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Personalized Recommendations

Increase Customer Engagement and Conversion Rates by providing highly personalized experiences across digital channels through recommendations, curated content, and targeted marketing promotions. 

Push relevant recommendations to your customers, based on their online behavior, profile, purchasing patterns, location, time, and more. Improve customer engagement and conversio

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ROI Examples
Data Needed

1. Get Inspired

Understand the Use-case under 5 minutes

2. Know More

Get to know more Business and Technical details about the use-case (15-30 minutes)

Deeper Intro

More detailed introduction covering business and technical aspects

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

Tech focused

More details on the technical aspects of the use-case

3. Do

Technical resources that will help you implement the use-case (notebooks, tutorials..)

Data Sets

Data Sets you can use to build Demos, POCs, or test Algorithms

Recommender Systems and Personalization Datasets

A collection of datasets that have been collected for research by UCSD’s lab. Datasets contain the following features: user/item interactions, star ratings, timestamps, & more. Data coming from: Amazon, Pinterest, GoodReads, Facebook, Twitter, Reddit, Behance, & more


Off-the-Shelf Products using AI for Personalized Recommendations

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