20-minute walkthrough with 2–3 personalized examples on your real pages.
Email, chat, or 24/7 phone support included on every paid plan.
Personyze’s BigCommerce related products recommendation engine uses each visitor’s interests, demographics, transaction history, and machine-learning algorithms to generate highly personalized suggestions, harnessing crowd patterns across shoppers.
The engine ships with a wide range of algorithms for e-commerce and beyond, so your BigCommerce shop surfaces the related products most likely to keep customers shopping — including frequently-bought-together cross-sells on product pages, as seen on Amazon.
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Integrating Personyze with BigCommerce is as simple as copy/pasting a tag into your tag manager. Once it’s active, Personyze can add product recommendations, track visitor activity, and unlock features well beyond recommendations — exit popups, personalized cart-abandonment emails, rotating banners, and more.
The related-products recommendations include a wide array of algorithms and variables, from a simple “buy it again” to frequently-bought-together bundles for cross-sells. You can also use machine-learning-based algorithms that use crowd data to find patterns no one would guess manually.
The Personyze team helps with setup — from integrating your product feed to configuring interaction monitoring. From there, you design the look and feel and tell Personyze where to embed the widgets. With managed service, recommendations can be live within days, with minimal team effort and zero IT resources.
A single tag in your tag manager connects Personyze; the team can assist with feed integration and configuration.
Yes — the same engine powers on-site and email recommendations.
BigCommerce related-products recommendations are only a few steps away — book a demo or view plans to get started.
30 minutes with a personalization expert. Bring your stack, your goals, your skepticism. We'll show you what changes when every visit feels like the only one.