AI SEO built for Google AI Overviews, ChatGPT & Perplexity

Traditional SEO optimises for ten blue links on a search results page. AI SEO optimises for answer engines — Google AI Overviews, ChatGPT, Perplexity, and Copilot — that summarise or cite a source rather than simply ranking it. The fundamentals still matter (crawlability, page speed, relevance), but AI SEO adds structured data, clear entity signals, and content written to be quoted accurately rather than just skimmed by a human on a results page.

There is no guaranteed placement in any AI answer, but visibility is systematically improvable. We structure product, collection, and content pages with schema markup, clear headings, and direct answers to the questions your customers actually ask — the signals large language models and Google's AI systems use most often when selecting and citing a source. Brands with clean structured data and authoritative content get surfaced more consistently than those without it.

Google AI Overviews and AI Mode, ChatGPT search and browsing, Perplexity, and Microsoft Copilot — plus the traditional organic results these systems still draw from. We do not treat any one platform in isolation; the technical and content foundations that earn citations in one answer engine overlap heavily with what earns rankings and citations in the others, so the work compounds across surfaces.

Very. Structured data — Product, Offer, FAQPage, BreadcrumbList, and Organization schema — gives AI systems an unambiguous, machine-readable version of what your page is about, rather than forcing them to infer it from prose alone. On Shopify this often needs custom implementation beyond what themes ship with, particularly for variants, reviews, and availability data feeding agentic shopping tools.

Increasingly, purchases are being researched — and in some cases initiated — by AI agents acting on a shopper's behalf. Agentic readiness means your product data, pricing, stock status, and policies are structured and accessible enough for an agent to parse reliably, not buried in JavaScript-rendered content or inconsistent metafields. We treat this as part of standard technical SEO now, not a future consideration.

Both, and deliberately together. Technical SEO without content that actually answers a question earns crawlability but not citations. Content without a sound technical foundation never gets seen by the systems that would cite it. Our AI-first approach treats site structure, schema, page speed, and content strategy as one connected workstream rather than separate deliverables from separate teams.

We track brand and product mentions in AI answers, citation frequency across the platforms we target, referral traffic from AI surfaces where it is attributable, and the usual organic signals — rankings, impressions, and click-through — since the two move together more often than not. Reporting is monthly, with clear before-and-after benchmarks agreed at kickoff.

It matters most for brands in competitive, research-heavy categories where customers ask comparison and recommendation questions before buying — skincare, supplements, homeware, and similar. Smaller catalogues in low-consideration categories see less immediate upside, though the technical foundations still improve traditional organic performance regardless. We assess fit honestly during discovery rather than selling AI SEO to every brand by default.

The principles are the same, but the implementation differs. Shopify's theme architecture, Liquid templating, and app ecosystem create specific constraints and opportunities — how metafields feed structured data, how variant data renders, how apps inject or block content that AI crawlers can read. We build AI SEO work directly into the theme rather than bolting on generic recommendations that ignore how Shopify actually serves pages.

Technical fixes and structured data can be live within weeks, but citation behaviour from AI systems tends to lag actual search rankings — these platforms re-crawl and re-evaluate sources on their own schedules. Most brands see measurable movement in AI answer visibility within two to four months, alongside earlier improvements in traditional organic metrics from the same technical and content work.