Create a happy ending for data-driven decision-making

BREAK
Our
Thought
Leadership
Group
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#DAWSG

DATA STORYTELLING: CREATE A HAPPY ENDING FOR
DATA-DRIVEN DECISION-MAKING
Siva Ganeshanandan
Director APAC Product and Industry Strategy@ Adobe
#DAWSG
@SivaGatWork

© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
Adobe
3 3

Adobe
4 4

male
female
12-18
18-36
36-55
55+
<$12k
$12k-$25k
$25k-$50k
$50k-$100k
northeast
northwest
central
southwest
southeast
rural
urban
suburban
manufacturing
financial services
automotive
banking
art+architecture
government
education
#FFCC00
#f1f1f1
#eeccff
#2950392
#239857
#00e0c9
F = k ( q1 q2 / r2 )
( sin θ1 )/(sin θ2 ) = v1 /v2 = n2 /n1 = λ1 /λ2
Fb = Vρg = mg
v = λ f
V = V0(1 + βΔ T )
1/ Ceq = 1/ C1 + 1/ C2 + 1/ C3
01
02
03
04
05
08
09
10
001 002 003
004 005 006
007 008 009

male
female
12-18
18-36
36-55
55+
<$12k
$12k-$25k
$25k-$50k
$50k-$100k
northeast
northwest
central
southwest
southeast
rural
urban
suburban
manufacturing
financial services
automotive
banking
art+architecture
government
education
#FFCC00
#f1f1f1
#eeccff
#2950392
#239857
#00e0c9
F = k ( q1 q2 / r2 )
( sin θ1 )/(sin θ2 ) = v1 /v2 = n2 /n1 = λ1 /λ2
Fb = Vρg = mg
v = λ f
V = V0(1 + βΔ T )
1/ Ceq = 1/ C1 + 1/ C2 + 1/ C3
01
02
03
04
05
08
09
10
001 002 003
004 005 006
007 008 009
7
62,486 TOOL USAGE
44.098%
AGENT DEFLECTION
69.78% COMPLETION RATE
SELF SERVICE APP RICH CONTENT
AND EXPERIENCE
89% ROI
+28% VIDEO VIEWS

MA-02 Data storytelling: Create a happy ending for data-driven decision-making
Brent Dykes | Evangelist, Analytics
@analyticshero

#AdobeSummit @analyticshero

BUDGET

A REALLY BIG TEAM

Online Form Clicks
64.8%
Unique Visitors
Hours of the Day
Call Center
Coverage
Form CTR

© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
Agenda
What is Data Storytelling?1
Narrative: Tips & Pitfalls2
Visuals: Tips & Pitfalls3

What is
Data Storytelling?
Data
Presentations? Infographics?
Reports &
Dashboards?
Data
Visualisations?
It depends.

Narrative Visuals
3 Keys to Data
Storytelling
Data

Data
Narrative Visuals
3 Keys to Data
Storytelling

Narrative
Data
3 Keys to Data
Storytelling
Visuals

Narrative
Data
3 Keys to Data
Storytelling
Engage
Visuals

Data
Narrative Visuals
Engage
Change
3 Keys to Data
Storytelling

Five Essential Components of a Data Story
MAIN
POINT
ž A data story must
help the audience
to understand a
central insight or
idea
ž It should have an
intended endpoint
or destination that
drives discussion
and action

MAIN
POINT
EXPLANATORY
FOCUS
ž An analyst provides
relevant context
and useful
commentary on the
data points
ž These details can
accompany the data
as annotations (text)
or speaking points
(audio)
Descriptive Explanatory
Describe
To represent or give an
account of in words or pictures
Explain
To make plain or clear; render
understandable or intelligible
Who?
What?
When?
WHY?
HOW?

MAIN
POINT
EXPLANATORY
FOCUS
LINEAR
SEQUENCE
ž A data story is
arranged in a
linear structure
where supporting
points build upon
each other
ž The layout or
presentation flow
should provide a
clear path for the
audience to follow
Story
An account of a
causally-related
or connected
series of events

MAIN
POINT
EXPLANATORY
FOCUS
LINEAR
SEQUENCE
NARRATIVE
ELEMENTS
ž A data story
borrows various
narrative
techniques from
literature and film
ž Setting, characters,
plot, and conflict
help to engage
the audience
more deeply on
an emotional level

MAIN
POINT
EXPLANATORY
FOCUS
LINEAR
SEQUENCE
NARRATIVE
ELEMENTS
VISUALS
ž Charts, diagrams,
and other imagery
are used to
simplify and clarify
complex ideas
ž Data visualisations
complement the
narrative and
contribute to both
comprehension
and memorability

Data Storytelling Landscape
MAIN
POINT
EXPLANATORY
FOCUS
LINEAR
SEQUENCE
NARRATIVE
ELEMENTS VISUALS
Data Presentations Often Often Often OftenYes
Curated Reports &
Dashboards Often Often Often YesMaybe
Infographics Often Maybe Maybe YesMaybe
Data Visualisations Maybe Rarely No YesMaybe
Automated Reports No No No OftenNo
Automated Dashboards No No No YesNo

Confusing
the TOOL
with the
TASK
Confusing
the TOOL
with the
TASK
PITFALL

Analytics Needs All of the Dominos to Fall

Agenda
Data
Narrative Visuals
Engage
Change

Personalisation is
not just what you
recommend
Personalisation is
not just what you
recommend
PITFALL

Six Critical Audience Questions
Audience
1. Key business goals & priorities?
2. Specific needs & questions?
3. How familiar with topic?
4. How data-savvy?
5. Seniority level?
6. Delivery method?
Considerations
Ensure data stories
are relevant
Anticipate what they
want to learn
Less familiar—More
context & conceptual
Less savvy—Less
detail and jargon
More senior—Lead
with summary
Indirect method—
More annotations(Direct/Indirect)

Data Storytelling Arc
Audience’s insights
into the business are
expanded
Beginning Middle End
Solution
& Next Steps
Share
recommendations
and discuss next steps
Rising Insights
Share findings that
reveal deeper insights
into the problem or
opportunity
Aha Moment
Present major finding
or key insight
Set-up
Background
on current
situation,
character(s),
and the hook
Structuring Your Data within a Story
+
MAIN POINT
VISUALS
NARRATIVE
ELEMENTS
EXPLANATORY
FOCUS
LINEAR
SEQUENCE

How to Prioritise What Data to Show in Your Story
Set-up
Background on
current situation,
character(s), and
the hook
Rising Insights
Share findings that
into the problem or
opportunity
Aha Moment
or key insight
Solution
& Next Steps
Share recommendations
ž What is the main
takeaway of your
analysis?
ž Can the impact be
monetised?
ž What conclusion do
you want your
audience to draw
from your analysis?
ž What supplemental
data will help with
decision making?
ž Are there different
solution options
that need to be
compared?
ž What will give your
audience adequate
background and
context?
ž What will grab your
audience’s
attention?
ž What other insights
contribute to the main
story?
ž What findings were
unexpected or surprising?
ž What questions can be
preemptively addressed
with data?
ž What can be removed
without hurtingthe story?
132 4
1
2
3 4

Data Prioritisation Example: Clothing Retailer
Set-up
Background on
current situation,
character(s), and
the hook
Rising Insights
Share findings that
into the problem or
opportunity
Aha Moment
or key insight
Solution
& Next Steps
Share recommendations
ž Men’s Timberland
Boots are a hot seller
this month (172%
increasein sales)
ž Promotional efforts
could drive an
incremental £650K
ž Email promotions
and internal search
results should be
primaryfocus
ž Homepage hero
ads and cross-
selling won’t be as
effective
ž Revenue jumped
17% year-over-year
for the same time
period
ž Revenue from Men's
category is up 56% Y-O-Y
ž Revenue from Men's
Footwear is driving87%
of this increase
132 4
1
2
3 4

No Heroes
in Your
Data Story
No Heroes
in Your
Data Story
PITFALL
So am I
chopped
liver?

How to Insert Characters in Your Data Story
Identify where
your analysis
intersects with
people
Determine which
customer traits
are important to
your message
Search for
appropriate
character
imagery
Create a
persona for
your hero
Build the
customer
journey with
visual elements
Qualitative dataStock photos Screenshots
54321

Agenda
Visuals: Tips & Pitfalls3
Data
Narrative Visuals
Engage
Change

WARNING!WARNING!
Overload
your
audience
with data
Overload
your
audience
with data
PITFALL

Sensory Memory
Working Memory
Long-Term Memory
WARNING!WARNING!

Intrinsic Load
Inherent difficulty of
the topic to learn
Extraneous Load
Non-relevant
elements shared
Germane Load
Work spent on
building schemas
Cognitive
Load Theory
Cognitive
Load Theory
Sensory Memory
Working Memory
Long-Term Memory

1 2
3 4
INTRINSIC
How to fold a paper plane
How to pilot an airliner
EXTRANEOUS GERMANE
MAXIMISEMANAGE MINIMISE

Six Tips for Better Data Storytelling
Use content staging to reveal insights1
Choose the right visualisation2
Ditch the defaults3
Remove competing noise to create a stronger signal4
Draw the audience into your analysis5
Make your data relatable6
MANAGE
MINIMISE
MAXIMISE
INTRINSIC
EXTRANEOUS
GERMANE

1. Use Content Staging to Reveal Insights
Sales Lead Rate
Form Complete Rate
0
1
2
3
4
5
6
7
8
9%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Form Start Rate
Feb 19-21: A new spring
promotion led to a high
level of unqualified leads. It
was stopped after 2 days.

Steps for Content Staging Your Charts
1. Select entire chart
2. Create a copy
3. Select “Paste Special” as
Picture (Windows Metafile)
4. Ungroup chart
5. Click “Yes” to convert to
Microsoft Drawing object
6. Add animations to parts of
the chart
MANAGE

Steps for Content Staging Your Charts
1. Select entire chart
2. Create a copy
3. Select “Paste Special” as
Picture (Windows Metafile)
4. Ungroup chart
5. Click “Yes” to convert to
Microsoft Drawing object
6. Add animations to parts of
the chart
Donut
& Pie
Line
Bar &
Column
Scatterplot
Bitmap
MANAGE

2. Choose the Right Visualisation
More accurate
comparisons
More generic
comparisons
2D position along
common but
unaligned scales
Length Angle Volume Shading
Direction Area Curvature Color Hue
2D position along
common, aligned
scale
Graphical Perception: Theory, Experimentation, and
Application to the Development of Graphical Methods
(Cleveland & McGill, 1984) via The Functional Art
(Alberto Cairo, 2013)
MINIMISE

2. Choose the Right Visualisation
Facebook
Twitter
YouTube
LinkedIn
Google+
5%
29%
32%
25%
9% Facebook
Twitter
YouTube
LinkedIn
Google+ 5%
32%
29%
25%
9%
“OK” “BETTER”
http://bit.ly/1kNp8GxStephen Few article on pie charts
MINIMISE

3. Ditch the Defaults
MINIMISE

MINIMISE
Remove unnecessary legend
ž Click on legend and delete
Details

MINIMISE
Fix horizontal date axis
ž Right-click on horizontal axis >
Format Axis
ž Click on Number tab
ž In Format Code, type
“mmmmm” and click Add
Details

MINIMISE
Fix the vertical revenue axis
ž Right-click on vertical axis >
Format Axis
“[=600000]$#,##0;#,##0” and click
Add
ž Note: Change 600000 to match
your max value
Details

MINIMISE
Remove unnecessary zeroes
Format Axis
ž On Axis Options tab, change
Display Units setting from “None”
to “Thousands”
“[=600]$#,##0;#,##0” and click
Add
ž Note: Change 600 to match your
max value
Details

MINIMISE
Remove unnecessary spacing
ž Right-click on horizontal axis >
Format Axis
Position Axis setting from
“Between tick marks” to “On tick
marks”
Details

MINIMISE
Remove vertical axis and tick marks
Details
Format Axis
Major Tick Mark Type setting
from “Outside” to “None”
ž On Line Color tab, change setting
from “Automatic” to “No line”

MINIMISE
Lighten gridlines
ž Right click on gridlines > Format
Gridlines
ž In Line Color tab, change setting
from “Automatic” to “Solid line”
ž Select light gray color
Details

MINIMISE
Change to corporate fonts
ž Select different areas and
change font from Calibri to
corporate font(s)
ž Lighten font color of
“Thousands” and remove bold
ž Center “Thousands” on
vertical axis
Details

MINIMISE
Add a more meaningful title
ž Click on title and add new title
Details

MINIMISE
Change line format and color
ž Right-click on line > Format
Data Series
ž On Line Color tab, change
“Automatic” to “Solid line” and
select desired color
ž On Marker Options tab,
change Marker Type from
“None” to “Built-in”
ž Select Circle type and size 6
ž On Marker Fill tab, change
“Automatic” to “Solid Fill”
(white)
ž On Marker Line Color tab,
change “Automatic” to “Solid
line” and select same color as
line
Details

MINIMISE
Add direct label for key data point
ž Right-click on line > Format
Data Series
ž On Marker Fill tab, change
color from white to line color
ž On Marker Line Color tab,
change color from line color
to white
ž Select specific point (click
twice) and right-click > Format
Data Point
ž Change marker fill to black
ž Increase size from 6 to 7
ž Add text box to label point
ž Change title (if necessary)
Details

MINIMISE
Voila!
ž Select chart
ž Design tab in Excel > Save as
Template
ž Give it a descriptive name for
future reference
Details

MINIMISE
Before After

4. Remove Competing Noise to Create a Stronger Signal
MINIMISE
Signal
Noise

5.9
3.1
4.8
2.6
70%
76%
0%
20%
40%
60%
80%
0
2
4
6
Average Time
on Site
(minutes)
Average PVs
per Visit
Site Bounce
Rate
2013
2014
2014
2013
2013
2014
UK SITE’S ENGAGEMENT
PERFORMANCE MARKEDLY
DOWN VS. 2013
4.8
2.6
4.9
3.4
4.1
2.9
76%
45%
60%
0%
20%
40%
60%
80%
0
1
2
3
4
5
Average Time on Site
(minutes)
Average PVs per Visit Site Bounce Rate
UK
UK
UK
DE
DE
DE
NE
NE
NE
OTHER REGIONAL SITES HAVE
OUTPERFORMED UK SITE
Significant room
for improvement
“UGGGH”
In general, one data
visualisation per slide
4. Remove Competing Noise to Create a Stronger Signal

5.9
3.1
4.8
2.6
70%
76%
0%
20%
40%
60%
80%
0
2
4
6
Average Time on
Site (minutes)
Average PVs per
Visit
Site Bounce Rate
2013
2014
2014
2013
2013
2014
UK SITE’S ENGAGEMENT PERFORMANCE
MARKEDLY DOWN VS. 2013

4.8
2.6
4.9
3.4
4.1
2.9
76%
45%
60%
0%
20%
40%
60%
80%
0
1
2
3
4
5
Average Time on Site
(minutes)
Average PVs per Visit Site Bounce Rate
UK
UK
UK
DE
DE
DE
NE
NE
NE
OTHER REGIONAL SITES HAVE OUTPERFORMED UK SITE
Significant room
for improvement

5. Draw the Audience into Your Analysis
MAXIMISE
Challenger
ž Infographic-style page
ž Two steps to conversion: click CTA,
fill out modal form, and submit
Control
ž Existing landing experience
ž One step to conversion
Which version won?
WINNER
Form
Conversion
168%

14.3%
12.6%
9.7%
9.1%
8.6%
7.8%
6.8%
6.4%
4.9%
4.5%
Site Section Page Views
National 1,652,256
World 1,456,370
Sports 1,125,366
Politics 1,057,848
Business 990,677
Opinion 902,933
Technology 789,050
% Total
January 2014
How does this
compare to
January 2015?
Page Views % Change
1,999,230 21.0%
1,558,316 7.0%
1,485,483 32.0%
941,143 -11.0%
1,121,319 13.2%
575,747 -36.2%
764,838 -3.1%
825,636 10.8%
987,654 73.4%
890,838 71.3%
January 2015
MAXIMISE

MAXIMISE
National
Site Sections by
% of Total PVs
World
Sports
Business
Travel
Politics
Health
Entertainment
Technology
Opinion
14.3%
14.7%
12.6%
11.4%
9.7%
10.9%
9.1%
6.9%
8.6% 8.2%
7.8%
4.2%
6.8%
5.6%
6.4% 6.1%
4.9%
7.3%
4.5%
6.5%
January 2014 January 2015

MAXIMISE
National
Site Sections by
% of Total PVs
World
Sports
Business
Travel
Politics
Health
Entertainment
Technology
Opinion
14.3%
14.7%
12.6%
11.4%
9.7%
10.9%
9.1%
6.9%
8.6% 8.2%
7.8%
4.2%
6.8%
5.6%
6.4% 6.1%
4.9%
7.3%
4.5%
6.5%
January 2014 January 2015
73%h
71%h
Lifestyle audience is
growing organically
in popularity

6. Make Your Data Relatable
MAXIMISE

Examples for Making Your Data Relatable
MAXIMISE
Search keywords Conv. Rate Monthly Cost
acme 0% 1,750
corporation 0% 1,525
company 0% 1,400
organization 0% 1,250
industry 0% 900
association 0% 745
leader 0% 650
marketing 0% 615
firm 0% 590
brand 0% 575
£10,000
x12 = £120,000
Annually
£60K £60K

Examples for Making Your Data Relatable
MAXIMISE
Orders
Product Views
0
100
200
300
400
500
600
0 100 200 300 400 500 600 700 800 900 1000
BIO FIT Mens
SS Jersey
BIO FIT Mens
Bib Shorts
Century
Ladies SS
Jersey

Transitioning from Analysing to Storytelling
Data Explorer

Transitioning from Analysing to Storytelling
Data Explorer Data
Storyteller

© 2014 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. 78
Analytics Maturity-Predictive Marketing Workflow
What do you
want to improve
Anomaly
Detection
TRIGGER
QUESTION
TRIGGER
QUESTION
DATA
EXPLORATION
DATA
EXPLORATION
AUDIENCE
DISCOVERY
AUDIENCE
DISCOVERY
CUSTOMER
SCORING
CUSTOMER
SCORING EXECUTIONEXECUTION
Description
Feature
Uncover
relevant,
differentiated,
valuable
audiences
Clustering
Predict who is
most likely to
respond
Propensity
Scoring
Take action on
your audiences
Execution
Discover hidden
relationships
Correlations

Data Storyteller Resources
Books Links
Videos
Telling Compelling Stories with Numbers: Data Visualization
and Communication (Stephen Few)
http://1.usa.gov/1oWgmVL
The Joy of Statistics (BBC – Hans Rosling)
http://www.youtube.com/watch?v=CiCQepmcuj8
Persuasion and the Power of Story (Jennifer Aaker)
http://www.youtube.com/watch?v=AL-PAzrpqUQ
ž Storytelling with Data (http://bit.ly/1xaDVx0)
ž Data Stories: How to combine the power of storytelling with
effective data visualization (http://bit.ly/1C1RNzx)
ž Storytelling in the Boardroom 6-part series on
Office.microsoft.com (http://bit.ly/1pttMXM)
ž Web Analytics Kick Start Guide: http://bit.ly/KickStartGuide
(free download)
ž Powerpointninja.com
ž Visual.ly
ž Flowingdata.com

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PROFILES &
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MANAGER
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THE END!
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www.decision-science.com
Coming Soon!
#DAWSG

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