I wanted to learn a little more about how sites such as Amazon compile their suggested product lists based on other people’s spending habits.
I came across this lecture delivered via a MOOC by the University of Washington. The lecture clearly explains that it (broken down into basic form) is simply a case of counting the number of shoppers that bought any combination of products and offering the most popular items as last minute add-ons.
I found this very helpful when considering the building blocks of algorithms. It would appear that in this instance “Big Data” is being used for creative analysis for the benefit of the masses (Enyon 2013). However there is certainly scope for acknowledging that there are other behaviours within an online shopping experience that may not be identified by spotting trends.
I hope to cover such behaviours and trends by conducting a small experiment and documenting my findings before the end of this week.
Enyon, R. (2013). The rise of Big Data: what does it mean for education, technology, and media research? Learning, Media and Technology 38(3): pp. 237-240.