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

About Product Recommendations

Customise your emails and website with recommended items based on the products each individual visitor recently browsed, carted or purchased. Or, let your complete customer base decide what products you want to put on display.

Product recommendations are a great way to improve the customer journey, guiding visitors through the discovery process while simultaneously generating more revenue. With machine learning doing much of the heavy lifting experiment with different strategies, segmentation practices, exposing more products to users than ever before.

By transforming the data collected in APSIS One to proactive and personalised recommendations, our Product Recommendations Add-on optimise the relevance of marketing efforts, predicting what your customers may want to buy next, and increases your ROI!

The Logic behind Product Recommendations

The Product Recommendations asset will be populated with products depending on which of the three types of logic chosen.

  • Machine Learning: A Machine Learning asset will be populated with a mix of potential and actual purchases from all of the visitors of your website. Think of it as a Most Popular!

  • Crowdsourced: These assets will be populated with the products that your website visitors have recently been interacting with. A crowdsourced asset shows your visitors your hottest products with up-to-the-minute relevance.

  • Personalized: A Personalized asset is catered to the individual Profile - using behavioual and event data from their APSIS One Profile, these assets will display relevant products that have previously been browsed, carted, or purchased by the customer.

Learn more about which Product Recommendations strategies to use.

Get Product Recommendation

Buy the Product Recommendations Add-on by reaching out to your Account Manager or send a request buy heading over to Tools in the left menu in the bottom.

Locate the Product Recommendations Add-on and click buy to send a request.

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