LUWIZ
Expertise · E-commerce

E-commerce SEO Agency — Google & Generative AI

Thousands of URLs, a limited crawl budget, a reliance on paid that weighs on margin. We structure your catalog so it sells on Google — and gets recommended by shopping AI.

Optimisé pour être cité dans

ChatGPTPerplexityGeminiAI·OverviewsClaudeBing·CopilotSearchGPTYou.com

E-commerce SEO is the discipline that makes a product catalog visible and selling in Google's organic results — and now in the recommendations of shopping AI. For a merchant, it's the lever that reduces costly reliance on paid: traffic whose acquisition cost drops over time, instead of a click paid at full price on every visit.

Why e-commerce SEO is first a technical challenge

E-commerce SEO is above all an engineering job, because an online store is a very large-scale site. Where a brochure site has a few dozen pages, a catalog generates thousands, even tens of thousands of URLs: products, size and color variants, combined filter pages, pagination, internal search results. Google has only a limited crawl budget for each domain: it explores only a fraction of these URLs on each pass. Without a controlled architecture, your most profitable pages can stay poorly indexed while parasite URLs consume crawl resources. That's why we always start with the technical side — indexing, URL structure, speed, product structured data — before touching the content. A foundation we detail on our SEO agency page.

6-10 wks

to observe the first effects of technical fixes on indexing

60%+

of an average catalog's product pages receive almost no organic traffic for lack of optimization [À VALIDER]

-40%

reliance on paid targeted at 12 months by rebalancing the mix toward organic [À VALIDER]

What an e-commerce SEO engagement includes

Catalog technical audit

Crawl budget, indexing, filter and URL-parameter management, duplicate content, Core Web Vitals. We start from a quantified diagnosis at catalog scale.

Optimized category pages

The pages that capture the largest volumes. Content, linking and structure designed to concentrate authority where it converts.

Product & review schema

Product, Offer, AggregateRating, Review. The markup that triggers rich snippets on Google and that shopping AI reads first.

Optimization at scale

Page templates, description-generation rules, automated tags. Thousands of references handled without page-by-page writing.

Linking & silos

A silo architecture by product universe to direct internal strength toward priority categories.

Performance & mobile

Load speed and mobile experience, critical ranking and conversion factors in e-commerce.

E-commerce GEO: existing in AI shopping recommendations

E-commerce GEO is the optimization that makes your products understandable, trustworthy and citable by generative AI at the moment a shopper asks them for advice. Buying behavior is shifting: instead of scanning ten Google results, a consumer asks ChatGPT or Perplexity "what's the best [product] for [budget and use case], and where to buy it?" and receives a synthetic answer with a few recommended merchants. If your product pages aren't structured to be read by these models — clear product attributes, complete schema, usable reviews, honest comparisons — you disappear from this new storefront. GEO consists of making your catalog intelligible to AI: it's a nascent product-discovery channel that nearly all French online retailers still neglect. Our full method is detailed on the GEO agency page.

Catalog elementSEO optimization (Google)GEO optimization (shopping AI)
Product pageRich snippet price + rating in the SERPProduct cited as a recommendation in the AI answer
Category pageRanking on high-volume queriesSource for AI-generated comparisons
Customer reviewsStars shown under the resultSocial proof leveraged by the models
Buying guideCaptures informational queriesBecomes a source cited by AI
Key takeaway

In e-commerce, a well-structured catalog serves both surfaces at once: the same product schema that triggers a rich snippet on Google lets shopping AI understand and recommend your reference. It's a single technical effort for two sales channels.

The LUWIZ Method applied to e-commerce

The LUWIZ Method applied to e-commerce is our four-step framework that turns a catalog into a measurable organic acquisition engine. Diagnosis: technical audit at catalog scale, analysis of crawl budget, duplicate content and underused category pages. Foundation: priority technical fixes, optimization of the highest-revenue categories, product schema deployed at scale. Authority: citable buying guides, structured reviews, link-building and internal linking that concentrate strength on your strategic universes. Steering: tracking organic revenue, positions and AI citations, with monthly iteration. Each project is prioritized by its expected business impact, not by ease of execution.

Catalog technical diagnosis

Audit of crawl budget, indexing, duplication and Core Web Vitals across all your URLs.

Foundation & category pages

Priority technical fixes and optimization of categories with the highest revenue potential, product schema deployed.

Authority & AI citability

Citable buying guides, structured reviews, link-building and internal linking to become a reference on Google and in AI.

Revenue-driven steering

Tracking organic revenue and AI citations, rebalancing the paid/SEO mix, transparent monthly reporting.

Reduce reliance on paid, durably

Many merchants build all their traffic on Google Ads and Meta, and watch their margin melt with each rise in bids. E-commerce SEO isn't meant to eliminate paid, but to rebalance the mix: recover organically the queries where you pay today for clicks you could win durably, and free up budget for conquest. Solid organic traffic acts as an asset: it keeps producing when campaigns are paused, and its acquisition cost drops as your authority grows. Paired with GEO, it also positions you on the emerging AI shopping channel, where your competitors aren't investing yet. To go deeper, see our resources and our definition of schema markup.

-40% paid
Target for rebalancing the acquisition mix aimed at 12 months [À VALIDER]

The SEO mistakes that sink most stores

E-commerce SEO mistakes are recurring structural problems that, at scale, scatter a site's authority and make it partially invisible. The first is uncontrolled indexing: thousands of combined filter pages ("red dress size M under €50") end up in Google's index, dilute the crawl budget and compete with your real category pages. The second is massive duplicate content, inherited from supplier descriptions copied identically across hundreds of merchants. The third is the underuse of category pages, treated as simple product grids with no content or linking, when they capture the highest-volume queries. The fourth is the absence of product schema, which deprives the site of rich snippets and makes product pages illegible to shopping AI. Fixing these four foundations before adding content is what creates the most value on a catalog.

Controlled indexing

Management of filters, parameters and facets to let only the pages that deserve crawl budget be indexed.

Unique content on key pages

Original descriptions on high-stakes categories and product pages, where supplier duplication does the most damage.

Enriched categories

Content, linking and real structure on the pages that capture the most volume and convert.

Schema deployed everywhere

Product, Offer, AggregateRating across the whole catalog for rich snippets and AI legibility.

This foundation logic directly extends our SEO agency approach applied at large scale. Too many merchants launch content and link-building projects on a site whose indexing leaks everywhere: it's like filling a leaky bucket. The order of priorities matters as much as the actions themselves — we stabilize the catalog's technical side before investing in conquering new queries, otherwise every euro of content yields a return diminished by structural leaks. It's this rigorous sequencing, more than isolated tactics, that distinguishes e-commerce SEO that compounds over time from a series of optimizations with no cumulative effect.

Ready to make your catalog sell on Google and in AI?

La méthode

La Méthode LUWIZ — 4 étapes

1
Étape 1

Diagnostic

Audit de visibilité IA & SEO, cartographie des requêtes cibles sur Google, ChatGPT, Perplexity, Gemini et Claude.

2
Étape 2

Fondation

Structure technique et contenu citable : schema JSON-LD, llms.txt, passages de 134–167 mots, architecture en silos.

3
Étape 3

Autorité

Signaux E-E-A-T, mentions et citations externes, maillage interne qui consolide votre autorité topique.

4
Étape 4

Pilotage

Mesure du share of voice IA, reporting mensuel et optimisation continue de vos citations.

FAQ

Questions fréquentes

An online store easily generates thousands of URLs: products, variants, filters, pagination, internal searches. Google only crawls a portion of this volume — that's the crawl budget. Without a controlled architecture, strategic pages stay unindexed while parasite URLs waste resources. E-commerce SEO therefore starts with the technical side: indexing, structure, speed, product structured data.

No, that would be inefficient at scale. Priority goes to category pages, which capture the highest-volume queries and concentrate authority, then to high-potential product pages. For the rest of the catalog, we work through optimized templates and content-generation rules: consistent descriptions, tags and product schema across thousands of references, without manual page-by-page writing.

Profoundly. Shoppers now ask ChatGPT or Perplexity 'what's the best [product] for [use case] and where to buy it' and receive direct recommendations. If your products are neither understood nor cited by these engines, you lose a growing share of product discovery. GEO structures your product and category pages — schema, attributes, reviews, comparisons — so shopping AI cites you as a reference option.

Yes, that's even its major benefit in e-commerce. Paid pays for every click and stops the moment the budget stops; SEO builds traffic whose acquisition cost drops over time. The goal isn't to cut paid, but to rebalance the mix: recover organically the queries where you pay today for clicks you could win for free, and preserve your margin.

Duplication is endemic in e-commerce: product variants, combined filters, copied supplier descriptions. We handle it with a strategy of canonicalization, URL-parameter management and content unification, paired with original descriptions on high-stakes pages. A clean catalog no longer scatters its authority: each strategic page gets the signal it deserves.

Technical gains (indexing, speed, schema) produce effects in 6 to 10 weeks. On worked category pages, measurable organic progress appears from 4 to 6 months depending on your market's competition. We set monthly milestones and first prioritize categories with the highest revenue potential to generate returns early.

3 slots disponibles ce mois

Audit GEO gratuit — rapport en 48h

Score de visibilité IA de votre site. Gap analysis vs 3 concurrents directs. 5 optimisations prioritaires. Livré en PDF, sans engagement.

Réponse sous 24h · Sans engagement · contact@luwiz.io