Mom I need a new computer!
In this data science project, I have conducted a machine learing techniques on categorical data or commonly known as Unsupervised Learning. The code has been conducted in python and the results have found some very high quality results for Apple users.I have posted the code in the tab above labeled code and here. The data has been collected by university students in the hopes of better understanding purchasing decisions in what is the key demographic of most businesses, ages ~21-35. It’s best to not dive deep in some of the insights termonalogy as the “Persona’s” mentioned below are standard practice when aliasing data in order to better give feedback to non techinical leaders. Here below are the main insights from the data. Happy Shopping!
Here are the top 3 insights
Regardless of brand all persona’s, Hult DNA clusters, and personality clusters all will stay with their current brand of computer showing that students are conscious of the items they have and show great brand loyalty.
In the persona of surfers and across all personality clusters there was a desire to switch to MacBook’s. This persona was the only one that showed a willing to switch between the two major brands in the data set in windows and MacBook. The business strategy for Apple should be that we target this persona of individuals as they are most susceptible to being new customers for us at Apple. These individuals equate to 12% of the personality dataset. This can be leveraged and pursued by Apple.
Finally, Leaders in Hult DNA clusters across all Hult DNA personas showed that they are the only ones that are willing to try new brands and are switching to a third-party vendor in google Chromebooks. This should be a focus of research and more market understanding as we need to see if this is a just a trend for google Chromebook or is for all other types of laptops. These individuals equate to 33% of the Hult DNA dataset.