Difference between revisions of "ANLY482 AY2016-17 T2 Group21 : PROJECT FINDINGS"
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+ | 1. Customers influx during lunch hours and after dinner | ||
+ | 2. Influx of customers during lunch is prominent during collection launch days | ||
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Revision as of 02:02, 23 February 2017
Exploratory Data Analysis
Our team brokedown Dressabelle's user base in three categories:
- Guest Customers (those that purchase without an account)
- Registered Customers (those that purchase with a registered account)
- Registered Users (those that have an account but has never purchased anything)
Our team weighted customers according to their contribution towards Dressabelle's revenue.
![Customervalue.png](/ANLY482/img_auth.php/thumb/6/6e/Customervalue.png/500px-Customervalue.png)
Findings:
1. Top 25% of most valuable customers gives 72.52% of revenue
2. Top customers on average orders 12 times more than bottom tier customer
![Userreg.png](/ANLY482/img_auth.php/thumb/7/72/Userreg.png/500px-Userreg.png)
Findings:
1. Huge growth in 2013-14
2. Large growth of non-buyers in 2016, possibility due to offline referral
![Regbyweek.png](/ANLY482/img_auth.php/thumb/1/17/Regbyweek.png/500px-Regbyweek.png)
Findings:
Huge spikes of customers on Sunday and Thursday, which corresponds to weekly collection launches
Findings: 1. Customers influx during lunch hours and after dinner 2. Influx of customers during lunch is prominent during collection launch days