Search.co

For ecommerce

Get your products found, wherever shoppers search.

Shoppers compare on Google, in shopping results and inside AI assistants before they ever reach a cart. search.co shows where your category and product pages stand on each, what the pages above you do differently, and which fixes move revenue first.

Ask Brigham.aiWhich bike.co category pages are closest to page one, and what would it take to push “gravel bikes” into the top three?
Gravel bikes18,100/moE-bikes27,100/moBike repair9,900/moKids bikes8,100/mo

Gravel bikes

gravel bikebest gravel bikegravel bike for beginnerscarbon gravel bike

E-bikes

electric bikecommuter e-bikee-bike under 2000folding e-bike

Bike repair

bike tune up near metubeless setupbike repair stand

Kids bikes

kids bike size chartbalance bike20 inch kids bike
Example data
Top 100
Results scanned per query
5
AI assistants tracked
~967
On-page factors measured
$20
Per month, all tools

The ecommerce problem

Thousands of pages, and no idea which ones to fix first.

Example store
bike.co
Pages
Category + product
Surfaces
Google, Bing, AI, Shopping
Data
Live results + your GSC

Most of a store’s search potential sits in category pages. The rest is spread across hundreds of product pages, and copy on both is often written once at launch and never touched again.

search.co groups your keywords into the categories shoppers actually search, shows which category page ranks for each group, and grades it against the pages that outrank it. Shopping results, AI answers and competitor ad spend sit alongside, so organic and paid plans share one dataset.

Category pages

See exactly why a category page sits on page two.

Run a page scan on any category URL. We fetch the top 30 results for its main query, measure about 967 factors per page and correlate each with position. You get a grade and the gaps that matter most.

bike.co/gravel-bikes

vs. top 10 · “gravel bikes”

Grade C
Words of category copycorr 0.41640+550Products listedcorr 0.3348+24Buying-guide FAQscorr 0.296+6Internal links incorr 0.3731+24Page load (s)corr 0.222.1−1.8
Page scan · top 30 resultsExample data

AI shopping answers

Know when an assistant recommends a store, and which one.

Shoppers now ask assistants “what is the best gravel bike under $2,000” and get a short list. Track those prompts next to your keywords and see whether you are named, cited or left out.

PromptChatGPTPerplexityGeminiAI Overviews
best gravel bike under $2,000Not named#4Not namedCited
where to buy an e-bike online#3#2#5Not named
kids bike size by ageCitedCitedNot namedCited
best bike shop for tune upsNot namedNot namedNot namedNot named
Example data

01

Who gets named

AI competitors shows which stores and brands assistants recommend instead of you, and the pages they lean on.

02

What gets cited

Size charts and buying guides earn citations more often than product grids. Citations show you which of your pages assistants trust.

Shopping ads research

See the shopping ads you compete against before you spend.

Shopping ads research shows which products competitors push in paid shopping results, how they title them and what they charge.

CPC forecasts show what it costs to cover a category with ads while the organic page catches up.

  • Product titles that win

    Compare competitor shopping titles and prices for the same query.

  • Spend before you commit

    Forecast clicks and cost per category, powered by the ROI.me ad engine.

Sponsored· competitor-a.com

Ad 1

Gravel Bikes from $1,199 | Free Shipping

Carbon and alloy frames. 30-day test rides. Shop 60+ models.

Sponsored· bike.co

Ad 2

Gravel Bikes, Fitted and Tuned | bike.co

Every bike built and tuned by a mechanic before it ships.

Sponsored· competitor-b.com

Ad 3

Shop Gravel Bikes on Sale

Top brands, price match guarantee, easy returns.

Shopping ads research · “gravel bikes”Example data

Built for stores

The tools a store needs, in one plan.

Keyword clusters

Group thousands of keywords into categories so each one maps to a single page.

Content briefs

Headings, questions, entities and word-count targets for category intros and buying guides.

AI writer

Draft buying guides and category copy in your brand voice, with images and charts.

Site audit

Catch duplicate filter URLs, broken product links, missing structured data and slow templates.

Rank tracker

Daily positions for money terms, with SERP features like shopping and image packs flagged.

Ads and attribution

Shopping ads research, budget optimizer and a first-party pixel to track revenue.

Crawl the catalog

Find the template problems that hurt every product at once.

A single template bug can affect thousands of URLs. The site audit groups issues by section so you fix the template, not the page.

bike.co/bikes/42Filter URLs indexedThin introsNo FAQ schema/products/118Missing Product schemaDuplicate titlesOut-of-stock 404s/guides/6Orphan pagesNo links to categories/service/11Slow imagesMissing local info
  1. 01

    Crawl the store

    Run a site audit for technical, on-page and AI-readiness issues across every section.

  2. 02

    Fix by template

    Issues are grouped so one template change clears hundreds of pages.

  3. 03

    Re-crawl and compare

    Crawl-over-crawl comparison confirms what is fixed and flags anything new.

Ask Brigham

Ask which category to fix next and get a ranked answer.

Brigham.ai reads your rankings, Search Console data and live results, then returns fixes ordered by likely impact.

Which bike.co category should I work on this month to grow revenue from search?
Brigham.ai· example answer

Gravel bikes. It ranks #11 for a cluster with about 18,100 monthly searches, converts best in GA4, and the top results beat you mostly on copy depth and internal links. E-bikes has more volume but the top ten are much stronger, so it will take longer.

Ask this yourself

Recommended fixes

Sorted by impact

  1. 1

    Add a 600-word buying guide to /gravel-bikes

    Half day

    Top pages cover frame material, tire clearance and sizing. A brief is ready.

  2. 2

    Link from 20 related product pages

    1 hr

    Only 7 internal links point to the category today.

  3. 3

    Add FAQ and Product structured data

    2 hrs

    Pages cited in AI answers for this query all carry both.

  4. 4

    Block filter URLs from indexing

    1 hr

    312 filter combinations compete with the main category page.

Store SEO checklist

What we check on every store.

Category pages

4 checks
  • One page per keyword cluster
  • Intro and buying guide
  • Links from related categories
  • Clean filter handling

Product pages

4 checks
  • Unique titles and descriptions
  • Product structured data
  • Reviews and specs in text
  • Sensible out-of-stock handling

One view of revenue

Organic, AI and paid on the same dashboard.

Organic revenue

$48.2k

↑ +14%

Category pages in top 10

23

↑ +6

AI mentions

41

↑ +9

Shopping ad CPA

$18.40

↑ -11%

Example data

01

Real numbers

Clicks and conversions come from your own Search Console and GA4.

02

Shared reports

Send a branded report on a schedule, or share a live link.

Questions

Frequently asked.

Still unsure? Ask the team.

Does search.co work with any store platform?

Yes. The tools work from your public pages, live search results and your Search Console and GA4 data, so the platform your store runs on does not matter.

Can it handle a large catalog?

The site audit crawls the whole store and groups issues by section. For keyword research and page scans you spend credits on the categories and products you choose, so start with the pages that earn the most.

Can you guarantee my products appear in AI answers?

No one can. We show which prompts name you, which pages assistants cite and what the recommended stores have that you lack, so your work targets the gaps that tend to matter.

What does it cost?

One plan at $20 a month with 1,500 credits. A top-30 page scan uses 30 credits and re-scoring a draft in the editor is free. There is a 7-day free trial.

Find the category page that will pay off first.

Bring your store’s domain. Brigham will map your categories, find the ones closest to page one and rank the fixes.

Map my store’s category keywords, show which category pages are closest to the top 10, and list the fixes for the best one.