#102: CXO-Talk: Data, Machine Learning, and User Experience with Giorgos Zacharia, CTO, Kayak

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• published: 13 Mar 2015
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CXO-Talk brings you live conversations on leadership, innovation, and transformation with people shaping the future. Your hosts are Michael Krigsman and Vala Afshar. Learn more at http://cxo-talk.com Giorgos Zacharia is Chief Technology Officer (CTO) of KAYAK. He joined the company in 2008 as Chief Scientist. Prior to joining KAYAK, he was co-founder and CTO of Open Ratings, Inc., a leading supply risk management provider. Giorgos also co-founded two machine-learning driven hedge funds, Stocknomics and Emporics Capital Management. He holds four math and computer science degrees from MIT, including a PhD, won five medals in the International Mathematical and Physics Olympiads and was a Fulbright Scholar. Discussion Agenda Background • Tell us briefly about your professional and academic background • Tell us briefly about KAYAK? • What is the role of CTO at KAYAK? Data, Analytics, Customer Experience, and Product • What does KAYAK actually “sell”? Data, information, user experience, or something else? • Given this, what are the core competencies of KAYAK as an organization? • Give us a non-technical overview of how data flows from suppliers, through KAYAK systems, to users? What are the primary technical challenges you face? How do manage such large volumes of data? What is the link between data and user experience? What is the role of predictive analytics in the KAYAK product? Explain the role of machine learning to KAYAK? • Which is more important, technology or user experience? • How do you personalize the experience for individual users? • How do you optimize the website for traffic? • As a travel site, mobile is obviously critical to your strategy How does mobile fit into the product landscape? What are your guiding principles for mobile design? • What are the most challenging parts of the overall value chain we have been discussing? Business and Culture • What is the composition of KAYAK’s employee base? • On your LinkedIn profile, you specifically tell potential candidates to find a referral. Why? • Does this approach enable you to hire sufficient numbers of data scientists and other specialized experts? • What kind of culture is needed to support both intensive data science and highly engaging and friendly user experience? • How do you maintain that culture? • What approaches do you use for getting user feedback? How is customer success linked to company culture? • KAYAK obviously relies on continuous technical innovation How do you maintain that pace of technology change and advancement? Do you have formal innovation processes? Closing Thoughts / Advice • What advice do you have for startups trying to build a data-intensive company?