Groupon: Controlled Experimentation to Guide Product Innovation by Rajesh Parekh
Controlled Experimentation (or A/B testing) has evolved into a powerful tool for driving product strategy and innovation. The dramatic growth in online and mobile content, media, and commerce has enabled companies to make principled data-driven decisions. Large numbers of experiments are typically run to validate hypotheses, study causation, and optimize user experience, engagement, and monetization.
The popularity of controlled experimentation has given birth to several companies that specialize in offering tools and services to effectively setup, manage, and monitor large-scale tests. While the simplicity of this concept is disarming, there are several pitfalls that can stymie progress and occasionally lead to poor decisions.
Bio: Dr. Rajesh Parekh is Senior Director, Data Science at Groupon where he focuses on applying data mining, machine learning, and optimization algorithms to solving challenging problems in the space of daily deals.
Prior to Groupon, Rajesh was Senior Director of Research at Yahoo! Labs where he led the display advertising targeting sciences focusing on Yahoo!'s flagship Behavioral Targeting algorithms and other online advertising products. At Yahoo! he received the You Rock award for his work on real-time prediction of news-worthy queries, and the Data Wizard award for designing a system to optimize the number of sponsored ads shown on a search results page. Before Yahoo!, Rajesh was at Blue Martini software where he worked in data mining and analytics for retail e-commerce and at Allstate where he tackled key insurance problems such as cross-sell, customer retention, and fraud.
Rajesh earned his Ph.D. in Computer Science from Iowa State University. He has authored over 25 research publications and filed 20 patents. He is actively involved in the data mining community.
Also check out Rajesh's blog post to frame our discussion
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