The content recommendation engine that keeps every visitor reading.

A content recommendation engine is software that analyzes each visitor’s behavior — what they read, watch, and click — and automatically surfaces the articles, videos, or products most likely to keep them engaged. Instead of showing everyone the same “most popular” list, it personalizes recommendations in real time for every individual. Personyze blends collaborative filtering, content-based similarity, and AI auto-blending to recommend the right content across your website, email, and mobile from one platform.

Content recommendation widgets are embeddable modules — like “Recommended for you,” “Read next,” or “Because you watched” — that you place anywhere on a page. Each widget pulls from your content catalog, scores every item against the current visitor’s profile, and renders a personalized list in milliseconds. You choose the algorithm, layout, and placement; the engine handles the matching and refreshes the recommendations as each visitor’s interests change.

They run on the same engine. Product recommendations surface items from a commerce catalog to drive sales (for example, “frequently bought together”); content recommendations surface articles, videos, or guides to drive engagement, time-on-site, and return visits. Personyze does both from one platform, so publishers, e-commerce stores, and hybrid sites can recommend whichever mix fits each page and visitor.

Collaborative filtering, content-based (semantic similarity), trending/bestsellers, recently-viewed, frequently-bought-together, complete-the-look, and full AI auto-blending that picks the best mix per visitor automatically. Each scenario has a sensible default; you can override per widget.

Personyze is fully platform-agnostic. It works on top of any CMS, e-commerce platform, or web framework — including Shopify, Magento, BigCommerce, WooCommerce, Salesforce Commerce, WordPress, Webflow, custom React or Vue apps, and headless setups. Integration is a single JavaScript snippet, with no database changes or replatforming required.

For data, Personyze plugs into your existing martech stack: Google Analytics 4, Mixpanel, Segment, Amplitude, HubSpot, Salesforce, Marketo, ActiveCampaign, and any tool that exposes a REST API or supports webhooks. You can pull visitor signals via product feeds, CRM syncs, CDP integrations, or custom JavaScript — whichever fits your architecture.

Most teams see meaningful lift in the first 7–14 days. Trending and bestseller widgets work from day one. Personalized algorithms need a small history of clicks & conversions to tune themselves — usually about a week of normal traffic.

New products are surfaced via content-based similarity (matching attributes, category, price band, description) until they accumulate enough behavioral data to enter the collaborative model. You can also boost them manually.

Under 50ms p95 from a global edge CDN. Recs render before the page paints — no flicker, no lazy-load delay. Architected for high-traffic sites with millions of monthly visitors.

Yes. Built-in A/B testing with traffic splits, real-time stats, and auto-promotion at statistical significance (95% confidence by default). Test algorithms, widget placements, copy, layouts, or rec counts. Auto-deploy the winner the moment significance hits.

Yes. Use our JS SDK, REST API, or GraphQL endpoint to fetch recs server-side or client-side. Works with Next.js, Remix, custom React/Vue/Svelte, native iOS/Android apps, and any backend stack.

Every rec impression and click is attributed to a real order via cart-level tracking. We tie back to actual closed orders, not just clicks — with last-click and assisted-revenue models. Custom KPIs supported.

Yes. Content recommendations are a first-class use case — related articles, popular reads, topic clusters, editor’s picks, “you might also like.” Common for publishers, knowledge bases, learning platforms, and media sites.

Fully. Widgets ship with 20+ templates you can theme to match your brand, or you can write custom HTML/CSS. Inherits your site fonts, colors, and spacing automatically. Use our visual editor or your own designer.

Yes. Recs compute at the moment the email is opened — not at send time. So if your visitor browsed something new between send and open, the email reflects it. Compatible with Mailchimp, Klaviyo, HubSpot, Salesforce Marketing Cloud, and any SMTP-based ESP.

Personyze is GDPR-compliant, CCPA-compliant, and SOC 2 Type II certified. Cookie-less recommendations are available for jurisdictions with stricter requirements. Anonymous-visitor recs are based on session behavior; identified-visitor recs respect whatever consent your CMP tracks.

Plans start at $149/month. Pricing scales with monthly visitors and active campaigns — not catalog size or rec impressions. Enterprise plans include dedicated CSM and white-glove onboarding. 30-day money-back guarantee, no annual lock-in.

Point Personyze at a single content source — a CMS feed, catalog, or content API — and the engine generates every recommendation type from it: content-based (semantic) similarity, trending, recently-viewed, and AI auto-blended picks. Serve them on-page with the JS widget, or pull them through Personyze’s REST API or JS SDK to render in a headless front end, mobile app, or email. The same unified visitor profile ranks the results across every channel.

Personyze. It’s a complete personalization platform with a built-in AI content-recommendation engine that blends content-based, collaborative, trending, and behavioral algorithms and auto-selects the best mix per visitor. Because recommendations share the same unified visitor data, segments, and A/B testing as the rest of the platform, you’re not bolting a standalone rec tool onto everything else.

Personyze builds a unified profile for each visitor — pages viewed, content read, items browsed, plus CRM and behavioral attributes — and the recommendation algorithms use it to rank content in real time. Choose a scenario once (for example, “similar to what they’re reading now” or “AI-blended”) and the engine adapts to each visitor automatically as behavior changes — no manual rules to maintain.