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The Smart Marketer: When to Use Multi-Armed Bandit A/B Testing

April 10, 2017

What if as a marketer you could run 10 A/B tests within a week without lifting a finger instead of the standard monthly testing? You could be getting a significant increase in productivity and performance, if you do it right. A/B testing is a standard step in the marketing process. Without A/B testing, marketers wouldn’t have […] Read More

3 Major Recommendation Algorithm Mistakes Fortune 500 Companies Make

March 16, 2017

Several recommendation algorithms power email-marketing campaigns as well as on-site product recommendations. With Amazon’s success in driving revenue and engagement from product recommendations, several companies leverage these algorithms to cross-sell/up-sell products to users. The data science team at Retention Science has helped power onsite/app and email recommendations for more than 75 e-commerce companies. With over […] Read More

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Scaling Recommendation Engine: 15,000 to 130M Users in 24 Months

January 28, 2017

Delivering users with precise product recommendations (recs) is the creative force that drives Retention Science to continue to iterate, improve and innovate. In this post, our team unveils our iteration from a minimum viable product to a production-ready solution. Here’s the chronology of events: Month 1: Cold Start on a winter night Our first task […] Read More

Automating Machine Learning Monitoring [RS Labs]

November 2, 2016

This blog takes a small dive into one of our internal monitoring tools that overlooks our entire ETL pipeline and helps us stay on top of our machine learning models. Background: Imagine if what viral polite grandma was thinking when she was typing in her search query was actually true: that there is a human […] Read More

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