Product Recommendations Logic
Rikke Søndergaard avatar
Written by Rikke Søndergaard
Updated over a week ago

Product Recommendations Logic

In this Article

Machine learning

The Product Recommendations will show products according to a combination of potential and actual purchase behaviour of all the visitors of your website.


The Product Recommendations will look at specific behaviours (browsed, carted or purchased) of all visitors in your website and show products with most interaction during the last three (3) hours.


The Product Recommendations will display those products that the Profile viewing the asset has browsed, carted or purchased, ordered by most recent.

1. Choose the Logic that fit your strategy.


A fallback source will act as a backup whenever there isn't enough visitor data to select the products to be displayed in your Product Recommendations asset.

The primary logic is the one you've selected above.

The primary fallback source will be the first to be considered when in need of more products for your asset, due to your primary logic not having enough data.

The secondary fallback source is considered whenever the primary fallback still can't provide the data needed to fill the Product Recommendations asset.

The fallback sources should be more broad than the primary logic.

It's important that you consider how these three interact with each other. Choosing a fallback source that is more limited or specific than the primary logic may cause your Product Recommendations asset to lack enough products to display.

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