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Machine Learning Predictions for Subscription Companies

May 17, 2017

With the rapid acceleration of Subscription business models, several native e-Commerce companies like Amazon, Starbucks, and Sephora are moving towards adopting the subscription model. Machine learning can help marketers of subscription e-commerce businesses by providing predictive insights. ReSci’s (Retention Science) new lifecycle marketing product Subscription Cortex aims to harness the power of AI to the marketers. […] Read More

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

April 24, 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

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

April 15, 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

3 Major Recommendation Algorithm Mistakes Fortune 500 Companies Make

April 6, 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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