This document analyzes sales data from a coffee cafe between 2010-2011. It finds that food generates the most sales and discounts. Top selling food items include shakes and paninis, while beers and drafts are best sellers for liquor. Sales are highest on weekends and nights. The analysis identifies lower performing items and recommends combos and meals based on high selling items. RStudio and Tableau were used for the analysis.

1. Coffee Cafe Night Case Study
(Marketing & Retail Analytics)
Project
by
Saleesh Satheeshchandran

2. Summary of the Data
• The starting date is
01-04-2010
• Ending date is 31-
03-2011
• There are 14580
Observations.
• Time shows a 24
hours Operations
• Discounts are given
very rarely
• Inter quartile range
of pricing is Rs.95
to Rs.2100

3. Boxplot to show Outliers
• Rates • Discount • Total
• The pricing of items
have high number
of outliers in the
upper range.
• The discounts
offered have high
number of outliers
in the upper range.
• The total billing has
high number of
outliers in the
upper range.

4. • The category Food generates maximum
sale transactions and the highest
revenue.
• The same category accounts for
maximum discounts given.
• Merchandise is the category that
contributes the least in terms of the
transactions as well as revenue.

5. • Cappuccino, Red Bull, Lemon Iced tea, Berry Blast and Café latte are the highest
moving items in the category Beverages.
• Great Lakes Shake, JR.CHL Avalanche, Poutine with Fries, BMT Panini and Oreo
Cookie shake are the highest selling items in Food.
• Carlsberg, Tuborg and KF Draught are the highest moving items in the category
Liquor.

6. • Red Bull Sheesha, Plain Jain, Party Charges, Rose flavors and Guava are the highest selling items in
Miscellaneous.
• VLN Cab Sauv, Sula Blush Zinafandel, Red Sangria, VLN Chenin Blanc are the highest selling items in Wines.
• Nirvana Hukah, Sambuka, Mint, Kolkata Mint and NRG Hookah are the highest selling items in Tobacco.

7. • Both the
Volumes and
revenue are high
towards the
weekends.
• In the mid of the
week they are
comparatively
low.

8. • Beverages, food,
Liquor and
Tobacco shows a
variation through
week peeking at
the weekends.
• Wines,
Merchandise and
Miscellaneous
items do not
show much
variation.

10. • General trend
shows the sales
picking
momentum at
afternoon hours
and reaches a
peak at night
hours.
• It is minimal
during the
morning hours.

11. Items to Eliminate (Lower sale items in each category)

12. • Generally there is
no much of a
variation during
the course of an
year.
• There is a peak
during year ends
or new year.
• Merchandise,
Miscellaneous
and Wines remain
flat throughout
the year.

13. Frequency Plot

14. Association Rules from R

15. R codes Screenshot

19. Suggested Combos
• LEMON INFUSED CHAR GRILLED
VEG + HERB ROAST CHICKEN
• CAFFE LATTE + HAZELNUT FLAVOUR
• SATAY CHICKEN PANINI + ADD FRIES
• B.M.T. PANINI + FRENCH FRIES
• COUNTRY ROAST CHICKEN PANINI +
ADD FRIES
• CAPPUCCINO + ADD HAZELNUT
FLAVOUR
• VANILLA ICECREAM + GREAT LAKES
SHAKE
Suggested Meal
• COTTAGE CHEESE PANINI
+
• FRIES
+
• CAPPUCCINO OR GREAT LAKES
SHAKE

20. Tools Used and Reference
• R Studio 1.2.1335
• Tableau Desktop – Public Edition
• Link to Tableau Public file
https://public.tableau.com/profile/saleesh.satheeshchandran#!/vizho
me/Project-8SupportFile/CoffeeDayAnalysis?publish=yes