Industries
Most e-commerce SEO problems are architecture problems.
A catalogue that generates URLs faster than anyone can review them.
Category and facet combinations can produce tens of thousands of URLs from a few hundred products. Left alone, crawl budget goes to pages nobody should see while the categories that could rank stay thin.
On top of that sits the discovery shift: shoppers now ask models for recommendations, and marketplaces compete for the same queries with far more authority. Being specific about what you sell, for whom and on what terms is the part you still own.
What it covers
- Category and facet architecture with explicit indexation rules
- Product data quality as an SEO and AI input
- Seasonality, stock-outs and discontinued products
- Competing with marketplaces instead of ignoring them
- AI visibility on product recommendation prompts
How it works
01
Decide what the catalogue is allowed to generate
Before content, before links: which filter combinations may exist as indexable pages. Everything downstream depends on this, and in most shops nobody has ever decided it - the platform decided by default.
02
Treat product data as content
Attributes, dimensions, materials, compatibility. This is the material that answers 'which one fits my case', and it is the material a model needs to recommend you. Most shops have it in the database and not on the page.
03
Plan against the season, not the quarter
Demand arrives before the purchase, sometimes by months. Content published when the season starts has already missed it, and the calendar has to be built backwards from the buying curve.
04
Compete with marketplaces on the part they cannot copy
They win on authority and breadth. You win on knowing the product, the use case and the edge cases - which is also what makes a page worth citing rather than worth scraping.
What you get
- Indexation rules for categories and facets, written down
- Product data audit: what belongs on the page and is not there
- Seasonal content calendar built from the booking or buying curve
- Positioning against marketplaces on specificity, not on breadth
- AI visibility on product recommendation prompts
What is different here
Filters, variants and seasonality mean the site structure changes by itself - the question is whether it changes into pages worth indexing.