The aim of the project is to contribute to the development of the modern approach of customer segmentation using portfolio analysis for B2B markets specifically for Bangladesh in a most efficient way using a modern tool (i.e. CRM). A suggestion for the developer in Bangladesh b2b markets.

1. Customer Segmentation
Using Portfolio Optimization
for B2B Markets
A SUGGESTION FOR THE DEVELOPER IN BANGLADESH B2B MARKETS
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2. Supervised by
Dr. Supratip Ghose
Associate Professor
Submitted by
 Md Mazedul Islam Khan
143010200006
 Diponkar Mondal
143010200004
 Md. Mohiminol Islam
143010200014
 Ohaidur Rahman
143010200020
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3. Content
3
 Motivation
 Survey
 Problem Statement
 Introduction
 Methodology
 Experimentation
 CRM
 Conclusion
 Future Works

4. Motivation
Most of the work described in this project was conducted at the University of
Information Technology & Sciences (UITS). The reasons for conducting the project
are:
 I have served as a customer service and relationship engineer for more than 5
years and, thus, have a good understanding of assessment practices in the
customer segmentation and portfolio optimization.
 I have been actively involved in the process of customer segmentation and
portfolio optimization in the international market for quite a long time.
 Customer segmentation using portfolio optimization for Bangladeshi B2B
markets isn’t very known.
Thus, the potential for future of customer segmentation using portfolio
optimization is apparent for Bangladeshi market. So, this project can be a good
experience for our future career.
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5. Surveys
 [1] Bao-li Wang, Hong-yuan Tian, Xin-lan Chen. (2010). The Study on Customer
Relationship Management of B2B Enterprise Based on the Brand Promise of
Customer Perception. International Conference on E-Product E-Service and E-
Entertainment. IEEE.
 [2] Jingyuan Yang, Chuanren Liu, Mingfei Teng, March Liao, Hui Xiong. (2016).
Buyer targeting optimization: A unified customer segmentation perspective.
IEEE International Conference on Big Data (Big Data). IEEE.
 [3] Olga Petukhova. (2016). Customer segmentation for B2B markets. St.
Petersburg University. Research Paper.
 [4] Kumar, Nayan. (2018). Digital marketing in Bangladesh. BRAC university.
Internship report.
 [5] Jahan, Israt. (2013). A study of business to business website in Bangladesh.
Daffodil international university. Thesis.
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6. Related Works
 Paper [1] represents the customer relationship management for enterprise
level B2B businesses.
 Paper [2] represents an unified customer segmentation and buyer
targeting optimization using CRM.
 Paper [3] represents the research of an international university for B2B
markets using CRM.
 Paper [4] represents the new research agenda for business segmentation
in Bangladesh market.
 Paper [5] represents the marketing strategy selection, marketing metrics,
and performance for Bangladesh B2B markets.
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7. Timeline 7
May June July August
Survey
Methodology
Experiment
CRM

8. Problem Statement
How to customer segmentation using portfolio optimization for B2B markets
in a most efficient way?
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9. Introduction
 The aim of the project is to contribute to the development of modern
approach of customer segmentation using portfolio analysis for B2B
markets.
 B2B markets in Bangladesh are rich. However, most businesses in
Bangladesh are not very familiar with customer segmentation using
portfolio analysis.
 This project will be helpful for Bangladesh B2B markets to improve their
customer segmentation using portfolio analysis in a most efficient way
using the modern tools (i.e. CRM).
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10. What is customer segmentation?
 It is a practice of dividing a customer based into groups of individuals that
are similar in specific ways relevant to business.
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Better matching
of customer
needs
Enhanced
opportunity for
growth
Retention of
customer
Targeted IM
communications
Share of the
market segment
Enhanced
operation
efficiency
Better share of
customer wallet

11. What is portfolio optimization?
It is a process of selecting the best portfolio, out of the set of all portfolios
being considered.
 It ensures higher return for investments.
 It helps to minimize the total costs.
 It ensures lower financial risks.
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12. Methodology
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13. Business segmentation
Business
segmentation
Macro
segmentation
Geographic
Customer Type
Customer Size
Product Size
Micro
segmentation
Purchasing
Criteria
Purchasing
Strategy
Importance of
Purchase
Personal
Characteristics
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14. Customer portfolio analysis based on
financial portfolio
𝑉 =
𝑖=1
𝑁
𝑗=1
𝑁
𝜎𝑖𝑗𝜔𝑖 𝜔𝑗
Formula: Markowitz’s portfolio selection model
 Minimize the total risk of the entire customer portfolio to achieve higher
returns.
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𝑉 = Variance 𝜔𝑖 = Average profit rate
N = Amount of client invested 𝜔𝑗 = Invested ratio by client
𝜎𝑖 = Minimum expected profit rate

15. Variance comparison 15
 Lower variance results low risk, high return.
 Higher variance results high risk, low return.
0
2.5 2.5
00
0.5 0.5
00
0.5
1
1.5
2
2.5
3
High Low

16. The process of customer portfolio
optimization
 The customers should be grouped by one or several variables.
 The Industry beta can be used to measure the stability of the returns for
each industry.
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Variable Calculation Explanation
Industry beta (𝛽)
I𝑏 =
𝐶𝑜𝑣 𝑋𝑖, 𝑋𝑝
𝑉𝑝
Industry beta indicates the
degree to which each industry
contributes to the risk of the
entire customer portfolio.
𝑪𝒐𝒗 𝑿𝒊, 𝑿𝒑 - covariance
between industry return and
the return of the overall.
𝑽𝒑 – variance of the return for
the entire customer portfolio.

17. Risk of the entire portfolio calculation
 Comparing current customer portfolio and efficient customer portfolio
using the frontier graph.
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Variable Calculation Explanation
𝑉𝑝 - Variance of
portfolio 𝑉𝑝 =
𝑗=1
𝑛
(𝑥𝑗 − 𝑥𝑝) 2
𝑁 − 1
The formula allows to
compare the
performance of the
portfolio combinations.

18. Reward ratio calculation
 Find the most sustainable and profitable attractive portfolio.
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Variable Calculation Explanation
Reward Ratio (𝑅𝑅)
𝑅𝑅 =
𝑅𝑖
𝜎𝑖
Reward is measured as
the return above the risk
free rate.
𝑅𝑅 – customer reward
ratio.
𝑅𝑖 – return for the
portfolio.
𝜎𝑖 – standard deviation
of the return.

19. Experimentation
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20. Industries sales variability assessment
 Manufacturing industry
exhibits stable growth
pattern in costs over
three years.
 The industry that brings
the higher returns also
generates the largest
costs.
 Real Estate, Food and
Beverage production
industries register
modest growth.
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0
10000
20000
30000
40000
50000
60000
70000
2013 2014 2015
Annual invoices dynamics
Manufacturing
Food and Beverage
production
Real Estate
Automotive

21. Industry average return
 The individual average return of each industry was calculated using the
Industry beta coefficient.
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Average r
Manufacturing Real Estate Food and Beverage Automotive
8% 5.8% 7.7% 6.7%
Table: For three years period (2013-2015)

22. Efficient customer portfolio options
 The efficient frontier was constructed to compare the possible efficient
portfolios using the Markowitz’s portfolio selection model.
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5.5
6.5
7.5
8.5
0 2 4 6 8 10 12
Variance(*10-5)
Efficient frontier portfolios
return%

23. Efficient customer portfolio options
 Reward ratio calculation to compare the portfolios risk.
23
Desired return Risk Risk-Reward ratio
EP 1 6.00% 1,774426206 14,24368232
EP 2 6.50% 2,780055379 12,32782989
EP 3 7.00% 4,100930357 10,9309232
EP 4 7.50% 5,722805392 9,914179428
EP 5 8.00% 7,692281378 9,121419002

24. Current customer portfolio analysis
 The graph highlights the current portfolio of customers can be considered
as efficient.
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5.5
6.5
7.5
8.5
0 2 4 6 8 10 12 14
The efficient frontier portfolio and
current portfolio risk and return.
Variance(*10-5)
return%

25. CRM
CUSTOMER RELATIONSHIP MANAGEMENT
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26. Dashboard 26

27. Dashboard 27

28. Customers 28

29. Proposals 29

30. Estimates 30

31. Invoices 31

32. Payments 32

33. Items 33

34. Sales - Total Income 34

35. Sales - Payment Modes 35

36. Expenses 36

37. Expenses vs Income 37

38. Leads 38

39. Analysis 39

40. Client Dashboard 40

41. Project Overview 41

42. Invoices 42

43. Contracts 43

44. Conclusion
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45. Conclusion
 The task of creating efficient customer portfolio is solved with with
application of financial portfolio theory, which demonstrates how investors
can create an optimal portfolio that will maximize returns depending on
the given risk level.
 The efficient portfolio is constructed in order to compare possible efficient
portfolio combinations with the current customer portfolio.
 CRM was used to determine how to calculate all these in an efficient way.
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46. Future Work
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47. Future Work
 Further research should be conducted in order to test and confirm the
applicability of the approach to other B2B service companies.
 The sample given by a random B2B business constitutes only a part of the
all clients. Thus, the analysis doesn’t present the real situation to the
overall company performance. So, we’ll need to perform the analysis using
real world data.
 All the analysis calculations need to be well organized in the CRM to
ensure the results are correct.
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48. Thank you …
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