data-with-saumya
commented
2 years ago Introduction¶
This project is an Data Analytical assignment to analyse the data of a customer of KPMG, The Spyrocket Central, who deals in the selling of various brands of bicycle in all the four states of Australia. They had issues with stagnating sales and needed help in the following queries:
- What are the trends in the underlying data?
- Which customer segment has the highest customer value?
- What do you propose should be Sprocket Central Pty Ltd ’s marketing and growth strategy?
- What additional external datasets may be useful to obtain greater insights into customer preferences and propensity to purchase the products?
Database
Customer had share the database with the company, which consisted of the following information:
- Customer Demographic: It consisted of past three years' worth of details of cusotmer, their transaction type, profession, car's ownership status, gender, etc
- Transactions details: It consisted of all the transactions details like, type of payment, order status, brand, product bought, costing, etc, corresponding to each customer based on their customer ID and transaction ID
- There were also New Customer Lists and Customer Address, with a bit of additinal details
Process
The database had a lot of anomalies. So, I did the cleansing using MS-Excel and Google Spreadsheets. These were the error and anomalies that I had to work on:
- Customer Demographic:- DOB: inaccurate; Age: missing; Job title: blanks; Customer ID: incomplete; Gender: inconsistency; Default Column: gibberish, deleted
- Customer Address:- Customer ID: incomplete; State: inconsistency
- Transactions:- Profit: missing; Customer ID: incomplete; Online Orders: Blank; Brands: Blanks; Cancelled Order: filtered out; List Price: formatted; Product date: formatted
Analysis
After analysing and pointing out the errors, the following analysis was done on it:
- "New" and "Old" Customer Age Distributions
- Bike-related purchases over the last 3 years by gender
- Job industry distributions
- Number of cars owned and not owned in states
- RFM Analysis and Customer Classification.
Personal Project from an open opportunity provided by KPMG for budding Data Analyst!