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Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere

Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

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Page 1: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Final Project PresentationMatthew Chun, Kay Hiratsuka, Jiarun Zhang

Special thanks to Jacob LaRiviere

Page 2: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Ratio of Stock Codes

The revenue of the top four StockCodes counts for 6.60% of the total revenue.

Page 3: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Ratio of Customers

The revenue of the top four Customer ID’s count for 11.26% of the total revenue.

Page 4: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Spurt or Smooth Buying Behavior

Customers tend to purchase more at the end of the year near the holidays.

Until August, customers tend to have smooth buying behaviors.

Page 5: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Spurt or Smooth Buying Behavior Cont.

ACF captures the time dependence effect on revenue over time. From this graph, we can see how much customers spend today do not have a huge impact on how much the customers will spend tomorrow.

Page 6: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Customers who Buy the Top 4 Goods

Total Number of Distinct Customers that bought the top 4 goods: 1796

Customers who buy the top 4 goods buy a lot of other products and spend a significant amount on them.

Page 7: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Product’s Name Elasticity

*PAPER CRAFT , LITTLE BIRDIE (23843)

*N/A

REGENCY CAKESTAND 3 TIE (22423)

1.23517

WHITE HANGING HEART T-LIGHT HOLDER (85123A)

2.70215

JUMBO BAG RED RETROSPOT (85099B)

2.6224

Demand Elasticities for the Top 4 Goods

*PAPER CRAFT , LITTLE BIRDIE(23843) had only one data point. Therefore, we could not calculate the elasticity.

Table shows top 4 goods in decreasing revenue

Page 8: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Products Lerner’s Index

PAPER CRAFT , LITTLE BIRDIE (23843)

N/A

REGENCY CAKEST AND 3 TIE (22423)

0.8096

WHITE HANGING HEART T-LIGHT HOLDER (85123A)

0.3701

JUMBO BAG RED RETROSPOT (85099B)

0.3813

Value Based Pricing for the Top 4 Goods

● Table shows the top 4 goods ordered by decreasing revenue

● From largest to smallest markup is 22423, 85099B, 85123A

Page 9: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Customer Behavior

Large spending customers buy many more products than low spending customers.

There is a large difference in spending from top and bottom customers.

Leverage big buyers to sell different goods!

Page 10: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Customer Behavior Cont.

Target Dutch, Irish, and Australian Customers

The average hours between purchases for the top 4 customers is significantly less than for the rest of the customers (67.82 hours).

Page 11: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Summary

1. Impose value-based pricing on the first 3 quarters where the sales is smooth to increase the revenue

2. Prioritize evaluating pricing in Dutch, Irish, and Australian markets first as they are the big spenders on the top 4 goods

3. Leverage big buyers by selling them other goods

Page 12: Final Project Presentation · Final Project Presentation Matthew Chun, Kay Hiratsuka, Jiarun Zhang Special thanks to Jacob LaRiviere. Ratio of Stock Codes The revenue of the top four

Appendix and Extra Analysis Materials

1. analysis.py/analysis.html - create charts and analysis for questions 3 and 52. AvgFrequency.py/AvgFrequency.html - calculate average purchase frequencies3. FinalProjectElasticity.Rmd/FinalProjectElasticity.html - calculate elasticity for

question 44. part2-ts.R - creates the ACF plot5. Part2.xlsx - analysis on question 1, 2, and 5 and creates more graphs