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Successful Internet commerce sites have tens of thousands of unique daily visitors, creating large quantities of noisy traffic data. In the midst of this data are insights about customer behaviour that can help form commercial strategies and data driven decision making, however deriving these insights can be a complex process. Join Dr Abigail Lebrecht to learn how to identify changes in customer behaviour.
Restricting analysis to only looking at basic measurements of traffic numbers inevitably leads to more questions from business analysts - why has traffic increased today? Why has conversion decreased? Which types of customers are coming to the site? Questions of this variety are asked regularly after viewing simple traffic results so a traffic reporting system that executes more sophisticated measurements and analyses is required. Using time series and machine learning and statistical techniques, changes in the data can be isolated to give a daily or weekly detailed snapshot of the underlying customer behaviour prompting these changes.
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Dr Abigail Lebrecht is a Statistical Analyst at uSwitch.com focusing on using statistical and machine learning techniques to get the most value out of available data. She is passionate about encouraging the use of R statistical software techniques and an understanding of uncertainty in big or small data among both developers and commercial roles.