Shopify SEO agency
Your buyers ask ChatGPT what to buy, and it names someone else. Install Foliora on your store and it works the whole site — product and collection metadata, the pages you already have, structured data, and the machine-readable files AI crawlers read — then writes what is missing. You approve every change before it publishes. From $199 per month.
Publishes through
Cited across
How it works
No audit deck, no strategy phase, no six-week onboarding. The first check costs an email address, and everything after it ends in a change that is live on your store.
Enter your domain — no install, no card. Foliora reads your public pages, checks your category in Google, and asks ChatGPT, Gemini, Claude, and Grok what to buy in it. You get a score out of 100 and the names of the sites getting recommended instead of your store.
Not just new pages. Foliora rewrites weak product and collection metadata, fixes the architecture and canonicals underneath it, adds the product and FAQ schema an assistant needs to quote you, keeps your robots rules and llms.txt correct, and writes the comparison and buying-guide pages that do not exist yet.
You see every change before it happens, then Foliora writes it through Shopify's official Admin API — no theme edits, no copy-paste, no developer ticket. It re-reads the live page and puts the same questions back to the same assistants, so you see which change moved the score.
Two surfaces, one loop
Foliora scores a store out of 100 across four pillars, and the two heaviest are one per surface. A Shopify SEO agency that only works the Google half is leaving thirty points on the table.
Whether your category and buyer phrases return a page of yours at all, and how high. This is the classic work: collection architecture, canonicals, internal routes, product and category pages that deserve the position.
Whether ChatGPT, Gemini, Claude, Grok, and Google AI Overviews name your store when someone asks what to buy in your category — and which sites get named in your place when they do not.
Whether one page clearly owns what you sell, in enough depth and with the right product schema for both a crawler and an assistant to understand the offer without guessing.
Whether the pages a buyer needs before purchase actually exist: category, how to buy, comparison, and FAQ. Missing pages are the most common reason an assistant cites someone else.
The connected work
Ranking and being cited pull on the same foundation — real inventory, clear architecture, and pages that answer a purchase question — but they are measured separately, and only one of them is new.
Tie buyer demand to real products, variants, availability, and collection relationships before proposing a page.
Rewrite thin or duplicated product and collection titles and descriptions, then clarify the hierarchy, canonicals, redirects, and internal routes underneath them.
Ask a fixed set of buyer questions across ChatGPT, Gemini, Claude, Grok, and AI Overviews, and record whether your store is cited, mentioned, or ignored — plus the hosts named instead.
Write the page so an assistant can lift a clean, attributable answer from it: the question stated plainly, first-party evidence, product schema, and no claim the store cannot support.
Keep product, breadcrumb, and FAQ structured data valid, robots rules correct, and llms.txt current, so an assistant can parse what you sell instead of inferring it.
Check the rendered page after the API write succeeds, then re-run the Google check and the AI panel so the score moves on evidence rather than assumption.
What you get
Every engagement starts from the same snapshot and produces the same artifacts, so you can tell what was done and when.
What it costs
Shopify SEO agencies on this search result quote a retainer after a sales call. Ours is on the page, and the first snapshot costs an email address — no card, no charge.
The full loop on one domain: research, approve, publish, verify. Add capacity when you need it.
The boundary matters
Initial Shopify permissions deliberately exclude customer and order scopes. Write access is requested progressively only when execution is enabled, and theme or claim-heavy changes remain explicitly approval-gated.
Questions buyers ask
Shopify publishes SEO documentation and runs a marketplace where you can hire independent experts, but it does not run SEO for your store. The work — deciding which collection and product pages should exist, writing them, publishing them, and checking the live result — is yours to do or to hire out. Foliora does that work as a managed service on your own domain.
Foliora starts at $199 per month for one store, which covers 25 tracked buyer questions, 3 approved changes shipped per month, 250 managed pages, weekly site checks, and monthly sampling across ChatGPT, Gemini, Claude, Grok, and Google AI Overviews. Larger catalogs move to $499 or $999. Most Shopify SEO agencies quote a monthly retainer only after a sales call; our pricing is published, and the first snapshot costs an email address.
The useful ones change your store. That means mapping buyer demand to products you can actually sell, fixing collection architecture, canonicals and internal links, writing pages that answer purchase questions with real merchant knowledge, and then confirming the change rendered correctly on the live site. Reporting on rankings is the by-product, not the service.
Answer engine optimization is the work of getting an assistant to name your store when a buyer asks it what to buy, rather than naming a marketplace or a review site. In practice it is less exotic than it sounds: state the buying question plainly on a page, answer it with first-party product knowledge, mark the offer up with product schema, and make sure the page exists at all. The measurement is what differs — instead of a ranking position, you check whether the assistant cited you.
The foundation overlaps almost entirely: both need real inventory, clear collection architecture, and pages that answer purchase questions. What differs is coverage and measurement. Google rewards a page that ranks for a phrase; an assistant rewards a page it can quote and attribute, which puts more weight on structure, schema, and specificity. Foliora scores the two separately so you can see which surface is actually the problem before spending anything.
No tool ships the work. Apps can bulk-edit metadata, generate schema, and flag broken links, and those are worth having, but they do not decide which pages should exist or write them. The gap that costs Shopify merchants traffic is unwritten pages and unclear collection structure, which is a research and drafting problem rather than a tooling one.
They cite whoever answers the buying question clearly, and for most product categories that is currently a review site, a marketplace listing, or a competitor's guide rather than the store itself. Foliora samples a fixed panel of buyer questions across ChatGPT, Gemini, Claude, Grok, and Google AI Overviews, records which sites get named in your place, and treats those gaps as the page backlog.
Both, and that is the point. Foliora installs on your store and makes the changes itself through Shopify's official Admin API — metadata, structured data, redirects, collection and product pages, new guides — so there is no deck to act on and no developer ticket to file. What an agency normally supplies, the research and the judgment about which change is worth making, is what the software runs. You stay the approver: nothing is written to your live store until you have read the specific change.
Most of the early work is on pages that already exist. Thin or duplicated product and collection titles get rewritten, canonicals and internal routes get straightened out, product and FAQ schema gets repaired so an assistant can quote the page, and the machine-readable files AI crawlers depend on — your robots rules and llms.txt — get kept current. New pages come after that, for the buying questions your catalog cannot answer yet.
Not to start. The free snapshot reads only public pages and signs in to nothing. When you enable execution, Foliora requests Shopify permissions progressively through the official Admin API, and the initial scopes deliberately exclude customer and order data. Nothing is written to the live store until you approve the specific change.
The snapshot runs in minutes. After that the loop is continuous rather than a project: Foliora proposes changes, you approve them, they publish to your store, and the next check measures the live page. Search engines and AI assistants recrawl on their own schedule, so movement shows up over weeks, and each approved change is dated so you can see what shipped when.
Start with the public surface
Prefer the field guide? Use the catalog-led Shopify checklist
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