Effective research needs to result in outcomes, and changes that are beneficial to the organisation commissioning the research. The ability of the research to help bring about change depends on how it is communicated. In many cases, the only part of the research that has any impact or visibility is the presentation, i.e. the actual presentation and any report / ‘leave behind’/ or 'take-aways'. In this webinar, Ray Poynter, focuses on how to use the ‘Think, Feel, Do!’ approach to create effective communications, i.e. communications that result in actions.

1. Effective Presenting
with ‘Think, Feel, Do!’
Ray Poynter
Webinar, 7 October 2020

2. Sponsors
Gold
Silver
Communication

3. The difference between
means and ends
Means
Engagement
Storytelling
Visualisation
End
Action

4. Do!
Think
Feel

5. Do!
• Launch the product
• Choose option A
• Address customer dissatisfaction with check-in
• Do more research
• Cancel the project
• Keep doing exactly what you are doing …

6. Finding the Do!
Business
Question
Business
Context
Your data
and analysis
Do!

7. Changing Behaviour is Hard
From Behavioural Economics, we know changing behaviour is hard.
The ‘facts’ do not often change behaviour.

8. Changing Behaviour
Inform the rider
(Think)
Motivate the elephant
(Feel)
Shape the path
(Do!)

9. The Think
Business
Question

10. The Think
Business
Question
Business
Context

11. The Think
Business
Question
Business
Context
Your data
and analysis

12. The Think
Business
Question
Business
Context
Your data
and analysis
Think
->Do!

13. The Do! Defined by the Think
Do!
Feel
Think

14. The Do! Created by the Feel
Do!
Feel
Think

15. Think, Feel, Do
Think
– The facts are still important, they are platform that
everything else is built on.
Feel
– People rarely change their beliefs or behaviour because of
the facts – change happens at the emotional level.
Do
– Every story should be aimed at creating an outcome, an
action that the teller wants the recipient to do.

16. Example – USA Movie Popcorn
Center for Science in the Public Interest (CSPI).
In 1994 it revealed that
Medium bag popcorn = 37 grams saturated fat.
USDA (United States Department for Agriculture).
Recommended maximum = 20 grams.
20
37
0
10
20
30
40
Grams Fat
USDA Max
Popcorn

17. Creating Emotion
=
37 grams
++
37 grams

18. Movie Popcorn
Think, Feel, Do
• Think, the ‘facts’:
– Popcorn has saturated fat, saturated fat is not good,
there are limits
• Feel
– 3 junk meals in one day is dumb/gross
• Do
– When you are about to buy popcorn, think about all
that fat, feel a bit sick/scared, buy something else

19. Robust Simplification
Movie Popcorn Data
About double your daily fat allowance
Visual Story
A day’s worth of unhealthy food

20. Movie Popcorn
What was left out?
• Other things in the popcorn, e.g. salt & sugar
• Large bag of popcorn
• Other foods eaten in movie theatres
• Other comparators, e.g. normal daily meal

21. Structure

22. Narrative Flow
•A beginning, middle, and end
•The flow should be linear
•Use storytelling devices (e.g. humour,
personal anecdotes, interaction etc)
to enhance the flow

23. What are the key elements?
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
• Try to ensure you are talking about large groups of
people – ideally majorities
For example:
• If men are slightly more interested
• If young people are slightly more interested
• If people in London are slightly more interested
• Check Young, Men in London – that may be the key message

24. Do Not (Normally) use the Questionnaire Sequence
• Q1 by Age and Sex
• Q1 by Region
• Q2 by Age and Sex
• Q2 by Region
• ::
• ::
• Q1 by Age and Sex
• Q2 by Age and Sex
• ::
• ::
• Q1 by Region
• Q2 by Region
• ::
• ::

25. Do Not (Normally) use the Questionnaire Sequence
0
5000
10000
15000
20000
25000
0
100
200
300
400
500
600
700
Brazil China France Germany India Italy Japan Russia South Africa Sweden UK USA World
CasesPerMillion
DeathsPerMillion
Deaths and Cases Per Million of Population
(until 27 September 2020)
Deaths / 1Million Case / 1MillionSorted by alphabet
https://www.worldometers.info/coronavirus/ - downloaded 27 September 2020

26. Sort the data by something meaningful
0
5000
10000
15000
20000
25000
0
100
200
300
400
500
600
700
Brazil USA UK Italy Sweden France South Africa Russia World Germany India Japan China
CasesPerMillion
DeathsPerMillion
Deaths and Cases Per Million of Population
(until 27 September 2020)
Deaths / 1Million Case / 1MillionSorted by declining number of deaths per million https://www.worldometers.info/coronavirus/
downloaded 27 September 2020

27. Typical Structure
The Lead /
Elevator Pitch
Executive
Summary
Three themes
T1, T2, T3
Do
Theme 1
Theme 2
Theme 3
Evidence
1a, 1b, 1c
Evidence
2a, 2b, 2c
Evidence
3a, 3b, 3c
Close with the
Do!
Appendix
(Treasure Chest)
HT, Mike Sherman

28. Three Pieces of Evidence
• Focus on contrast, not repetition
– Different people learn in different ways
• For example:
– Quantitative evidence
– Qualitative evidence
– Video, open-ends, analytics

29. The Lead
Nora Ephron
When Harry Met Sally
Sleepless in Seattle
1st Day in Journalism School
5 Ws (Who, What, When, Where & Why?)
Asked to write the Lead for the school newspaper
“The entire school faculty will travel to Sacramento next
Thursday for a colloquium in new teaching methods.
Among the speakers will be anthropologist Margaret
Mead, college president Dr. Robert Maynard Hutchins, and
California Governor Edmund Brown.”
All the students wrote about the 5Ws – good, but not right.
The Lead?
No school next Thursday!

30. Truth Not Precision
MOVE!
TruthPrecision
Precision vs Truth in the real world

31. The Appendix

32. The Appendix
• Explain it is a Treasure Chest
– Not a garbage dump
• Make the information is easier to find
– A mix of tables, notes, and visuals
• It does not have to be one document
– It does not have to be in one place
• It needs to be one concept
– A single lookup system – accessing all the parts

33. 33
Storyboarding

34. Feelings

35. The Weak Link Between Finding
the Story and Telling the Story
In finding the story we have multiple data sources
We have many analytical tools to find the story in the
data
• For example, you might use predictive analytics to find the
story
But, the best way to tell the story does not have to rest
on the ‘best’ data
• You might use an image or consumer video to tell the story

36. Research shows we make
too many mistakes
You learned this from the data, but the
image conveys the message.

37. Use Analogies
• Explaining a joke is like dissecting a frog. You
understand it better but the frog dies in the
process.
• Pitching the film: Alien ‘like Jaws in space’
• ‘AI and big data is like high school sex, everybody
is talking about it, but nobody is actually doing it’

38. Take one thing away
from the ecosystem and
the whole system
collapses.

39. Memes

40. Tip – Collect Examples

41. Confusing messages

42. The Story?
• It is all about the Do!
• Use Think to find the Do!
• Use Feel to cause the Do!
• Structure your presentation to deliver the Do!
– The Lead
– The Story
– The Recommendation

43. Q & A

44. Sponsors
Gold
Silver
Communication