Recommendations
Product and content recommendations end to end — algorithms, feeds, filters, wizards, widgets and JSON delivery.
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Match the Visitor — Put What Fits Each Visitor First
Every recommendation widget picks its products or articles with an algorithm — Best Sellers, Personalized, Similar items and the rest. Match the visitor then decides their order for…
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Category & Interest Recommenders — Recommend a Section, Not an Item
Recommend where to go next rather than what to buy — a product category or an article topic — with the algorithms behind them and the designs that lay them…
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Tuning the Engine — Score Blend & Presets
The account-wide weights behind every recommendation ordering — purchases vs views, freshness, click feedback, and the per-visitor price range that stays off unless you switch it on.
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Recommendation Algorithms — What Each One Picks
Every algorithm in the recommendation picker — what it draws on, what it needs, and the page anchor that changes its meaning. Including Similar Items (AI), Back in Stock and…
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Recommendations — Start Here
Start here: the order to set recommendations up in — your data, the algorithms, the widget, designs and delivery outside your site — plus which algorithm suits which page and…
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Content Recommendations for Mobile Apps
Personalized article and video recommendations inside your iOS or Android app, sharing one profile with your website.
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Embed Content Recommendations in 3rd-Party Emails
Drop one HTML snippet into any ESP template and render personalized article, guide, and video recommendations per recipient at the moment the email is opened.
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Product Recommendations for Mobile Apps
Deliver personalized product recommendations inside your iOS or Android app — catalog, the interaction reporting that makes them work, and HTML vs JSON rendering.
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JSON API — Content Recommendations
Get content recommendations as raw JSON and render them in your own layout — catalog, interaction reporting, algorithm modifiers, and the response shape.
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JSON API — Product Recommendations
Get product recommendations as raw JSON and render them yourself — catalog, interaction reporting, algorithm choice, response shape, and how to consume the result.