CASE STUDY ONE
How will we upgrade our iPhones in 2022?
Below is the link for my project file so you can see what was going on inside my head!
This Case Study was to show my thought process in Data Analysis and how I answer the stakeholder's questions.
BREAKDOWN FOR MY CASE STUDY
My thought process & actions made
What is the question or the problem you're trying to solve?
Jamie needed a new iPhone and I was getting a phone from work. However, we wanted to make sure I had two phones so that I still have a personal device.
You could say that Jamie was my stakeholder and that I needed to impress with my Data Analysis skills! The goal was to provide our options for upgrading our iPhones and to find the cheapest overall option.
Where did the data come from?
The data sources I needed were the prices of Verizon and Apple. I was going to access other companies, but we've been using Verizon for so long and have been happy with their service so we didn't want to switch.
To get the answers we needed, I went through customer checkout on Apple and Verizon's websites so that I could see each other's prices. I captured this data and used it to answer the question.
The spreadsheet I made to contain this information included the cost of each iPhone overall, the payment terms, and the names of the options. This helped me see all the data I collected. The opensource data I collected for the cost of each phone is available on Apple and Verizon's websites.
How'd you clean the data?
My spreadsheet was shortly upgraded with more detailed information that I did have to review and clean the math portion. The dataset includes the monthly and annual cost of each option after factoring in trade-in credit for Jamie's old iPhone.
One thing that was brought to my attention when I was sharing my dataset was my personal iPhone 13 Pro. If I continued paying for my iPhone 13 Pro till September 2023, I'd own the device. So - I added what options would look like if we kept the 13 Pro!
Looking into the numbers to see what counts
In my data, I found that Verizon's due amount was about the same as Apple's when you factor in AppleCare+ to the device you're buying. However, the difference between the two came down to monthly payments and trade-in credit. Jamie's XR was worth $200 at Apple but worth $412 at Verizon. Funny enough, when my entire case study was done, Verizon changed the trade-in amount to $699 which changed everything!
I was most proud of my data visualizations in the sharing phase. I worked hard on making them visually appealing but also cut right to the point. It was easy to see what was and wasn't the best option(s) for Jamie and me. That's the beauty of Data Analysis!
A Real Success
When proceeding with the upgrading process, Jamie and I found a Verizon deal where we got to upgrade the iPhone XR for $700 versus the $412 upgrade. So Jamie was able to get my iPhone 13 Pro, and I was able to get a personal iPhone along with a work phone!
Additional data I could take for my work would be to analyze the cost of iPhones at AT&T and T-Mobile which are the other smartphone competitors and see which company offers the best value for your phone.