The document discusses using social media data and customer relationship management (CRM) data to perform customer segmentation, targeting, and positioning. Key points: 1. The study combines CRM purchase history and Facebook interaction data to calculate RFM scores and segment customers into four clusters. 2. The clusters represent different customer profiles based on shopping and dissemination behaviors - from high values in both to low values in both. 3. Customers in each cluster are targeted on Facebook pages and CRM categories. Positioning identifies topics of most interest for each cluster. 4. The hybrid analysis of social media and CRM data provides insights to better understand customer segments.

1. THE POWER OF CUSTOMER VALUES
WITH SOCIAL MEDIA IN THE MARKET
SEGMENTATION
JeffreyTsai

2. Since Social media becomes a buzz
word, there are many users to ….
2

3. Increased exposure for companies’ business is the
marketers use social media for sale the things.
Source: http://www.pagetrafficbuzz.com/learn-companies-connecting-social-media/17235/

4. Learning from the markets, recognizing the
group of customer patterns still a critical
job for marketers
Because marketers must have the vision to see the value of customers

5. According to Woodruff (1997)
“a customer perceived preference for and evaluation of those products
attributes, attribute performances, and consequences arising from use that
facilitate (or block) achieving the customer’s goals and purposes in use
situations” by Woodruff

6. Segmentation
Identifying meaningfully
different groups of
customers
Targeting
Selecting which segment to
serve
Positioning
Implementing chosen image
and appeal to chosen
segment
Marketers
Customers
STP is a familiar
strategic approach
in Modern
Marketing.
Segmentation, Targeting and Positioning (STP)
Process

7. Recency
Frequency
Money
When did the customer
last make a purchase?
How often is the customer
making purchases?
What is the customer’s
return rate?
RFM models is a scoring model and do not explicitly provide a dollar number for
customer value. However, RFM are important past purchase variables that should be
good predictors of future purchase behavior of customers. (Gupta et al., 2005)
RFM Model

8. We used practical data
combining RFM model and
the STP strategy with data-
mining in CRM & Social
Media.
CRM Records
FB Interactive
Records
RFM Scores
Calculations
Social interactive Fanspage
CRM shopping category
Customer
Segmentation
Association Rules
&
Jaccard Coefficient
Data
Presentation
Customer
Targeting
Modularity Algorithm
&
Betweenness Centrality
Data
Preprocessing
Customer
Positioning
Research Process
K-means

9. CRM Records
FB Interactive records
Data Format
Facebook_ID Post_time page_id page_name post_id
100000998715544 2015/1/1 152905932107 152905932107_10152635799292108
1786662017 2015/1/1 152905932107 152905932107_10152635799292108
100001469254677 2015/1/1 127628276929 127628276929_10152470414971930
100000802633627 2015/1/1 127628276929 127628276929_10152478522571930
100007917434130 2015/1/1 127628276929 127628276929_10152478522571930
Facebook_ID Money Among Date Product name Product category
100000144441048 840 1 2015/1/1 12
100000199943019 699 1 2015/1/1 6
100000144441048 150 1 2015/1/1
( .159)2015
100000998715544 238 1 2015/1/1
101
100000998715544 227 1 2015/1/1
( ) :
Connections

10. https://www.facebook.com/127628276929/posts/10152470414971930

11. Data Preprocessing
Unit: Month
CRM
Facebook
1st day of next month
- trading date
E.g. : 2/1 - 1/1 = 31
Accumulating a
month’s BUY frequency
E.g. : 1/1 to 1/31
bought 5 books
Accumulating a
month’s spending
E.g. : Accumulating
5 times spending = 1000
1st day of next month
- visiting date
Accumulating a
month’s frequency
of put the like
Accumulating a month’s
interactive CW Pages’
posts / Accumulating a
month’s total visiting
fanspage
E.g. : 2/1 - 1/20 = 11
E.g. : 1/1 to 1/31
push the like button
4 times
E.g. : 10 CW pages posts
/ Accumulating100 posts
= 0.1

12. Facebook ID
CRM Facebook
R F M R F M
1438706957 9.333 9 2783 18 1 0.018
1667846450 27.024 1 587.5 12.333 5.667 0.103
100000294682354 6 5 1553 31 0 0
636098539 3.548 1 1980 31 0 0
100000193167290 18.617 4 774 22 1 0.007
1018548854 5 2 585 4.75 20.25 0.292
The result of Data Preprocessing
near end of
month
Spend
money
number
of books
near middle
of month
visiting
weight
number of
interaction

13. RFM Scores
We based on the 80/20 rules to segment the data into five different levels
Locating the buy times
1st level score = 3.0
2nd level score = 8.0
3rd level score=13.0
4th level score = 20.0
The range of scores
Reader <= 3.0 = 1
3.0 < Reader <= 8.0 = 2
8.0 < Reader <=13.0 = 3
13.0 < Reader <= 20.0 = 4
Reader > 20.0 = 5
The distribution of the RFM scores
Scores
level
CRM Facebook
R F M R F M
1 177 2080 215 1431 2245 1629
2 699 306 737 166 146 347
3 768 64 810 319 37 211
4 554 5 535 438 22 179
5 258 1 159 102 6 90
a lot among readers
don't read CW’s
Facebook

14. The result of RFM Scores
Facebook ID
CRM Facebook CRM_scores Facebook_scores
R F M R F M R F M R F M
1438706957 9.333 9 2783 18 1 0.018 4 3 4 3 1 1
1667846450 27.024 1 587.5 12.333 5.667 0.103 2 1 2 3 1 2
100000294682354 6 5 1553 31 0 0 4 2 4 1 1 1
636098539 3.548 1 1980 31 0 0 5 1 4 1 1 1
100000193167290 18.617 4 774 22 1 0.007 3 2 3 2 1 1
1018548854 5 2 585 4.75 20.25 0.292 4 1 2 4 2 4
They aren’t active user in each CW Fanspage

15. Customer segmentation: K-means
Num. of observations
Clustering
1 428
2 896
3 497
4 635
Clustering result
Clustering
1 2 3 4
CRM
R 2.9 2.71 3.27 3.29
F 1.18 1.06 1.22 1.34
M 2.92 2.16 2.83 3.89
Facebook
R 3.48 1.06 3.74 1.08
F 1.43 1 1.25 1
M 3.84 1.03 1.78 1.05
1. High Disseminating value, normal shopping value
2. Both shopping & disseminating is low
3. High shopping value, normal disseminating value
4. High shopping value, low disseminating value
Loyal readers,
sometimes buy
some books
Not loyal
customers
loyal buyer,
sometimes reader
from Facebook
Loyal Buyers

16. Shopping RFM
Disseminating RFM
1
2
3
4
?

17. 17
Facebook_ID
CRM Facebook
Clusters
R F M R F M
1438706957 4 3 4 3 1 1 3
1667846450 2 1 2 3 1 2 3
100000294682354 4 2 4 1 1 1 4
636098539 5 1 4 1 1 1 4
100000193167290 3 2 3 2 1 1 4
1018548854 4 1 2 4 2 4 1
Customer Targeting
Facebook_ID Clusters
Visiting Fanspages
(Likes)
Buy Categories
1438706957 3 FB1, FB2, FB3 C1, C2
1667846450 3 FB2, FB3, FB5, FB6 C2, C3, C4
100000294682354 4 FB2, FB5, FB6, FB8 C2, C3, C4
636098539 1 FB1, FB4, FB5, FB7 C1, C3, C4, C5
Hybrid the social interactive Fanspage & CRM shopping categories

18. The customers are concerning the
Fanspage’s Posts
5652
3754
3053
2717
cheers 2212
2149
1362
1257
952
928
877
managertoday 855
766
676
630
‧ 616
nexttv 567
552
smart 537
High Disseminating value, normal shopping value
Customer Positioning
The result of 1st clustering : 428
Design & Stylish
Parenting
Traveling
Complex

19. Parenting
Health & education
Cheer
Health
Magazine
Traveling
Parenting
Illustrator
Celebrity
Cosmetic
Design
Business
Customer Positioning
The result of 1st clustering : 428

20. The customers are concerning the
Fanspage’s Posts
519
410
tripass 367
322
voguetaiwan 306
275
_crm 247
245
icook 228
213
goodlife 208
184
183
(
)
182
_crm
164
_crm 162
goodtv 158
157
_crm
145
141
Foundation & Volunteer
Political
Traveling
Magazines
New Tech & Entrepreneur
Customer Positioning
The result of 2nd clustering : 896
Despite both shopping & disseminating is low, they sometimes buy the books from the Internet

21. Customer Positioning
The result of 2nd clustering : 896
Magazine & Health
Family & Parenting
Education
Parenting
Cooking
Cosmetic

22. The customers are concerning the
Fanspage’s Posts
icook 4986
4380
3411
2861
mamaclub 2584
2490
2362
2347
voguetaiwan 2172
2170
sisy'sworldnews
2093
1918
1801
qqmei 1681
1635
( ) 1628
cheers 1606
-
lessonsfrommovies
1505
tripass 1410
1380
Magazine
Parenting & cooking
Customer Positioning
The result of 3rd clustering : 497
Political
Celebrity
Women’s talk
Illustrator
High shopping value, normal
disseminating value

23. Customer Positioning
The result of 3rd clustering : 497
Parenting & Living
Women’s talk
Financial
Health
Parenting
Cooking
Traveling
Celebrity
Investment
Soul
Illustrator
Health
Celebrity

24. Political
New Tech & Entrepreneur
Illustrator
The customers are concerning
the Fanspage’s Posts
_crm 650
gracetw 332
_crm 282
212
_crm 184
vivianhsu 182
_crm 182
icook 175
165
159
158
duncandesign 156
133
133
130
janethsieh 114
yilan 109
pansci 109
2xpeople2 108
Customer Positioning
The result of 4th clustering : 635
High shopping value, low
disseminating value

25. Customer Positioning
The result of 4th clustering : 635
Investment
Stylish
Parenting
Cooking
Cosmetic
Celebrity
Financial & Magazine
Parenting

26. Conclusions
1. We established a hybrid method to combine the CRM
and social media data.
2. We found the difference of each clusters, which the
company focuses on.

27. Thanks for your
attention
This is our web site:
http://leaderboard.ideas.iii.org.tw/home