20-minute walkthrough with 2–3 personalized examples on your real pages.
Email, chat, or 24/7 phone support included on every paid plan.
One visitor profile behind all of it. Anything you build in one place is available in the others.
Product and content recommendations that learn what each visitor wants — and serve it across web, email and in-app in milliseconds.
Choose from AI models, merchandising logic, or an algorithm you write yourself — then blend them. Shoppers can add to cart or save for later straight from the widget, and the same engine renders inside the emails you already send.
Whether you sell products or publish articles, Personyze adapts to every visitor in real time — lifting AOV for retailers and time-on-site for publishers.
Show every shopper the products they’re most likely to buy — on PDPs, category pages, cart, checkout, and post-purchase.
Keep readers reading. Surface the next article, video, or guide that matches what they’re into — based on topic, behavior, and intent.
Layer dynamic badges over recommendations to drive urgency and trust — trending, low stock, social proof, price drops, new arrivals.
One recommendation engine, every channel. The same personalized picks follow your visitor from web to email to push notifications — coherent, never duplicated.
Thirty-one base algorithms decide the order, and each one adapts to what it already knows about the visitor. The rules decide who gets into the list at all — and the badge is the last thing a shopper reads before they click.
Co-viewed by other visitors — ranked for the person looking at the page right now.
Test generic recommendations against AI-personalized picks head-to-head. Auto-optimization promotes the winner the moment it hits significance.
Layer dynamic badges and personal tags on top of any recommendation. Build trust with social proof, urgency with scarcity, and warmth with personal touches — all powered by your existing data.
See exactly which recommendations drive revenue, by widget, page, algorithm, and segment. Attribution that ties recs to actual closed orders.
Set up once, then let the engine learn and improve. No data engineers, no ML team, no rebuilds — just measurable lift on day one.
Sync product or content data via Shopify, Magento, WooCommerce, BigCommerce, or any REST API. We handle inventory updates, pricing, attributes, and stock in real time.
Pick the page (PDP, category, cart, article, homepage) and the visitor segment (new, returning, high-value, mobile, etc). Or run for everyone.
Collaborative filtering, content-based, frequently-bought-together, trending, recently-viewed, or full AI auto-blending. Each scenario has a recommended default.
Test recommendations in our Sandbox simulator with real visitor data. Share preview links with stakeholders. Roll out by traffic percentage when you’re ready.
Every visitor gets the right products, articles, or content for them — computed in under 50ms and tracked back to revenue. The engine learns and improves automatically.
From step-by-step onboarding to ROI tracking, every piece of the recs workflow lives in one platform — backed by a team that’s been doing this since 2008.
Catalog connection, widget placement, algorithm selection, and first-go-live — all guided by a dedicated success manager. Most teams ship recs within 5 days.
20+ widget types — carousels, grids, stripes, popups, banners — all themeable to match your brand. No design or dev needed.
Native connectors for Shopify, Magento, WooCommerce, BigCommerce, Salesforce, HubSpot — or roll your own with our API and webhooks.
Every rec click tied to a real order. See revenue by widget, page, algorithm, and segment. Custom KPIs for whatever your team measures on.
Algorithms self-tune based on performance. The engine learns from clicks, conversions, and revenue and continuously improves — no manual retraining.
True pay-as-you-go. Pricing scales with monthly visitors and active campaigns — not by catalog size or rec impressions. 30-day money-back guarantee.
Estimate the lift from bigger baskets, better discovery, and repeat purchases — in about a minute.
The questions teams ask most when evaluating a recommendation engine. Got something else? Bring it to the call.
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.
Yes — it’s one engine shared across the whole platform. The same recommendations can render inside open-time emails sent through your existing ESP, the visitor signals that power them come from behavioral targeting, and you can A/B test algorithms and placements against each other to prove revenue lift. One tag, one visitor profile, every channel.
AI-powered recommendations that learn what every visitor wants — and serve it across web, email, mobile, and ads in milliseconds.