1. Cases on Association Rules
IT for CRM Strategies
Cases on Association Rules

2. CASE 1:
Icecream -Target Brands & Variables

3. 1. Icecream -Target Brands & Variables
Varaibles
Gusttimo
Baskin Robbins
Natture
Haagen-dazs
Etc.
Taste
Price
Mood
Distance
Brand Image
Service
Rumor

4. Where do you visit the most for ice cream?
2. Questionnaires
Where do you visit the most for ice cream?
①.Gusttimo ②.Baskin Robbins ③.Natture ④.Haagen-daz ⑤. Red Mango ⑥. Palazzo ⑦.etc
Why do you visit there?
①.Taste ②.Price ③.Mood ④ .Distance ⑤. Image ⑥. Service ⑦. Rumor

5. Not important-------------Most important
3. Questionnaire Method
Choose the number below according to your value level when you choose to eat ice cream
Classification
Not important Most important
Taste
(1) (2) (3) (4) (5) (6) (7)
Price
Mood
Distance
Image
Service
Rumor

6. 4. Average value on each variables

7. 5. Derive rules by using Magnum Opus
Mood -> Red Mango [Coverage=0.025 (4); Support=0.019 (3); Strength=0.750;
Lift=4.11; Leverage= (2.3); p=0.0195]
Red Mango -> Mood [Coverage=0.182 (29); Support=0.019 (3); Strength=0.103;
Baskin -> distance [Coverage=0.390 (62); Support=0.145 (23); Strength=0.371;
Lift=2.03; Leverage= (11.7); p=1.28E-006]
distance -> Baskin [Coverage=0.182 (29); Support=0.145 (23); Strength=0.793;
Gustimo -> Taste [Coverage=0.258 (41); Support=0.233 (37); Strength=0.902;
Lift=1.56; Leverage= (13.3); p=3.18E-007]
Taste -> Gustimo [Coverage=0.579 (92); Support=0.233 (37); Strength=0.402; 7

8. CASE 2: Lotte World

9. Problem Definition & constraints Phases Alternatives
Contents 1
Problem Definition & constraints
Phases
Alternatives
1. Using RFID
2. Exit Poll
4. Result Example
5. Effectiveness & application

10. Problem Definition & Phases 2
- Attraction locating
: avoid conflict between target segments
- inefficient customer route
 Lower customer satisfaction
Constraints
- Attraction re-location : Impossible
Phases
1. Data Mining
2. Using Model
3. Finding efficient customer route & Promotion strategy
4. Max (Customer satisfaction)

11. Indicating & Choice of Alternatives
HOW – Association Rules 3
Association Rules
Indicating & Choice of Alternatives
1. Using RFID
- Clear understanding about
customer’s moving route, location, time
- Technical Difficulty, and Heavy cost
2. Exit Poll
- Easy application
- Light cost
- Limit in data : quantity, quality
Survey
: Let customers to check all facilities they rode
Make Market-Basket
Association Rules Analysis
: based on Market-Basket

12. Survey Example 4 Basic information gender age Marriage Children
※ Mark Attractions that you rode today
For Lotteworld Adventure
For Magic Island
Adventure of Sinbad
( )
Atlantis
Spain Pirate Ship
Gyro Drop
Frog Hooper
Gyro Swing
Marry-go-round
Bunge Drop
Crazy Bumper Car
Comet Express
Kids Bumper car
Marry-go-Round 3
Ball Battle
Sky Surfing
Flume Ride
Bumper car
Giant Roop
Ghost House
Marry-go-round 2
Castle Music Show
Illusion Odyssey
Fantasy Dream
Out-Law
Automoblile Racing
4D Movies
Kingdom of Children
Magic Theater
EureKa
Puppet Theater
Geneve Excursion Ship
French Revolution
Lake Boat
Jungle Adventure
World Monorail
Rage of Parao
Balloon Travel
dynamic Theater
Animal Theater
Garden Stage Concert
Street Concert
Parade
Basic information
gender
age
Marriage
Children
Age of Children
Place of Residence
others

13. Result Example & Applications 5
1. Student (age 12~18)
- P(Gyro drop  Atlantis) : 70%
2. Parents with Little children
- P(Marry-go-Round  Kids Bumpercar) : 60%
Applications
We will be able to check
: Who is using what kind of facilities
Finding Effective Route
Making Promotion Strategy
Locate extra store at specific customer’s route

14. CASE 3: Gmart case

15. : Gmart located at Yongsan
Data Collection
: Gmart located at Yongsan
- Customer data
POS data from daily transaction
- Location
Chung-pa dong, Yongsa,, Seoul
- Period ~
- Number of data
1,334 cases
- Contents in the data
POS fields names(date, time,
POS manager, receipt number, product name
, quantity, amount, classification)
- G mart system screen -

16. Data Cookies, Milk Yogurt ,Frozen fool Bear, Cookies, Coffee
Milk, Water .

17. Extracted Association Rule
Water
is associated with Cookies
with strength = 0.500
coverage = 0.002: 2 cases satisfy the LHS
support = 0.001: 1 case satisfies both the LHS and the RHS
lift : the strength is times greater than the strength if there were no association
leverage = : the support is (1.0 case) greater than if there were no association
is associated with Coffee and Newspaper