Camera Retail Ecommerce with AI Product Ranking
Photo Store
Every shopper sees their own store: campaigns, grids, search, the mega menu and the basket are ranked from each customer’s order history — and every position explains itself.
- products
- 350
- products
- brands
- 42
- brands
- campaigns
- 21
- campaigns
- markets
- 2
- markets
What it shows
- Vector ranking everywhere
- Explainable scores
- Merchandiser vector lab
- Forgiving search
Pricing and markets
Discovery and personalisation
- Vector personalisation
Discovery ranks the store per shopper
- Explainable ranking
Merchandising rules
- Typo-tolerant search
Content and inspiration
Sells to
B2C and B2B
Industry
Electronics
Languages
English
Currencies
GBP, USD
Inside the store
A front page ranked for each shopper
Campaigns and product grids are ordered by Discovery vectors built from the customer’s own order history.
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Category pages that explain themselves
Every card carries a score badge that says why it sits where it does.
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21 campaigns, re-ranked per customer
The same campaigns, in a different order for a pro video shooter than for a wildlife photographer.
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How it works, in one page
A plain-language explainer of the ranking, written for merchandisers rather than developers.
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Stores cut from similar stone
Built agentically with the Crystallize MCP. Its repository rebuilds the whole tenant, including model, taxonomy, catalogue and customers, from one command. Prices and stock are demo values.