[Digital commerce & conversion]() / [Use cases]() / [Site search]() [How it works]() [What you get]() [Scope]() [Start a review]() [Digital commerce & conversion]()[Search & discovery]() # Fix searches that miss the right product. Shoppers find the right product however they ask, and exact codes, stock and facts stay true. [Start with a conversion review]() [How it works]() Failed searches Launch week · 1,240 - “rain jacket”Returned socks **212**Fixed - “washable jacket”The wash ranked above the jacket **96**Fixed - “waterproof jacket”Results never say waterproof unless the facts do **64**Held - “gift for a hiker”Too open for a list of results **58**To the assistant The failed-search ledger. The merchandiser starts each week here. ## Sound familiar? - “Rain jacket” returns socks. - A merchandiser boosts one product at a time, every week. - Searching the style code doesn’t always find the product. A shopper who types a search has told you what they want. If the result misses, you paid for the visit and lost the sale. Fernway’s launch week, failed searches 1. ## 1,240 searches failed in launch week. They returned nothing, or the shopper left without a click. Each one is a shopper using a word you don’t. 2. ## 1,100 were understood. AI reads intent, spelling and subjective phrases like “gift for a hiker”. The other 140 weren’t about this launch, so they waited. 3. ## 940 got the right product first. Rules decide the order: style codes always win, stock is checked, and “not waterproof” is shown rather than hidden. 4. ## 210 bought. One of them searched “washable jacket” and found the jacket, not the wash. Your merchandisers approved every rule behind it. 5. ## The best query got a before and after. For “washable jacket” the wash used to rank first. Now the jacket does, and the ranking is on file. Search **1,240**Failed searches **1,100**Intent understood **940**Right product first **210**Bought Where it landed WJ washable jacket Reached bought Bought RJ rain jacket Reached right product first Canvas jacket first, “not waterproof” shown C4 CAT-042 Reached right product first Exact match, always OM olive medium canvas Reached right product first Out of stock: Navy M offered JK jakcet Reached right product first Spelling fixed GH gift for a hiker Reached intent understood Sent to the assistant WP waterproof jacket Reached intent understood Nothing claimed falsely SK socks Reached failed searches Not this launch Ranking for “washable jacket” Launch week Rank Before After 1 Canvas wash Canvas field jacket 2 Wax bar Care Kit 3 Care Kit Canvas wash 4 Canvas field jacket Wax bar Accessories still show, below the product [See the ranking]() ## What changes. ShowTodayWith the engine Fixing a miss A merchandiser patches one query at a time AI reads intent and spelling, and the fix covers the group Exact codes Mostly work, until a similar item outranks them Style codes always win, by rule Stock and facts A sold-out size is the first result Stock is checked, and unclaimed facts aren’t implied Judging A few searches tried by hand A judged set of real queries, run on every change ## How it works. 5 steps, 4 stages. - AI**1** - Rules and automation**3** - Your team**1** - Approval 1. 1 Collect 1. Rules and automation ### Collect the failed searches Zero-result searches, rewrites and exits, grouped by query and counted every week. - Shopify 2. 2 Understand 1. AI ### Read what the shopper meant Synonyms, misspellings and open phrases like “gift for a hiker”, mapped to products or to the assistant. 3. 3 Decide 1. Rules and automation ### Keep exact codes and facts true Style codes, stock and claims are fixed rules, never ranking guesses. “Not waterproof” is shown. 2. Your team Approval ### Approve the rules Merchandisers approve the commercial priorities and the facts search may state. 4. 4 Check 1. Rules and automation ### Run the judged set Real queries with known right answers run on every change, including codes, misspellings and deleted products. Next week’s failed searches start the cycle ## What you get. Real work, every week. Ranking for “washable jacket” Launch week Rank Before After 1 Canvas wash Canvas field jacket 2 Wax bar Care Kit 3 Care Kit Canvas wash 4 Canvas field jacket Wax bar Accessories still show, below the product The ranking for one failed query, before and after. The jacket is first, and the care products follow it. Search tests · every release **19 of 20**judged queries return the right product first - CAT-042 finds the Canvas field jacket - Sold-out Olive M offers Navy M - “jakcet” still finds jackets - A deleted product never appears One cached result The test sheet that runs on every change, so a fix for one query can’t break another. ## How you’ll know it’s working. 1. Searches that find the right product Judged on real queries, including exact codes and misspellings. 2. Contribution per search user Held out against shoppers on the old search. Comparing search users with all visitors proves nothing. 3. Merchant hours spent patching The weekly boosts and synonyms that shouldn’t be needed any more. Baselines agreed before we build. ## Works with what you have. Commerce - Shopify - Adobe Commerce Search & AI - Algolia - Constructor Measurement - Google Analytics We configure first As of October 2026, Shopify’s Search & Discovery is free and includes semantic search, and Adobe Commerce ships its own. We judge what you have on your real queries before suggesting anything else. We build when Exact codes, stock rules and a judged query set need logic your platform’s settings don’t hold. ## What a first build includes. Built in your accounts, around your team. Scope, fee and baseline agreed before we start. 1. 1 Design 2. 2 Build 3. 3 Run it, or hand it over [Start with a review]() [Scope this build]() ### We build - A weekly failed-search review - Intent and spelling rules around your platform’s search - Exact-code, stock and claim rules - A judged query set that runs on every change ### We start from - Search logs and click data - Product catalog and stock - Past boosts, synonyms and redirects ### From your team Owner Head of ecommerce, with merchandising Involves - Ecommerce - Merchandising - Catalog - Engineering ## Questions teams ask. Isn’t semantic search built into our platform now? Often, yes. Shopify and Adobe Commerce both ship it. We test it on your real queries first. What’s usually missing is the rules around it: exact codes, stock and what a page may claim. Can AI show things we don’t sell, or claim things that aren’t true? Not through search. Rules decide what’s eligible and which facts show, and a semantic match never outranks an exact code. A claim with no source stays out. Do merchandisers lose control? No. They approve the rules and the priorities, and every change is on file. What goes away is boosting one product at a time. Who owns it once it’s running? You do. It’s built in your accounts, documented, with training for the people who run it. Ownership usually sits with your head of ecommerce, with merchandising. We can keep running it with you, or step back. How do we start? Usually with a conversion review: two to four weeks, a fixed fee credited to the build, and a plan that’s yours. If the job is already clear, we can scope the build directly. ## Part of your conversion engine. One of 14 use cases, in 5 parts. [See the whole conversion engine]() 1. [Evidence & decisions **2**]() 2. [Search & discovery **2**]() 3. [Guidance **4**]() 4. [Cart & checkout **4**]() 5. [Releases **2**]() In search & discovery - **Site search**You’re here - [**Search platform choice**Decide whether to keep, tune or replace your site search]() Works with - [**Product page answers**Answer the buying questions your product pages leave open]() - [**Conversion diagnosis**Find what’s costing you sales, and what to fix first]() See it at work - [**In Fernway’s eight weeks**Week 2: “rain jacket” stopped returning socks]() ## Help shoppers find what they meant. Start with a conversion review. [Start with a conversion review]() [**Talk it through first**15 minutes]() We reply within one business day. --- Source: [https://www.thekeating.co/use-cases/site-search-relevance/]() [Contact Keating & Co](mailto:nelson@thekeating.co) · [Agent guidance](https://www.thekeating.co/llms.txt)