What is the aim of this course?
In consulting you will spend a lot of time on creating presentations to show the results of your analyses to the customer. That is why, data visualization is so important. With proper display of data you have more chances of convincing the customers that your approach makes sense. In this course I will teach how to use different data visualization techniques to show the results of your analyses during consulting projects.
In the course you will learn the following things:
1. What types of slides you should use to present your thoughts
2. What types of charts you should use for data visualization
3. How to read the charts
4. How to create charts in Excel
5. How to create charts in PowerPoint
6. How to create dynamic charts in Excel
For more check the following course
https://bit.ly/DataVisualizationMC
2. 2
In consulting you will spend a lot of time on creating presentations
to show the results of your analyses to the customer.
3. 3
That is why, data visualization is so important. With proper display of data you
have more chances of convincing the customers that your approach makes sense.
4. 4
That is why, data visualization is so important. With proper display of data you
have more chances of convincing the customers that your approach makes sense.
5. 5
In this course I will teach how to use different data visualization techniques
to show the results of your analyses during consulting projects.
6. 6
Target Group What you will learn What you will get
Management Consultants &
Business Analysts
Analysts working in PE, VC funds
Analysts working in PMO or
Strategic Departments
Controllers working in Financial
Department
What kind of charts and slides you
can use during consulting projects
How to read charts
How to create fast and efficiently
good looking charts in Excel and in
Power Point
Ready made analyses in Excel
Templates of slides and charts
List of Recommended readings
(articles, books)
7. 7
How to read charts &
Which chart type you
should use
Essential Charts in Excel
Types of slides you can use
in presentation
How to create charts in
Power Point
Data Visualization using
Conditional Formatting
PivotCharts
Dynamic Charts in Excel
8. 8
This presentation will teach you how to use
different data visualization techniques on the
level of top management consultants
9. 9
What you will see in this presentation is a part of my online course where you
can find case studies showing analyses along with detailed calculations in Excel
Data Visualization for Management
Consultants & Analysts
$190
$19
Click here to check my course
11. 11
In business you have to make a lot of important decisions
In this course I will teach how to use different data visualization techniques
to show the results of your analyses during consulting projects.
12. 12
How to read charts &
Which chart type you
should use
Essential Charts in Excel
Types of slides you can use
in presentation
How to create charts in
Power Point
Data Visualization using
Conditional Formatting
PivotCharts
Dynamic Charts in Excel
15. 15
In consulting you will be creating presentations to show the results of your
analyses. We will discuss the main types of slides you will be using.
16. 16
I will show you show you not only charts but other types of slides as
well
17. 17
Slides for Management
Consultants & Business Analysts
Examples from consulting projects
presentation
We will go through main examples Check the presentation in Additional
Resources for more than 300 examples of slides
20. 20
Consulting jobs requires fast reading and understanding of charts. In this
section, we will discuss what you should pay attention to, not to make mistakes.
21. 21
In this section we will talk about the following things
What is a good chart
The process of creating
charts
How to lie with charts
23. 23
People on purpose or by accident lie quite often with charts. In
this lecture, I will show you the most often used methods.
24. 24
Below some of the ways, in which they may try to influence you with
the charts
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that supports
the hypothesis
Message inconsistent with data
25. 25
Let’s start with the first one
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that supports
the hypothesis
Message inconsistent with data
26. 26
Below an example how you can adjust axes to make difference between
data to look smaller or bigger
Wrong graph Correct graph
100
101
102
99
100
101
102
103
Year 1 Year 2 Year 3
100 101 102
0
20
40
60
80
100
120
Year 1 Year 2 Year 3
Sales of product A in following years
In M USD
Sales of product A in following years
In M USD
27. 27
Below an example how you can adjust axes to make difference between
data to look smaller or bigger
Wrong graph Correct graph
100
101
102
Year 1 Year 2 Year 3
100 101 102
Year 1 Year 2 Year 3
Sales of product A in following years
In M USD
Sales of product A in following years
In M USD
28. 28
Let’s see how we can change the data reception through trendlines
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
29. 29
Below an example of the use of a trendline to data with no correlation
between them
Wrong graph Correct graph
0
2
4
6
8
10
0 2 4 6 8 10
Correlation between 2 data series
0
2
4
6
8
10
0 2 4 6 8 10
Correlation between 2 data series
30. 30
Let’s see how we can change of the units may be confusing to the
recipient
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
31. 31
Below an example of how the use of incorrect units may affect the
readability of the data in the graph
Wrong graph Correct graph
200 000
300 000
400 000
Year 1 Year 2 Year 3
Potential revenues in following years
In thousands of USD
200
300
400
Year 1 Year 2 Year 3
Potential revenues in following years
In M USD
32. 32
Let’s see how we can choice of colors may affect graph interpretation
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
33. 33
Below an example of wrong graph when the incorrect colors of the
graph may be confusing for data interpreting
Qualify Leads Create Demand
Negotiate the
contract
Sign the contract Up-sell
Retail
Industry
30%
30% 30% 40% 50%
Health
Industry
80%
60% 40% 20% 50%
Financial
Industry
10%
70% 40% 25% 30%
Technology 30%
20% 80% 80% 70%
Sales funnel by cohorts using color coding
In %
0% - 50%
50% - 100%
34. 34
Below an example of correct graph when the colors of the graph
support data interpreting
0% - 30%
35% - 40%
45% - 50%
55% - 70%
More than 80%
Qualify Leads Create Demand
Negotiate the
contract
Sign the contract Up-sell
Retail
Industry
30%
30% 30% 40% 50%
Health
Industry
80%
60% 40% 20% 50%
Financial
Industry
10%
70% 40% 25% 30%
Technology 30%
20% 80% 80% 70%
Sales funnel by cohorts using color coding
In %
35. 35
Let’s see how we can manipulate data selecting the period that support
our hypothesis
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
36. 36
Below an example of how data manipulation can support our
hypothesis
Revenues by years
In M USD
100
150
90
80
200
300
Year 1 Year 2 Year 3 Year 4 Year 5 Year 6
Revenues by years
In M USD
Wrong graph Correct graph
100
150
90
80
200
300
Year 1 Year 2 Year 3 Year 4 Year 5 Year 6
Message: The revenues have increased in recent years
37. 37
Let’s see how message that is inconsistent with data may be confusing
for data interpreting
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
38. 38
Below an example of message that is inconsistent with data
320
100
80
300
290 295
Month 1 Month 2 Month 3 Month 4 Month 5 Month 6
Sales by months
In thousands of EUR
Message: A slight decrease in sales in months 2 and 3 was caused by some problems with the
availability of products at the manufacturer
39. 39
Below an example of message that is consistent with data
320
100
80
300
290 295
Month 1 Month 2 Month 3 Month 4 Month 5 Month 6
Sales by months
In thousands of EUR
Message: A large drop in sales in month 2 and 3 was caused by big problems with the
availability of products at the manufacturer
40. 40
Below some of the ways, in which they may try to influence you with
the charts
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that supports
the hypothesis
Message inconsistent with data
41. 41
Check the video on YouTube for more details
Click here to go to the video
43. 43
Now let’s see when can we say that the chart is a good one
Consistent with message
Clear easy to read
The right type
With properly defined color
coding
Adjusted to the audience
Has an Excel to support it
With proper units Don’t manipulate the audience
45. 45
Create a structure of
the presentation
Write down the
messages you want to
convey
Sketch the slides
Create a template in
Power Point
For every slide create
the underlying
analysis or gather
needed info
Check for errors,
mistakes and
omissions
Write the beginning
and the end of the
presentation
Create Executive
Summary
Check the flow of the
whole presentation
and modify if needed
slides or the structure
Fill in the slides with
data and charts
Just as a reminder the creation of presentation consists of 10 phases of
46. 46
Create a structure of
the presentation
Write down the
messages you want to
convey
Sketch the slides
Create a template in
Power Point
For every slide create
the underlying
analysis or gather
needed info
Check for errors,
mistakes and
omissions
Write the beginning
and the end of the
presentation
Create Executive
Summary
Check the flow of the
whole presentation
and modify if needed
slides or the structure
Fill in the slides with
data and charts
The choice of slides is done in the Sketch phase. You may modify the
charts later on
47. 47
If we were to take a look only at the process of creating a chart we
would have the following sequence
Write down the
messages you want
to convey
Decide what type of
data you want to
show
Select the type of
chart that suits your
needs
Input data into the
chart
Modify or change
the type of the chart
48. 48
For more details and content check my online course where you can find case
studies showing analyses along with detailed calculations in Excel
Data Visualization for Management
Consultants & Analysts
$190
$19
Click here to check my course
51. 51
Before you decide which chart to choose, it's important to understand
why you need one and what story you want to tell your audience.
52. 52
There are 7 main reasons for which we can create a graphical
representation of data
What I want to show
How something
has change over
time
Compare across
2-dimensions
different options
Compare across
3-dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
53. 53
There are 7 main reasons for which we can create a graphical
representation of data
What I want to show
How something
has change over
time
Compare across
2-dimensions
different options
Compare across
3-dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
Clustered column
chart
Line chart
Stacked area
chart
Scatter Chart /
Bubble chart
Heat map
100 % stacked
column
2 Clustered
column charts
with 1 column
1 Clustered
column charts
with 2 columns
2 Clustered bar
charts with 1 Bar
1 Clustered bar
chart with 2 Bars
Combo chart with
– column and line
3 Clustered
column charts
with 1 column
1 Clustered
column chart
with 3 columns
Bubble chart
3 Clustered bar
charts with 1 Bar
1 Clustered bar
chart with 3 Bars
Snake graph (Line
graph with
markers)
Radar chart
100 % Stacked
column chart
100 % Stacked
bar chart
Waterfall chart
Pareto chart
Infographic chart
Other
Funnel chart
Clustered column
chart
Clustered Bar
Waterfall chart
Heat map
Map with color
coding
Map + Clustered
column chart
Regular charts
Map + Clustered
bar chart
54. 54
There are 7 main reasons for which we can create a graphical
representation of data
What I want to show
How something
has change over
time
Compare across
2-dimensions
different options
Compare across
3-dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
56. 56
Let's see how we can present data that changes over time
What I want to show
How something has
change over time
Compare across 2-
dimensions
different options
Compare across 3-
dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
Clustered column
chart
Line chart
Stacked area chart
Scatter Chart /
Bubble chart
Heat map
100 % stacked
column
57. 57
Check the video on YouTube for more details
Click here to go to the video
59. 59
Stacked column with absolute values
100 150 200 250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
60. 60
100 % stacked column chart with absolute values
100
150 200 250
400
400
200
300 450
500
80
100
200 250 300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
61. 61
100 % stacked column chart with percentages
17%
33% 29% 26%
33%
69%
44%
43% 47%
42%
14%
22%
29% 26% 25%
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Share of business units in Total Revenues of a chain of clinics by years
In percentage
63. 63
Bubble chart
Revenues of a chain of clinics by years and business units
In M of EUR
100
400
80
150
200
100
200
300
200
250
450
250
400
500
300
0 1 2 3 4 5 6
Dentists
GP Doctors
Others
Year
64. 64
Scatter chart – same color with labels
Revenues of a chain of clinics by years and business units
In M of EUR
Dentists; 100
GP Doctors; 400
Others; 80
Dentists; 150
GP Doctors; 200
Others; 100
Dentists; 200
GP Doctors; 300
Others; 200
Dentists; 250
GP Doctors; 450
Others; 250
Dentists; 400
GP Doctors; 500
Others; 300
0 1 2 3 4 5 6
Year
65. 65
Scatter chart – different colors with labels
Revenues of a chain of clinics by years and business units
In M of EUR
Dentists; 100
GP Doctors; 400
Others; 80
Dentists; 150
GP Doctors; 200
Others; 100
Dentists; 200
GP Doctors; 300
Others; 200
Dentists; 250
GP Doctors; 450
Others; 250
Destists; 400
GP Doctors; 500
Others; 300
0 1 2 3 4 5 6
Year
Dentists
GP Doctors
Others
66. 66
Scatter chart – different colors no labels
Revenues of a chain of clinics by years and business units
In M of EUR
100
400
80
150
200
100
200
300
200
250
450
250
400
500
300
0 1 2 3 4 5 6
Year
Dentists
GP Doctors
Others
67. 67
Heat map
Revenues of a chain of clinics by years and business units
In M of EUR
Dentists
GP Doctors
Others
Year 1 Year 2 Year 3 Year 4 Year 5
< 100
100 – 199
200 – 299
300 – 399
400 – 499
400 – 499
68. 68
When it comes to me, in most cases I would use the clustered column
chart or the stacked column chart
100 150 200 250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
100
150
200
250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Stacked column in absolute values Clustered column
70. 70
Let's see how we can present data with 2 dimensions
What I want to show
How something has
change over time
Compare across 2-
dimensions different
options
Compare across 3-
dimensions different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
2 Clustered column
charts with 1 column
1 Clustered column
charts with 2
columns
2 Clustered bar
charts with 1 Bar
1 Clustered bar
chart with 2 Bars
Combo chart with –
column and line
Scatter chart
71. 71
211
117
200 200
50
Company 1 Company 2 Company 3 Company 4 Company 5
Cost of the project
In thousands of USD
36 33
52 52
16
Company 1 Company 2 Company 3 Company 4 Company 5
Time needed for full implementation
In weeks
2 Clustered column charts with 1 column
72. 72
211
117
200 200
50
36 33 52 52
16
Company 1 Company 2 Company 3 Company 4 Company 5
Cost of the project vs Time needed for full implementation
In thousands of USD & In weeks
1 Clustered column charts with 2 dimensions
Cost of project (in thousands of USD)
Time needed (in weeks)
75. 75
50
200
200
117
211
Company 5
Company 4
Company 3
Company 2
Company 1
Cost of the project
In thousands of USD
16
52
52
33
36
Company 5
Company 4
Company 3
Company 2
Company 1
Time needed for full implementation
In weeks
2 Clustered bar charts with 1 Bar
76. 76
1 Clustered bar with 2 Bars
50
200
200
117
211
16
52
52
33
36
Company 5
Company 4
Company 3
Company 2
Company 1
Cost of the project & Time needed for full implementation
In thousands of USD & In weeks
Cost of project (in thousands of USD)
Time needed (in weeks)
77. 77
Scatter Chart
Cost of the project
In thousands of USD
Company 1
Company 2
Company 3
Company 4
Company 5
0
50
100
150
200
250
0 10 20 30 40 50 60
Time needed for full
implementation
(In weeks)
78. 78
When it comes to me, in most cases I would use the 2 Clustered column
charts with 1 column or scatter chart
2 Clustered column charts with 1 column Scatter chart
80. 80
Let's see how we can present data with 3 dimensions
What I want to show
How something has
change over time
Compare across 2-
dimension different
options
Compare across 3-
dimension different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
3 Clustered column
charts with 1
column
1 Clustered column
chart with 3
columns
Bubble chart
3 Clustered bar
charts with 1 Bar
1 Clustered bar
chart with 3 Bars
85. 85
When it comes to me, in most cases I would use the 2 bar charts or 3
Clustered bar charts with 1 bar
Bubble Charts 3 Clustered bar charts with 1 bar
87. 87
Let's see how we can present data that change their composition over time
What I want to show
How something has
change over time
Compare across 2-
dimensions different
options
Compare across 3-
dimensions different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
Snake graph (Line
graph with markers)
Radar chart
88. 88
Snake graph (Line graph with markers)
Price image for 2 firms
In USD
0
20
40
60
80
100
Regular price level Promotions /
Discounts
Price emotional
impact
Assortment Image Price Fairness Value for money
level
Consitency of price
strategy
Price Transparency
Firm A Firm B
Importance of specific criteria
% of people that thought that criteria is the most important
25%
19%
12% 10% 10% 10% 9%
5%
Regular price level Promotions /
Discounts
Price emotional
impact
Assortment Image Price Fairness Value for money level Consitency of price
strategy
Price Transparency
89. 89
Radar Chart
0
20
40
60
80
100
Regular price level
Promotions / Discounts
Price emotional impact
Assortment Image
Price Fairness
Value for money level
Consitency of price strategy
Price Transparency
Firm A Firm B
Price image for 2 firms
In USD
91. 91
Let's see how we can present data that change their composition over time
What I want to show
How something has
change over time
Compare across 2-
dimension different
options
Compare across 3-
dimension different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
100 % Stacked
column chart
100 % Stacked bar
chart
100 % Stacked area
chart
Waterfall chart
Pareto chart
Infographic chart
Doughnut chart
Tree Map
92. 92
100 % stacked column chart with absolute values
100
150 200 250
400
400
200
300 450
500
80
100
200 250 300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
93. 93
100 % stacked column chart with percentages
17%
33% 29% 26%
33%
69%
44%
43% 47%
42%
14%
22%
29% 26% 25%
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Share of business units in Total Revenues of a chain of clinics by years
In percentage
94. 94
Stacked column chart with absolute values
100 150 200 250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
95. 95
100 % stacked bar chart with absolute values
100
150
200
250
400
400
200
300
450
500
80
100
200
250
300
Year 1
Year 2
Year 3
Year 4
Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
96. 96
100 % stacked bar chart with percentages
17%
33%
29%
26%
33%
69%
44%
43%
47%
42%
14%
22%
29%
26%
25%
Year 1
Year 2
Year 3
Year 4
Year 5
Dentists GP Doctors Others
Share of business units in Total Revenues of a chain of clinics by years
In percentage
97. 97
100% Stacked area chart with absolute values
100
150 200 250
400
400
200
300 450
500
80
100
200 250 300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
98. 98
100% Stacked area chart with percentages
17%
33% 29% 26%
33%
69%
44%
43% 47%
42%
14%
22%
29% 26% 25%
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
100. 100
Infographic chart
Share of business units in Total Revenues of a chain of clinics in Year 1
In percentage
17%
Dentists
69 %
GP Doctors
14 %
Others
101. 101
Infographic chart
Share of business units in Total Revenues of a chain of clinics in Year 1
In percentage
17%
Dentists
69 %
GP Doctors
14 %
Others
102. 102
Infographic chart
Share of business units in Total Revenues of a chain of clinics in Year 1
In percentage
Dentists – 17%
GP Doctors – 69%
Others – 14%
104. 104
Doughnut chart
Share of Product sales in Total Revenues of a retail company in Year 1 vs Year 2
In percentage
10%
12%
24%
6%
18%
19%
11%
12%
14%
28%
7%
19%
15%
5%
Product 1
Product 2
Product 3
Product 4
Product 5
Product 6
Product 7
Year 1
Year 2
105. 105
Doughnut chart
Sales and Margin of the following products
In percentage
10%
12%
24%
6%
18%
19%
11%
5%
11%
43%
10%
12%
12%
7%
Product 1
Product 2
Product 3
Product 4
Product 5
Product 6
Product 7
Margin
Sales
106. 106
When it comes to me, in most cases I would use the 100 % stacked
column chart or waterfall chart
100 % stacked column chart Waterfall chart
108. 108
Let's see how we can present funnel analysis
What I want to show
How something has
change over time
Compare across 2-
dimensions
different options
Compare across 3-
dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local differences
Funnel chart
Clustered column
chart
Clustered Bar
Waterfall chart
Heat map
110. 110
Funnel chart using shapes
Click to the add
Visit app store website
Run the app
Download and install app
Fill in registration data
Complete registration
100%
85%
62%
54%
38%
24%
% of initial
Group
Conversion
rate
100%
85%
73%
87%
70%
64%
Number of customers who, after clicking on an advertisement of the app, became its users
In %
112. 112
Clustered bart chart
Funnel Analysis of customers who decided to book a hotel online
In millions
3
7
14
18
20
Purchase
Register
Add to cart
Product viewed
Start session
113. 113
Waterfall chart
Funnel Analysis of customers who decided to book a hotel online
In millions
20
2
18
4
14
7
7
3
3
Start session End session Product
viewed
Product
abandoned
Add to cart Product not
added
Registered Not registered Purchase
114. 114
Qualify Leads Create Demand Negotiate the contract Sign the contract Up-sell
Heat map
Retail Industry 30%
30% 30% 40% 50%
Health
Industry
80%
60% 40% 20% 50%
Financial
Industry
10%
70% 40% 25% 30%
Technology 30%
20% 80% 80% 70%
Sales funnel by cohorts using color coding
In %
115. 115
When it comes to me, in most cases I would use the 100 % stacked
column chart or waterfall chart
Clustered bar chart Waterfall charts Heat map charts
117. 117
Let's see how we can present local differences
What I want to show
How something has
change over time
Compare across 2-
dimension different
options
Compare across 3-
dimension different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
Map with color
coding
Map + Clustered
column chart
Regular charts
Map + Clustered
bar chart
118. 118
Map with color coding – PowerPoint map
Shares of sales of cosmetics products in following countries
In %
100%
Shares of sales :
74%
31%
26%
85%
14%
119. 119
100%
Shares of sales :
Map with color coding – map made out of shapes
74%
31%
26%
Shares of sales of cosmetics products in following countries
In %
85%
14%
120. 120
PowerPoint Map + Clustered column chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland United
Kingdom
Germany France Spain Italy
121. 121
Map made out of shapes + Clustered column chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland United
Kingdom
Germany France Spain Italy
122. 122
PowerPoint Map + Clustered bar chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland
United Kingdom
Germany
France
Spain
Italy
123. 123
Map made out of shapes + Clustered bart chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland
United Kingdom
Germany
France
Spain
Italy
124. 124
Clustered bar chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland
United Kingdom
Germany
France
Spain
Italy
125. 125
For more details and content check my online course where you can find case
studies showing analyses along with detailed calculations in Excel
Data Visualization for Management
Consultants & Analysts
$190
$19
Click here to check my course
128. 128
Let’s see how you can create fast and efficiently charts in Excel. In
this section we will concentrate on some technical tips.
129. 129
In this section we will talk about the following things
How to format the chart
How to have a one chart
with 2 axes
Basics of creating a chart in
Excel
How to reverse the order
of data in the chart
How to reuse formatting
from previous charts
Bar chart with different
colors
How to add total for
stacked column charts
How to highlight specific
periods on the chart
How to create more
complicated charts
130. 130
Check the video on YouTube showing how to create a waterfall chart
Click here to go to the video
132. 132
Sometimes you will want to create more complicated charts that you
cannot do directly in Excel. I will show how to find a way around
133. 133
In the next lectures we will have a look at 2 case studies
Waterfall Charts showing
potential stores
Scatter Charts with labels
showing new products
134. 134
Check the video on YouTube showing how to create a waterfall chart
Click here to go to the video
135. 135
Check the video on YouTube showing how to create scatter plot with labels
Click here to go to the video
138. 138
For data visualization you don’t have to use charts. In some cases conditional
formatting does a great job. In this section we will discuss it in practices
139. 139
In this section we will talk about the following things
Charts using conditional
formatting
Heat Maps using
conditional formatting
Basics of Conditional
Formatting
Sparklines
142. 142
Let’s see how you can create fast and efficiently charts in Power
Point. In this section we will concentrate on some technical tips.
143. 143
In this section we will talk about the following things
How to make the chart look
nice in Power Point
Library of formatted charts
Basics of creating a chart in
Power Point
Chart Animation
144. 144
Check the video on YouTube for more details
Click here to go to the video
147. 147
Pivot Charts are great tools that will help you with data visualization.
In this section we will have a look how to use them in practice.
148. 148
In this section we will talk about the following things
Combining slicers with
Pivot Charts
Building a Dashboard
Pivot Charts Example
Online store-checks – Case
study using Pivots
Look & Feel of Pivot Chart
Using Customer reviews –
Case study using Pivots
150. 150
In many cases you will have to do not only store checks in physical stores
but also in online stores. We will discuss this subject in this lecture.
151. 151
Before going deeper into this lecture I would recommend revising the
lecture on offline store-checks
Offline store-check
152. 152
In the online store checks you can compare different types of stores
Compare different
online stores
Compare offline to
online for the same
brand
Compare offline to
online for different
brands
For example H&M online to
Zara online
For example H&M online to
H&M offline
For example H&M online to
Zara offline
Understand difference in
product range and pricing
used in the online world
Understand difference in
product range and pricing
policy used by the same
brand in offline and online
worlds.
Do they have the same policy
or they use different sets of
rules for the online and
offline world
You want to compare 2
brands
For one of them you don’t
have the offline data i.e.
from another country. In this
case you can use the online
data as a proxy to make the
comparison.
This will require adjustments
so you can trulely ompare
the 2 brands
Compare different
offline stores
For example H&M offline to
Zara offline
Understand difference in
product range and pricing
used in the offline world
Example
Purpose
153. 153
Below the main methods you can use to do the online store-check
Create a script to
automate the
process
Use data scraping
tools
Do the store-check
manually
Buy data from the
3rd party
Use the API or ask
for data the
provider
155. 155
During online store-check you most likely will be gathering the following
information
Name, photos of the product &
assigned categories
Prices of specific products
Available quantity
# of reviews
Rules for organizing data on the
webpage
Rules for presenting data
Additional information on the
availability in offline stores
Discounts on the product
157. 157
Let’s see how you can use the online store-checks to analyze the market.
This time around we will do a store-check for cosmetics
158. 158
A few information about what you have to do
You will concentrate only on
cosmetics for the face
You have data on 200 SKUs
You have information on the
brand, price, group, size
Analyze the data from the online
store-check
160. 160
The information from customers is extremely important. Nowadays we have plenty of sites
that gather customers reviews. We will discuss how you can use them in market research
161. 161
Below a short summary of what you can learn from sites with review
What customers pay attention
to
Customer Segments
What current players are good
at
What current players don’t do
too well
You can estimate NPS (Net
Promoter Score)
You can check how popular
certain brands / solutions are
In some cases you can contact
the reviewer
You learn the language used by
the customers
165. 165
Imagine that you were hired by a firm to analyze the emailing software market and to tell
them whether there is a niche for them to create a new product. Use the customer reviews
166. 166
A few information about what you have and what are your goals
You decided to concentrate on the
Mailchimp customers
Your boss proposed to concentrate
only on the users that have 3 stars
You have gathered data from 900
users by data scraping
Propose on which aspect they
should concentrate
168. 168
One of the ways to understand the market and competitors is to try and compare products
especially from different firms. You can do that using comparison tools / sites
169. 169
Below a short summary of what you can learn from comparison sites
How popular specific product is
To what extent products differ in
terms of features / characteristics
What customer segments do they
target
Pros and Cons of each and every
solution
How widely specific products are
used
Pricing and sales strategy
Customer support offered
Links to other products / Product
Ecosystem
170. 170
Below some examples where you can find product comparison
Some Review Sites
Sites dedicated to
comparisons
Other
G2
Trust Radius
Software Advice
GetApp
Comparison done by
influencers
Product Rankings
Reddit
Quora
E-commerce /
Marketplaces
Amazon
Best Buy
173. 173
In some cases you will want to make your charts more dynamic so it can readjust to
changes in parameters or questions asked. I will show you how you can achieve it in Excel.
174. 174
In this section we will talk about the following things
Dynamic Charts using
VLOOKUP & MATCH
Dynamic Charts using
SUMIFS
Dynamic Charts using Pivot
Charts
How to add new data to
the chart automatically
177. 177
In 80% of the time you will be using simple charts similar to what we have shown
so far. Now we will have a look at some interesting charts that are less frequently.
178. 178
In this section we will talk about the following things
Maps Tree Maps
Pareto Chart
Doughnut Charts
Funnel Charts Box & Whisker Chart
179. 179
For more details and content check my online course where you can find case
studies showing analyses along with detailed calculations in Excel
Data Visualization for Management
Consultants & Analysts
$190
$19
Click here to check my course