Difference between revisions of "ANLY482 AY2016-17 T2 Group21 : PROJECT FINDINGS"
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* Customer influx during lunch hours and after dinner | * Customer influx during lunch hours and after dinner | ||
** Influx during lunch is prominent during days of collection launch | ** Influx during lunch is prominent during days of collection launch | ||
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<b>Orders</b> | <b>Orders</b> | ||
* Decrease in the average product pricing leads to an increase in customer order size and an overall increase sales revenue generated per order | * Decrease in the average product pricing leads to an increase in customer order size and an overall increase sales revenue generated per order | ||
| − | * Hypothesis: Dressabelle's customer base is price sensitive | + | * <i><b>Hypothesis:</b> Dressabelle's customer base is price sensitive</i> |
<b>Order Source</b> | <b>Order Source</b> | ||
* Organic and referrals are the order mediums for at least 54% of the new customers | * Organic and referrals are the order mediums for at least 54% of the new customers | ||
| − | * Email is the most effective medium for generating subsequent orders | + | * Email is the most effective medium for generating subsequent orders for repeated buyers |
| − | < | + | ** <i><b>Hypothesis:</b> Email is an effective marketing channel for user retention</i> |
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==<div style="background: #404041;font-weight: light; padding:0.3em; text-transform:uppercase;letter-spacing:0.1em;font-size:18px; font-family: 'Century Gothic'"><font color=#ffffff><center>Exploratory Data Analysis</center></font></div>== | ==<div style="background: #404041;font-weight: light; padding:0.3em; text-transform:uppercase;letter-spacing:0.1em;font-size:18px; font-family: 'Century Gothic'"><font color=#ffffff><center>Exploratory Data Analysis</center></font></div>== | ||
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Our team weighted customers according to their contribution towards Dressabelle's revenue. | Our team weighted customers according to their contribution towards Dressabelle's revenue. | ||
| − | [[File:Customervalue.png|center|600px]] | + | <div>[[File:Customervalue.png|center|600px]] |
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<b>Findings:</b> | <b>Findings:</b> | ||
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<div style="font-size:18px"><b>Understanding User Growth</b></div> | <div style="font-size:18px"><b>Understanding User Growth</b></div> | ||
| − | [[File:userreg.png|center|840px]] | + | <div>[[File:userreg.png|center|840px]] |
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<b>Findings:</b> | <b>Findings:</b> | ||
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</div> | </div> | ||
| − | [[File:regbyweek.png|center|840px]] | + | <div>[[File:regbyweek.png|center|840px]] |
| − | + | <b>Findings:</b> | |
Huge spikes of customers on Sunday and Thursday, which corresponds to weekly collection launches | Huge spikes of customers on Sunday and Thursday, which corresponds to weekly collection launches | ||
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| − | [[File:regbyhour.png|center|840px]] | + | <div>[[File:regbyhour.png|center|840px]] |
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<b>Findings:</b> | <b>Findings:</b> | ||
1. Customers influx during lunch hours and after dinner | 1. Customers influx during lunch hours and after dinner | ||
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<div style="font-size:18px"><b>Understanding Revenue</b></div> | <div style="font-size:18px"><b>Understanding Revenue</b></div> | ||
| − | [[File:revenue.png|center|840px]] | + | <div>[[File:revenue.png|center|840px]] |
| − | + | <b>Findings:</b> | |
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1. Sales tends to peak in May | 1. Sales tends to peak in May | ||
2.Sales pattern in 2016 did not follow the usual sales trend | 2.Sales pattern in 2016 did not follow the usual sales trend | ||
</div> | </div> | ||
Revision as of 02:23, 23 February 2017
| Mid-Term |
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Executive Summary
Users
- One third of the registered users do not make purchases
- Top 25% of most valuable customers gives 72.52% of revenue
- On average, customers in the top segment orders 12 times more than bottom tier customers
- Large growth in offline buyers
- Due to offline referrals
- Huge spikes of customers on Sunday and Thursday which corresponds to their weekly collection launches
- Customer influx during lunch hours and after dinner
- Influx during lunch is prominent during days of collection launch
Orders
- Decrease in the average product pricing leads to an increase in customer order size and an overall increase sales revenue generated per order
- Hypothesis: Dressabelle's customer base is price sensitive
Order Source
- Organic and referrals are the order mediums for at least 54% of the new customers
- Email is the most effective medium for generating subsequent orders for repeated buyers
- Hypothesis: Email is an effective marketing channel for user retention
Exploratory Data Analysis
Understanding User Base
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)
Findings: ⅓ of total users do not make purchases
Our team weighted customers according to their contribution towards Dressabelle's revenue.
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
Understanding User Growth
Findings:
1. Huge growth in 2013-14
2. Large growth of non-buyers in 2016, possibility due to offline referral
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
Understanding Revenue
Findings: 1. Sales tends to peak in May
2.Sales pattern in 2016 did not follow the usual sales trend
