In the last few years technology has been evolving at an unparalleled rate and as a result, we’ve seen innovation and disruption in the market place like never before. From subscription boxes and comparison sites to smart apps for your home, services are being consumed in all kinds of ways. The most successful brands understand the psyches of their consumers and have the ability to predict trends before they actualise, which is where Big Data comes in.
A particularly disruptive company whose business strategy relies on Big Data is internationally renowned online price comparison site, Skyscanner. Their Director of Experimentation, Colin McFarland, explained how the company uses Big Data to conduct AB Testing, which involves controlled assessments on small groups of people. These experiments help to discern causality and provide an insight into how users actually use the internet product. The company measures the potential success of new features by running them simultaneously in two separate test groups, and seeing which performs better. Failure, as well as success, is an integral part of the process as it eliminates what doesn’t work, and helps the team to ultimately decide which features to employ. The key to AB Testing is making the experiments configurable so that they can be changed or stopped easily, which is important as the groups are often switched. This is to ensure that the experiments are virtually undetectable to users, who opt in automatically by simply using the website.
It’s not all about AB Testing though; in reality, not everything can be validated by experimentation. Research and theory are also important and have resulted in some of the company’s most innovative ideas. Some of these ideas were actually a result of ‘avoiding the HiPPO’, which is a phrase that was adopted by the team to make the decision-making process more streamlined. The original intent was to give important people in decision-making roles more information, so that they don’t have to make decisions on a whim. A good example Colin gave was when they noticed that mobile users were taking screenshots of potential flight options on their phones. The users clearly wanted to save the information or direct the details to someone else. The team took heed of this and built a feature which recognises when a screenshot is being taken. The page details are then saved, and the user is redirected back to the page upon their next visit. Another great example is when the team implemented machine learning to make recommendations to the user based on their recent search history, which saves them the hassle of submitting information repeatedly. The team wouldn't be able to create features like these without studying the users and their behaviour, which is why Big Data is so useful.
By this stage of the talk the whole room was captivated. The company has established an agile framework led entirely by the consumer, which wouldn't be possible without Big Data. The tool, in combination with the process of experimentation, allows them to really understand their users, which is ultimately the key to success.
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