Recommendations with personalized products

This type of recommendation lets you suggests the products on the basis of user buying preferences and their behavioral profile. Data about similar users and analysis of algorithms can be enriched by specific product categories. They can work well, for example in the cosmetics industry (eye color, skin type), tourism (preferred destinations), real estate (the type of property sought) and clothing (size). In this way, recommendations can be even more accurate.

Display recommended products selected on the basis of similar browsing paths of other customers, purchases they made, their browsing history. The machine learning mechanism on the website will allow you to completely automate the process. As a result, users will, above all, see products they might be interested in – the perfect recommendation.

Screenshot presenting similar products recommendations

Example of use - Home appliances industry

The client wanted to increase engagement and revenue on their Home Page. A campaign was based on personalized recommendations. Personalized products were displayed to the customers based on their purchase and browsing histories.

Results

First client:

  • 10.98% CTR,
  • 4.36% conversion rate (the number of purchased products vs clicks),
  • 3% shares in profits.

Second client:

  • For the home page, the increase in CTR from 0.48% to 1.25% and the increase in the conversion rate from 2.8% to 4.3%.

Read more

  • Learn how to configure personalized recommendations and how to configure it. Above you will find complete guide to implement this solution in your campaigns

  • You can also check the statistics from your recommendations

This use case belongs to the following categories:

Challenges:

Features:

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