How to move from the data we collect to the stories we use to communicate the research findings.

1. Marketing Research & Social Communication
Lesson 6
From Data Tables to Storytelling
Ray Poynter
1Ray Poynter, Marketing Research & Social Communication, 2015

2. Agenda
1. Homework
2. Storytelling and market research
3. Looking at data
4. From data to stories
5. Quiz and assignment for next week
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3. Homework
What is the main story that is being told by
Hans Rosling?
Ray Poynter, Marketing Research & Social Communication, 2015 3

4. Qualitative & Quantitative
Qualitative
– QuaLitative
– Language
Quantitative
– QuaNTitative
– Numbers & Tables
Ray Poynter, Marketing Research & Social Communication, 2015 4

5. Data Tables and Storytelling
• Most quantitative data comes from
surveys
• We typically look at that data in tables or
via interactive tools
• Data is what the market researcher uses
• Most clients want answers not data
– Many want advice not just answers
• Storytelling is the current preferred method
of delivering answers and advice
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6. What is Storytelling in MR?
It is not the same as fiction
In market research, storytelling means
1. Narrative flow
2. Interesting
3. Attention grabbing
4. Attention keeping
5. Memorable
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7. Narrative Flow
Stories with a beginning, middle and end
Hans Rosling
1. The Western understanding of the world is
flawed – no better than chimpanzees
2. The misconceptions are based on an out of
date picture
3. If we use data we can see that the world has
changed
4. So, solving the world’s problems requires
knowledge about the world, which means
collecting and using the right data
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8. From Data to Stories
Design the survey to answer questions and
provide material for your story
Read the open-ended responses and top-
lines to monitor the story unfolding
1. Check your data
2. Find the total picture
3. Find the relevant detail
4. Create the story
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9. Is my data ‘right’?
Checking starts during fieldwork
– Incompletes
– Distribution of demographics
– Open-ended comments (aka as verbatims)
QA – Quality Assurance
– Remove test interviews
– Review partial interviews
– Missing data
– Open-ended comments
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10. From Data to Stories
1. Check your data
2. Find the total picture
3. Find the relevant detail
4. Create the story
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11. Two Choices for Examining
Survey Data
1. Interactive systems
The modern way
2. CrossTabs
The traditional way
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12. Interactive Data Tools
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13. Banner, e.g. Male/Female, User/Nonuser, <30, 30-50, >50
Question
Responses
Strongly Agree
Agree
Neither A/D
Disagree
Disagree Strongly
Banner, e.g. Male/Female, User/Nonuser, <30, 30-50, >50
Question
Responses
Strongly Agree
Agree
Neither A/D
Disagree
Disagree Strongly
Banner, e.g. Male/Female, User/Nonuser, <30, 30-50, >50
Question
Responses
Strongly Agree
Agree
Neither A/D
Disagree
Disagree Strongly
Banner, e.g. Male/Female, User/Nonuser, <30, 30-50, >50
Question
Responses
Strongly Agree
Agree
Neither A/D
Disagree
Disagree Strongly
What are crosstabs?
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In almost all countries, tables are read as columns, from top to bottom
Banner, e.g. Male/Female, User/Nonuser, <30, 30-50, >50
Question
Responses
Strongly Agree
Agree
Neither A/D
Disagree
Disagree Strongly

14. Where does the best MR come from?
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Column % Which of the following best describes you? Countries Merged
Total Research or
Consultancy
Supplier
Supplier to the
research
industry
Research
Buyer/User
Academic +
Other
English
Speaking
Non-English
Speaking
UK 63% 61% 60% 92% 40% 66% 60%
USA 51% 52% 50% 46% 60% 52% 50%
Germany 18% 13% 30% 15% 60% 16% 21%
Australia 15% 14% 15% 15% 20% 16% 12%
Canada 11% 8% 20% 0% 40% 9% 14%
France 7% 7% 10% 8% 0% 7% 7%
Japan 5% 3% 15% 0% 0% 3% 7%
Brazil 3% 3% 5% 0% 0% 3% 2%
China 2% 1% 5% 0% 0% 3% 0%
Italy 2% 1% 5% 0% 0% 0% 5%
Other 8% 10% 10% 0% 0% 9% 7%
None of these 11% 15% 5% 0% 0% 9% 14%
Column n 109 71 20 13 5 67 42
In almost all countries, tables are read as columns, from top to bottom

15. In Japan
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該
当
数
し
て
い
る
し
て
い
な
い
全
体
1200 51% 49%
性
別
男性 530 46% 54%
女性 670 55% 45%
年
齢
１０代 234 4% 96%
２０代 277 32% 68%
３０代 240 62% 38%
４０代 226 75% 25%
５０代 223 88% 12%
婚
姻
状
況
している 613 100% 0%
していない 587 0% 10%

16. Where do I start with
quantitative analysis?
1. The brief
2. The proposal
3. What you already know
4. Initial hypotheses
5. Find the total picture
6. Find the important variations
from the total picture
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17. Where does the best MR come from?
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Column % Which of the following best describes you? Countries Merged
Total Research or
Consultancy
Supplier
Supplier to the
research
industry
Research
Buyer/User
Academic +
Other
English
Speaking
Non-English
Speaking
UK 63% 61% 60% 92% 40% 66% 60%
USA 51% 52% 50% 46% 60% 52% 50%
Germany 18% 13% 30% 15% 60% 16% 21%
Australia 15% 14% 15% 15% 20% 16% 12%
Canada 11% 8% 20% 0% 40% 9% 14%
France 7% 7% 10% 8% 0% 7% 7%
Japan 5% 3% 15% 0% 0% 3% 7%
Brazil 3% 3% 5% 0% 0% 3% 2%
China 2% 1% 5% 0% 0% 3% 0%
Italy 2% 1% 5% 0% 0% 0% 5%
Other 8% 10% 10% 0% 0% 9% 7%
None of these 11% 15% 5% 0% 0% 9% 14%
Column n 109 71 20 13 5 67 42
The wrong approach to starting analysis

18. Where does the best MR come from?
Ray Poynter, Marketing Research & Social Communication, 2015 18
Column % Which of the following best describes you? Countries Merged
Total Research or
Consultancy
Supplier
Supplier to the
research
industry
Research
Buyer/User
Academic +
Other
English
Speaking
Non-English
Speaking
UK 63% 61% 60% 92% 40% 66% 60%
USA 51% 52% 50% 46% 60% 52% 50%
Germany 18% 13% 30% 15% 60% 16% 21%
Australia 15% 14% 15% 15% 20% 16% 12%
Canada 11% 8% 20% 0% 40% 9% 14%
France 7% 7% 10% 8% 0% 7% 7%
Japan 5% 3% 15% 0% 0% 3% 7%
Brazil 3% 3% 5% 0% 0% 3% 2%
China 2% 1% 5% 0% 0% 3% 0%
Italy 2% 1% 5% 0% 0% 0% 5%
Other 8% 10% 10% 0% 0% 9% 7%
None of these 11% 15% 5% 0% 0% 9% 14%
Column n 109 71 20 13 5 67 42

19. 0%
10%
20%
30%
40%
50%
60%
70%
Which Country Produces the Best MR?
The Big Message
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Questions
Why are the UK & USA so high/different?
Is this true for everybody?
What are the implications of this?

20. Selecting Variables for Analysis
1. What are the objectives of the research?
2. What does your experience suggest?
3. What variables are ‘actionable’?
4. Expect to develop the list of key variables
during the analysis, including:
– Dropping variables
– Merging variables
– Creating variables
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21. What are the key findings?
1. Link to the project objectives
2. ‘Need to know’ not ‘nice to know’
3. Supported by patterns or themes in the
data
– Not just a single data point
4. Clear findings
– e.g. In our chart UK and USA are a long way
ahead in terms of Best Research
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22. 0%
10%
20%
30%
40%
50%
60%
70%
Want to see more speakers from Best research quality Non-English
If people do not see enough speakers from your country,
they expect the research to be of a lower quality!
NewMR Survey, May 2015, N=133 (Non-English Speaking=43), Population = English speaking followers of NewMR

23. What can I do with the verbatims?
• Analyse them qualitatively
• Sentiment analysis
• Code them
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24. Simple Example of Coding
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25. Machine versus Human Coding
• Human coding
– Slow, expensive, more accurate
• Computer coding
– Fast, less expensive (or cheap), less accurate
• Hybrid (human coding to train machine
coding)
– Initially: Slow, expensive, accurate
– Repeat projects: Fast, less expensive,
accurate
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26. Advanced analytics procedures
We use advanced analytics when there isn’t
an easier, faster, cheaper option
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Make things as simple as possible,
but not simpler.
Albert Einstein

27. Ray Poynter, Marketing Research & Social Communication, 2015 27

28. Ray Poynter, Marketing Research & Social Communication, 2015 28

29. Big Picture
1. Researchers work with data and they
produce answers and advice
2. Storytelling is currently considered the
best way to deliver market research
results
3. Start with the Total Picture
4. Then explore important variations
5. Focus on ‘Need to Know’ – not ‘Nice to
Know’
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30. Before Next Lesson
1. Read Chapter 11 – How to Analyse
Quantitative Data
2. Complete the survey on the website
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31. Questions?
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32. Quiz Lesson 6
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Put your name on the sheet