Chris Moody starts out with presenting what his department at Twitter uses big data for. It’s an amazingly wide range: From a cooperation with the US Library Of Congress in Washington DC, to helping flood victims in Jakarta and assisting pharmaceutical companies in finding new side effects of cold medicines.
With him on the panel is Tony Haile from „Chartbeat“, Jane Zavalishina, CEO at “Yandex Data Factory”, and Werner Vogels from “Amazon”. Their conversation centers on the following questions: Where can you actually employ big data sensibly? Which are the right parameters? Where can you still rely on your instincts and where should you outsource the decision making to algorithms? Moody answer to the latter question: „The days of gut instincts are gone“.
Tony Haile contributes another interesting aspect to the debate. In his opinion, quality content is crucial to drive traffic and ultimately make money online. „We have to optimize for the minds, not just for the index finger“, he says.
Werner Vogels agrees and highlights the importance of personalizing the consumer’s experience through data analysis: „Data has the advantage to help you understand who your costumer is. Today, you need to deliver a personalized experience because you have to build a long-term relationship with the client. Otherwise, he will shop elsewhere “.
However, host Nicholas Carlsen from “Business Insider” is curious: Where does creativity still play a part in big data business? All panel members agree, it is still an important asset. Jane Zavalishina says: “Finding the right goals in data analysis requires great creativity. Many companies want to use big data, but most do not know what they want to measure“. Vogels adds that sometimes picking the right algorithm can be a real creative challenge.
Twitter’ Chris Moody ends the debate on a positive note once again highlighting the advantages of big data analysis: “In the future our customer experience will be more positive. We will make better choices and live easier and more efficient lives due to big data“.