Storefront tracker
A 2KB script captures every shopper search — what they typed, how many results came back, whether they clicked anything. Auto-installs, no code.
Catalog matching
Each query is matched against your products with fuzzy + semantic search. Misses become “missing product” opportunities; weak matches become “wrong match” opportunities.
Revenue estimation
Monthly volume × your AOV × your category’s benchmark conversion rate = the revenue at risk for each gap, ranked.
Shopper searches track automatically
Storefront searches are captured in real time and analyzed daily — you don’t need to do anything. Hit Refresh data on the dashboard after a product launch, a price drop, or anytime you’ve added new SKUs so gap detection re-scores against the new catalog. Revenue numbers stabilize once you have 50+ monthly searches — below that, the dashboard shows volume but holds back $ estimates because the sample is too small to trust.
Tackle Missing products first
These are searches that returned zero results — pure buying intent that hit a wall. Each one is a customer who tried to spend money on your store. Adding the right SKU (or a category page that catches it) is the single highest-leverage fix in this app: one new product can recover the revenue from dozens of failed searches per month.
Fix Wrong matches with synonyms
Shoppers found products but nobody clicked — usually because Shopify surfaced the wrong items. Open Shopify Search & Discovery and add the suggested synonym (e.g. “tee shirt” → “t-shirt”). The next time someone searches that term, the relevant product ranks first.
Re-check after every catalog change
New collections, seasonal launches, or even renaming products can create fresh search gaps overnight. Make a habit of opening GapFinder within 48 hours of any catalog shift — that’s when the highest-impact gaps surface and the easiest wins are still on the table.
Watch the trend, not single days
A query showing up once is noise. A query showing up 10+ times in the last 30 days is signal. The dashboard ranks gaps by occurrence × benchmark conversion rate × your AOV — high-occurrence gaps are always the right place to start.