The Product Recommendations action renders a fully customizable, responsive widget of personalized products — driven by views, cart contents and purchases, blending crowd wisdom (best sellers, bought-together) with each visitor’s own behaviour. This guide covers the action itself; the Product Recommendations wizard walks the full campaign end to end.
Prerequisites
- A product catalog synced.
- Interaction tracking for view / add-to-cart / purchase — the events the algorithms learn from. Until there is enough data, Personyze falls back to contextual recommendations so the widget is never empty.
Adding the action
In any campaign type that shows content — most often a Targeting & Personalization or Product Recommendations campaign — open Content, click Add action and pick Product Recommendations.
Choosing the algorithm
The Recommendation source picker groups the algorithms — personalized, crowd-based, item-based, and fallbacks. The full catalogue with when-to-use guidance is on Product Recommendations Algorithms and Algorithm Types.
Sharpen the result set with filters (price, category, stock, any catalog field — fixed or relative to the visitor) and fallbacks for when the primary algorithm has too few items.
Look & feel
Widget settings work like every action editor: click an element in the live preview or use the sidebar; each setting has its own CSS hook and a ⚡ Variations button for per-audience values (see the variations walkthrough). Edit action with AI restyles the widget from a plain-language prompt. Card fields come from your catalog columns — price, brand, badge, anything you synced. A quick add-to-cart button can be enabled per template.
Placement
Same placement machinery as every action: inline in one or more placeholders, or floating with position, backdrop, triggers (arrival / scroll / exit intent / your own trigger) and plain-language frequency caps.
Measuring
The widget reports impressions, clicks and attributed revenue to the campaign’s Performance step; recommendations-specific analytics live under Analytics. To pit algorithms or designs against each other, activate A/B testing on the Content step.
Related
- Product Recommendations wizard — the full campaign, step by step.
- JSON feed variant — same algorithms, rendered by your own code.
- Buy-together discounts and managed upselling.