Search That Understands What Shoppers Mean

Athos Commerce’s AI-powered ecommerce site search solution goes beyond keyword matching to understand shopper intent. Unlike native platform search, it handles natural language, typos, and synonyms, automatically enriching your product catalog for maximum discoverability. It gives merchandisers full visibility into why products rank and how to fix issues fast.

Search uses AI to decode shopper intent behind every query, even when words are misspelled, phrased differently, or entered in another language. With support for 31 languages, automatic spell correction, synonym mapping, and intent-based results, every search finds a relevant product so no shopper ever hits a dead end.

AI Data Enrichment automatically extracts keywords from your product descriptions, normalizes naming variations, standardizes color terms, and maps synonyms across your catalog. This bridges the gap between what you call your products and what shoppers actually search for. This makes your full catalog discoverable without any manual tagging or data work from your team.

Search Preview gives your team complete transparency into rankings in real time. You can inspect search results, see match strength and scoring signals, identify which query terms influenced ranking, and view the exact product data used in matching. Most issues that would previously take hours to troubleshoot can be identified and corrected in minutes without engineering support.

Results vary by business, but customer outcomes are measurable and consistent. Thule, a global outdoor brand operating across 23 markets, recorded an 80% increase in search usage, a 41% decrease in search abandonment, and a click-through rate increase of 10% after implementing Athos Commerce Search. Search users on their site also convert at 2.69% compared to 0.59% for non-search users.

Ecommerce site search is the search function built into an online store that lets shoppers type what they want into a search bar and get matching products back. It is different from browsing categories because the shopper tells you exactly what they are after. On-site search users are among the highest-intent visitors on retail websites, so a strong search experience usually leads to higher conversion rates than category browsing alone.

Google search crawls the open web and ranks pages. An internal search engine only looks at your own catalog and ranks products. That means an ecommerce search engine has to understand product attributes, inventory, pricing, and shopper behavior in a way general web search does not. Athos Commerce runs your internal search on your live catalog data so shoppers only see products you can actually sell them.

Yes. Mobile users rely on the search box more heavily than desktop shoppers because scrolling through categories on a small screen takes longer. Athos Commerce Search returns fast, relevant suggestions as soon as someone taps the search bar, keeping the user experience consistent across phones, tablets, and desktop.

Yes. Faceted search lets shoppers filter search results by size, color, price, brand, and any other attribute in your catalog. Filters update in real time, so a shopper can narrow a broad query down to accurate results in a few taps. This pairs well with search because it gives shoppers a way to refine when the first set of products is close but not exact.

Yes. Product discovery does not stop at the first click. Athos Commerce can surface related products and similar products alongside search results and on product pages, giving shoppers more paths to purchase and lifting average order value.

Artificial intelligence and machine learning power almost every part of the search functionality. Natural language processing reads product descriptions and shopper queries to figure out what someone actually means. Machine learning then adjusts ranking based on how shoppers behave over time. Two people can type the same query and see different results because personalization tailors the output to each shopper.

Shoppers who use search already know what they want, so they convert at a much higher rate than shoppers who only browse. Improving your search feature lifts conversion rate, average order value, and customer satisfaction at the same time. A better customer experience also means fewer abandoned sessions and more repeat visits from potential customers who found what they needed the first time.

Autocomplete suggestions appear in the search box as a shopper types. They save keystrokes, correct spelling before the shopper finishes, and guide people toward a search term that actually returns products. For mobile users especially, autocomplete cuts the effort of typing a full query on a small keyboard.

Athos Commerce Search is built for ecommerce merchants on Shopify, and it also supports Magento, BigCommerce, and Miva. Most online retailer teams are up and running without developer time, so your ecommerce site gets a better search function without a heavy technical lift.