Ever since the e-commerce boom, online businesses have started their data collection journey to build comprehensive profiles of their customers. From their specific purchases to what their preferences are and decisions anywhere on the Internet. Recently in the last few years with data modeling and machine learning tools becoming more accessible, a shift has begun where consumers can actually track and analyze their purchasing habits to determine utility and benefit.
There was interesting experiment by a strategy consultant who decided to track every single clothing he wore for 3 years. Initially, he was looking to determine if it made sense to buy expensive clothing. However, this journey of his resulted in a deep analysis of the cost performance of clothing:
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Furthermore, what was interesting was how he created a formula to determine Cost per wear:
His analysis went on further with plot diagrams and came up with numerous insights including a key one that a wardrobe with only your favourite clothes may be the best in terms of cost performance.
Overall this exercise is very interesting in the sense that the same methodology can be applied to other purchases of product and services to determine the true utility for each consumer. Although the tools and methodology used right now requires some data modeling skills, in future machine learning and more mainstream black box models could be offered to consumers in which they plug in their history / track usage of products and services to determine true utility.
Stay tuned, for more insights in this revolutionary space...
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