"Hey Siri, what's the best bike for steep hills?" Your listing says "Carbon-Fiber Road Frame." The right product. Zero overlap. As conversational search grows, these gaps are only multiplying. We analyzed the vocabulary of over 360 million product titles and descriptions and resolved it against 101.3 million search keywords, 70.5 million voice queries, and buyer intent signals. Updated weekly, the intelligence reflects what is happening in the market right now, not last quarter.
There is a widening gap between how brands describe products and how humans actually search for them. A buyer asks, "Hey Siri, what's the best bike for steep hills?" A retailer lists "Carbon-Fiber Road Frame." Precise, technical, correct. The right product. Two completely different vocabularies. The platform has no way to connect them, so the sale never happens. This is not an edge case. It is the default. Across over 360 million product titles, the merchant vocabulary and the shopper vocabulary rarely overlap. As voice search and conversational queries grow, the gap widens. Our engine was built specifically on commercial vocabulary, trained to understand what merchants mean when they write a product listing and what shoppers mean when they type or speak a search query. That specificity is what makes the intersection visible.
"Best bike for steep hills" vs "Carbon-Fiber Road Frame." Product vocabulary and shopper vocabulary don't overlap, and conversational search is making the gap wider every day.
High-demand items with strong semantic signals but zero advertising coverage. High-intent customers stranded, ad campaigns underperforming, and nobody knows why.
Missing products, categories, or attributes that shoppers expect but can't find. Standard taxonomies answer one question. Our engine answers hundreds.
Optimize for fuller, intent-aligned catalogs. Each cluster is enriched across 5 semantic dimensions simultaneously: categories, demographics, occasions, use cases, and seasons.
Keywords with high intent but low matching products and low competition go undetected. Our opportunity scoring combines demand, competition, and seller density into a single 0-100 score.
Uncover trends, pricing signals, and competitive weaknesses. 95M price events across 2 years of tracking reveal rising, falling, and volatile markets before competitors react.
We examine and screen over 1.5 million online stores every week. Only retailers that pass our data integrity filters make it into the graph, including major department stores, publicly traded DTC brands, specialty retailers, and custom cart platforms.
We screen 1.5M+ online stores and exclude nearly half. 687K stores are filtered out as spam, dropshippers, or failing data integrity checks. The 714K that remain include major department stores, publicly traded brands, specialty retailers, and 100M+ product listings from custom shopping cart platforms. Every title, description, and naming structure is linguistically decomposed, not just counted. Pricing data reflects actual storefront prices: the brand's own pricing strategy, not marketplace algorithm adjustments.
Three products that work the intersection from different angles. One enriches your catalog, one lets you explore the graph, and one tells you exactly what to do next.
Your product titles and descriptions meet your buyers' search language here. Upload your catalog or sync your Shopify store. The engine resolves your product vocabulary against 29.6M canonical neighborhoods and 22.3M buyer intent keywords, assigns high-value keywords with CPC and competition data, and generates gap analysis reports that show exactly where your listings are invisible to the people trying to find them.
Navigate the full intersection visually. Start from any node: a keyword, a product cluster, a store, a demographic, an occasion. Traverse the connections between product vocabulary and buyer vocabulary. Every cluster node displays 18 financial attributes on hover: price, demand, sellers, CPC, competition, opportunity score, and more.
Upload your catalog. Our AI analyzes it against the full enrichment graph. You get back specific actions. Not charts. Not dashboards. Not raw data. Actions.
Merchants describe products in one language. Consumers search in another. Reach Dog built the map between them: over 360 million listings deconstructed, the meaning behind every search signal decoded, resolved into a single graph that translates between the two. Every product on the platform reads from that same graph. The 17 Intelligence Reports turn it into actions for your catalog.
Where product vocabulary and buyer vocabulary resolve into one map
Upload your catalog. Our AI runs it against the full graph. You get back 17 intelligence briefs with specific actions: which products to change, which keywords to target, what revenue to expect. You upload. We analyze. You act.
Skip brute-force data cleaning. Jump straight to high-value discovery.
How big is the wireless earbuds market? Count titles, clusters, search volume, price bands, and seller density in a single query across over 360 million analyzed listings.
High-SV keywords with few competing products. Surface ghost inventory and untapped voids with demand-supply gap scoring across 29.6M clusters.
Which stores dominate your category? Compare seller density, intent breadth, category distribution, and geographic coverage across 714K data-integrity-screened retailers.
Track price trends across product clusters over 2 years. Weekly snapshots capture rising, falling, and volatile markets as they shift, not months after the fact.
Target keywords and conversational queries with high intent and low competition. CPC tiers, revenue potential, and opportunity scores per cluster. Export directly to Google Ads Editor.
"What do young women buy for New Year's Eve?" Cross-dimension queries spanning categories, demographics, occasions, seasons, and use cases. Weekly snapshots track how the market evolves in real time.
The engine deconstructs product vocabulary and buyer vocabulary independently, then resolves the intersection into a connected, queryable graph.
Over 360 million product titles and descriptions analyzed, decomposed, and resolved into 29.6M semantic neighborhoods. "Women's Boho Floral Maxi Dress" and "Ladies Bohemian Long Flower Print Dress" collapse into the same node. Each enriched across 5 dimensions: who buys it, when, why, what for, and what season. Sourced from 1.5M+ stores screened down to 714K that pass data integrity filters.
1M seed keywords from Google Ads and Amazon expand into 22.3M intent nodes. 70.5M voice and conversational search queries generated, including the "Hey Siri" vocabulary that's growing fastest. Resolved against 127M cluster centroids into 223M connections. 82% of all keywords carry a demand signal.
1.5M+ stores screened, 714K pass integrity filters, 95M price events across 2 years. CPC, competition, demand scoring, opportunity tiers, price momentum, and demand velocity, all connecting vocabulary to dollars. The entire graph refreshes weekly.
Access the enrichment graph wherever you already work.
Same enrichment graph, native on Google Cloud, updated weekly. BigQuery Partner Connect for zero-setup access to the full taxonomy dataset.
Install the Taxonomy Engine directly from the Shopify App Store. Sync your catalog and get enriched keywords, gap analysis, and ad campaigns.
1.27B rows across 28 tables + 2 views. Full SQL access to the semantic graph, updated weekly. CLUSTER_FULL view for one-query enriched cluster data.