: Google Shopping. The volume is unmatched, the price comparison module is genuinely accurate on known items, and the AI Overview layer summarizes well. The trade-off is that the top three results are paid placements, the editorial layer is mediocre, and the fashion-specific filtering (brand, size, material, return window) is weak compared to dedicated tools. Google Shopping is the right tool for "I know exactly what I want, who has it cheapest." It is the wrong tool for "I want a black wool coat for under $400, show me my options."

How aggregators actually work (the affiliate side)#

It is worth being honest about how an aggregator stays in business. The model is affiliate revenue: when you click through to a retailer and buy, the aggregator gets a percentage of the sale (typically 2 to 8%) from the retailer. The retailer pays this because the aggregator drove the customer. The customer pays nothing extra; the affiliate fee comes out of the retailer's margin, not on top of the retail price. This is the entire reason aggregators are free to use.

The implication for you is that an aggregator is incentivized to show you the cheapest live price (because that is what closes the sale and earns the fee). What an aggregator is not incentivized to do is hold inventory or take a cut at checkout, because that would break the model. Fetchi specifically does not hold inventory, does not take a cut at checkout, and does not mark up the retail price. The click goes to the retailer; the retailer ships the product; we earn a referral fee. That is the entire business.

“An aggregator is incentivized to show you the cheapest live price, because that is what closes the sale and earns the affiliate fee. That is the entire reason aggregators are free.”

Picking the right tool for the question you are actually asking#

If the question is "where can I buy this specific designer piece cheapest right now," use an aggregator. The products catalog is built for exactly this question; it re-prices across 100+ retailers hourly and sorts by lowest live in-stock price. Cross-reference Google Shopping for the long-tail listings the aggregator may not index, but the aggregator is the right first stop.

If the question is "I want a category of thing, show me my options," use an aggregator with category filters. The menswear and womenswear indexes on Fetchi are organized exactly for this: browse by category, filter by brand or price, sort by sale or newest. The same workflow works on Lyst and ShopStyle, with different catalog skews.

If the question is "I want to buy from a specific retailer because their returns are good," skip the aggregator entirely and go direct. Nordstrom's 30-day no-questions returns are worth the modest price premium for many shoppers. Mytheresa's authentication on resale-prone bags is worth the same. Pick the retailer first, browse their catalog second.

And if the question is "what should I even be looking for," neither aggregator nor retailer-direct is the right tool. That is the discovery problem and it is what AI assistants (ChatGPT, Perplexity) solve better than any catalog search. The full landscape is covered in our piece on the best AI fashion search engine.

The Fetchi specifics#

Where Fetchi sits in this taxonomy: aggregator, 100+ retailers, 1,800+ brands, six regional storefronts (US, Canada, UK, Australia, EU, global), hourly re-pricing, no inventory held, no markup, no checkout cut. The regional storefronts handle the shipping problem; if you are in Vancouver, the Canadian storefront only surfaces retailers that ship to Canada with predictable duty handling. The editorial layer (this piece, the archive, the brand-specific guides) is built to bridge discovery and comparison so you do not need three tools for one purchase.

For the broader market, the products index and category pages on Fetchi mirror the structure you would build manually with three to four tabs open. The whole point is to compress the manual workflow into one search.