VeryQuery

Matches for shoppers. Intelligence for you.

Your shoppers find what they want in their own words. You see what your catalog is being asked for, and where the gaps are. Same map under both. Wire it into live search, or import your query history and read it on its own. Either path is a real start.

See a live catalog's map See pricing
Fig. 01 The intent map, in motion.
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01 The Problem

The translation tax.

Every search bar on the internet asks your customer to translate human desire into database terms. Color: charcoal. Length: midi. Category: coat. Occasion: last train, November. Nobody thinks like that, so they bounce. The exit is one tab away.

On your side of the counter, the cost is quiet but real. A merchandising team maintains a category tree shoppers never reach for. Lost sales look identical to bounce. Next season gets bought on gut, because the real demand signal is trapped inside a thousand queries nobody has time to read.

02 How to bring it in

Two paths.
Same map.

Shopify shops install the app. Everyone else integrates the API. Both paths give you the same product, search out front and intelligence behind it, with the same data sharpening both. Pick the one your stack lives on.

Shopify

Install. Toggle the surfaces.

Connect your shop, enable the embeds and section blocks you want. Search replaces the native results page with a ranked grid, sortable by relevance or price. Similar items drops onto product pages. Smart Categories surfaces the auto-derived categories as a navigation grid you place anywhere. Configuration lives in the VeryQuery dashboard, so the same setup follows you across theme changes.

  • Search results page replacement, filters and sort dropdown included
  • Similar items on product pages, density configurable
  • Smart Categories grid, auto-derived from your catalog
  • Empty-state navigation and signal capture, no manual tagging
  • Same dashboard the API customers use

What integrates: a few toggles in your theme editor.

API

Wire one endpoint. Render as you choose.

Search is one POST: query and filters in, ranked product IDs out. Similar items takes a product id and returns a ranked list. Catalog ingest mirrors your data via webhook. Build the surface yourself, blend results with your existing search, or pipe them into whatever stack you run. Your backend owns the key; the browser never sees it.

  • Natural-language intent search, no synonym dictionary
  • "More like this" for any product, by id
  • IDs in, IDs out. Your storefront stays yours
  • OpenAPI documented, webhook-driven catalog ingest
  • Works alongside your existing keyword search, not instead of it

What integrates: one endpoint on your server.

Different integration paths, identical product. Every shopper query that reaches us sharpens the same map your team reads, whether it came in through the Shopify proxy or your own backend.

03 Capabilities

One substrate,
two capabilities.

Discovery lives on the serve side. Intelligence lives on the read side. Same map under both. Two surfaces that sharpen each other.

Serve · Discovery

Search that reads intent, not strings.

Shoppers describe what they want in their own words and find it. Every product page gets a real “more like this” row. No rules, no synonym maintenance, no curation queue. Runs alongside your existing search: route the intent lane to us, keep the rest where it is.

  • Natural-language intent search, no synonym dictionary
  • Phrases like "this dress but in linen" land where you'd expect
  • Similar-item rows on the product pages you choose
  • Long-tail inventory, surfaced by meaning
  • No category tree, no synonyms, no seasonal re-tagging
Read · Intelligence

A planning surface you didn't have.

Your catalog and your shopper queries as one map. Empirical, not authored. Rank what's underserved, see the shape of the demand you already have, project a hypothetical product before you place the order. The kind of work that used to cost a consulting engagement.

  • Your catalog's categories, derived from what you actually sell
  • 2D demand map with a live heatmap of shopper intent
  • Demand vs. supply per category, ranked as a single index
  • Rising, steady, or cooling, window over window
  • Product placement: project a hypothetical SKU onto the map
  • Hardest-to-fit queries: demand the categories miss
  • Per-item and per-query trend, top items surfaced
04 Integration

Light footprint.
Either way in.

The API path is server-to-server. Your backend POSTs a query, gets back a ranked list of your own item IDs, and your storefront renders the result the way it already does. No JavaScript in your storefront, nothing on your checkout, no widget in your header.

The Shopify path is theme-app extensions. App embeds and section blocks render in Shadow DOM, scoped to the surfaces the merchant placed in their theme editor and untouched the rest of the way. The native theme keeps its checkout, its header, its product templates wherever you didn't put us.

Prices and inventory stay in your system of record either way. We don't hoard catalog data, we don't store PII, and we don't route shopper traffic through anywhere it doesn't already go. The integration is something you can turn off, at a toggle or by not calling.

05 In the field

Four catalogs,
both sides running live.

Four fully-built catalog demos. Each one has live intent search wired on the serve side, hitting production infrastructure on every keystroke. Each one also has its intelligence map running on the read side, rendered inline on the store's own homepage from real shopper queries. Tap a phrase to see search; scroll to the bottom of any demo to see the map. These don’t take orders; the demo is in both sides.

Scroll to the bottom of any demo homepage to see that store's intelligence map. The labels are the store's own product categories, derived empirically from the items it actually sells. The warmth is shopper demand. Same view the store gets in their planning surface, drawn from real traffic.

Like what you just saw? It’s self-serve from here. See pricing and start today

06 The Flywheel

Every query
sharpens your
map.

Every query stays. The ones your shoppers type today, the ones you imported from last year, the category passes your team made last week, all of it lives in the same map. The more your customers shop and the more history you feed in, the richer your picture of demand becomes, and the sharper every surface you build on top of it.

Your search bar stops being a cost center. It starts paying you back: matches for shoppers, intelligence for you.

07 The Ledger

Questions your data
is already trying to answer.

You have a catalog. You have a trailing year of shopper searches sitting in an export somewhere. That is enough to read the shape of your demand today, without a single live query flowing through us. The ledger below is what falls out of that read.

The question
What it usually costs
Your data's answer
QuestionWhat categories does my catalog actually span?
Usually costsA merchandising hire per season
Data saysDerived from your items, named in plain English.
QuestionWhich categories are shoppers reaching for hardest?
Usually costsA BI consultant, a quarter to answer
Data saysRanked demand index per category, rising or cooling.
QuestionWhere would a new SKU sit in my assortment?
Usually costsBuyer gut, followed by markdown
Data saysA coordinate on the map, neighbors listed, density read.
QuestionWhat are shoppers searching for that I don't carry?
Usually costsRevenue that looks like bounce
Data saysThe queries your categories can't cleanly place.
QuestionCould my search bar actually read intent?
Usually costsSynonym dictionaries, agency retainers
Data saysYes. The same map, served back to your shoppers.
QuestionNet
Usually costsHalf a dozen vendors, ongoing
Data saysOne line item. Two capabilities.
08 Enterprise

For catalogs at scale.

Past the Scale tier: custom volumes, dedicated support, negotiated terms. Tell us what you need and we'll reply within the week. Smaller catalogs don't need a form; pricing is public.

Direct [email protected]