On this project, I worked on a dataset from a fantasy game Heroes of Pymoli.
Like many others in its genre, the game is free-to-play, but players are encouraged to purchase optional items that enhance their playing experience.
So I analyzed the data to generate a report that breaks down the game's purchasing data into meaningful insights.
My final report should include each of the following:
Player Count:Total Number of Players
Purchasing Analysis (Total): Number of Unique Items Average Purchase Price Total Number of Purchases Total Revenue
Gender Demographics: Percentage and Count of Male Players Percentage and Count of Female Players Percentage and Count of Other / Non-Disclosed
Purchasing Analysis (Gender)broken by gender: Purchase Count Average Purchase Price Total Purchase Value Average Purchase Total per Person by Gender
Age Demographics broken into bins of 4 years (i.e. <10, 10-14, 15-19, etc.): Purchase Count Average Purchase Price Total Purchase Value Average Purchase Total per Person by Age Group
Top 5 spenders in the game by total purchase value, then list (in a table): SN Purchase Count Average Purchase Price Total Purchase Value
5 Most Popular Items by purchase count, then list (in a table): Item ID Item Name Purchase Count Item Price Total Purchase Value
5 Most Profitable Items by total purchase value, then list (in a table): Item ID Item Name Purchase Count Item Price Total Purchase Value