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How to Increase Customer Loyalty Using Cluster Analysis
and Decision Tree
Analysis of customer behavior and service
design
What is the most important factor in CRM or servicing
customers?1.
2. Identify Needs of customers
3. Loyalty
Questions on brand loyalty
• Why is brand royalty so important to most companies?
Perspectives of Brand Loyalty
• Customer loyalty as customer’s commitment or attachment to a brand, store, manufacturer, service provider
Or• Entity based on favorable attitudes and
behavioral responses, such as repeat purchases
• Ex) ‘Red Devil’ for national soccer team
Organizations and their loyal customers
• Airlines• Credit card companies• Internet stores• Banks• Car dealers• Cell phone
Brand Loyalty as Behavior
• Rate of repurchasing [examples] Chicago Bulls, Cubs, Heinz, Crispy Cream donuts, Starbuck• Proportion of purchase = the number of time the most frequently purchased brand
total number of times the product category is purchased
5 types of customer behaviors
• Undivided loyalty: A A A A A A A A A• Occasional switcher: A A A B A A A C• Switched loyalty: A A A A A B B B B B• Divided loyalty: A A A B B B A A A B B
B• Indifference: A B C D A B C D A B C D
Churn rate
• Switch from one brand to other brand
• Customers RFM (key variables in market segmentation, also understanding loyal customer)
- recency - frequency - monetary: average purchase size
Brand loyalty as attitude
• Why customer has loyalty on a brand?
[example] bank, internet shop, airlines, credit
cards• Brand loyalty is a behavioral
response to an attitude toward a brand
Loyalty versus inertia
Inertial loyalty
• Habitual
• Latent loyalty -strong commitment -low repeat purchase [example] SONY PS2, Nintendo
Factors that affect customer loyalty
(Intimacy)
Attitudinal and behavioral components of loyalty
15
Personalization of Service in the Web Using Intimacy Theory,
Cluster Analysis, and Decision Tree
: How to increase intimacy with customers
Introduction
• Face – to – face• Object – medium - object
– Digital interaction with Internet
• Setting Interpersonal Distance– Intimacy theory– Web interface development
Research Background• Designer , Web Master based pages…
– Personalization, categorization- User , customer based web pages
• Relations adjustment of interface by emplyee
Frequent Customer
Not Frequent
Clerk
Proxemics• People surround themselves with a
“bubble” of personal space(Hall, 1966)
Intimate distance: 0 ~ 1.5 feet(0.45 m)
Personal distance: 1.5 ~ 4 feet(1.2 m)
Social distance: 4 ~ 12 feet(3.6 m)
Public distance: more than 12 feet
person
Machine Learning Modeling
• Prediction(supervised learning)– Inputs output– Neural networks, rule induction,
regression
• Clustering(unsupervised learning)– Inputs similarity– k-means
• Association– Input output
Cluster Analysis of Customers
Cluster Distribution
Cluster
Ratio(%)
CountIntimacy
Level
A 20.86 34 2.41
B 25.77 42 3.02
C 24.54 40 3.85
D 28.83 47 2.87
• Cluster A– if (Rep = good) And (period = 6
months) Or (rep = excellent) Or (Rep = good) And (visit = weekly)
Rule Set for each cluster
Cluster B if (Rep = good) And (period = 1 year) Or (rep = good) And (visit = monthly) And (period =
1year) Or (rep = good) And (visit = monthly) And (period =
1month) Or (rep = good) And (visit = monthly) And (period =
2years) Or (rep = good) And (visit = monthly) And (period =
6months) Cluster C
if (Rep = good) And (visit = 1 year) Or (Rep = good) And (visit = > 1 year Or (Rep = good) And (visit = monthly) And (period = > 2
years) Or (Rep = good) And (visit = daily)
Cluster D if (Rep = middle) And (period = 1month) Or (Rep = middle) And (period = 2years) Or (Rep = middle) And (period = >2years
• Physical distance
Analysis from Rules/Decision Tree
object object
Psycholgical distance
reputationreputation No. of visitsNo. of visits
Membership periodMembership period
X
Y
Dynamic Web Page Personalized
Main Page
Logged/personalizing
Web Page Type IFor Cluster A
Web Page Type IIFor Cluster B
Web Page Type IIIFor Cluster C
Web Page Type IVFor Cluster D