getting answers without asking questions at bhbia workshop
TRANSCRIPT
Getting answers without
asking questions
Using social media netnography with
patients
January 17th 2013
Robert Dossin – Director Life Sciences & Healthcare
Ghent I Rotterdam I London I Timisoara I New York
www.insites-consulting.com
Today’s session
Introduction
Social Media Netnography: Methodology
Applications
Cases (4)
FAQ (10)
Today’s
programme
Listening online - helping patients
In this session InSites Consulting will show how
observational methods can lead to new patients
insights for pharmaceuticals teams.
3
User-
generated-
content
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Observational research
1. Social media netnography
2. Multimedia ethography
Netnography
Where does observing fit in?
6
Discussions Surveys % Observing
Traditionally used most in
the pharmaceutical industry
Not yet fully exploited
in the pharmaceutical
industry
≠ clinical observation
6
Who has
experience
with
observational
research?
8 3 pillars Observational
research
Tapping into online conversations
Social Media Nethnography
Social Media Dashboards / Monitoring
exploratory for enhanced quality
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Observational
research
Social media netnography
= research methodology
that makes use of publicly
available user-generated-
content in order to answer a
research question
10
Observational
research
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The process
Ethnography
As with any innovation and new method there are advantages as well as
concerns. Please take 5 minutes and write down your concerns, the reasons why,
the applications you think of and what you really would want to know
CONCERNS APPLICATIONS
REASONS WHY I WOULD WANT TO KNOW
Exercise 3
Observational
research
13
Play by the book!
Respect key MR principles
ESOMAR & BHBIA guidelines
PHARMA specific
requirements and drug
safety/pharmacovigilance
Even AGENCY-CLIENT
specific processes
13
When pioneering novel techniques it is important to rely on a partner who can go along with you, follow you in your reflections, bring in suggestions and adapt accordingly. We have appreciated InSites’ flexibility, the stimulating discussions we had, their drive to transform the “golden nugget” into a workable approach, … finally their commitment to move forward and to deliver.
Rudi Van Campenhout, UCB pharma
Social media netnography Award winning methodology
ANALYSIS
SURVEY/ TOPIC GUIDE DEVELOPMENT
SAMPLING RESPONDENTS
FRAMEWORK DEVELOPMENT
SAMPLING UNIVERSE DETECTION
PASSIVE DATA COLLECTION
Traditional research Social media nethnography
TOP-DOWN & BOTTOM-UP CONTENT & TEXT ANALYTICS
ACTIVE DATA COLLECTION
Observational
research
Reversed research process
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Observational
research
1. Universe detection
Representativeness
‘It’s the end of the world as we know it’
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Observational
research
Conversations are the new unit of analysis
Keywords for sampling
Conversations on epilespy
Conversations on Epilepsy brands
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Observational
research
Selecting the right keywords
Conversations on doctor
Analysis
Conversations on epilespy
Conversations on Epilepsy brands
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Observational
research
Selecting the right keywords
Good definition of a universe
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Observational
research
Google keywords
Thesaurus
Keywords for search engine optimization
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Observational
research
Sampling is still key
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Observational
research
Vis
ito
rs
# sources
Small # Large influence
Medium influence Specialized in topics
Long tail
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Observational
research
Vis
ito
rs
# sources
http://www.healthboards.com/
http://www.coping-with-epilepsy.com/ http://scott-lwe.blogspot.com/
http://bschool.pepperdine.edu/studentblog/index.php/2010/07/freedom-from-epilepsy-
doesnt-come-free/
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Observational
research
Profile information on poster / user level
– Internet has no boundaries
– Only information available that is spontaneously shared
– Representativity: what do we know about profile on social media?
Profile information on source level
– Type of social media source
– Meta data
About influentials
– On person level
– On source
Observational
research
About profile information
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Observational
research
2. Data collection
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Observational
research
All doubles, headers & footers eliminated
One post can only appear once!
Data restructuring
= maximum error reduction
Observational
research
Historical data
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
week 1
week 2
week 3
week 4
week 5
week 6
week 7
week 8
week 9
week 10
week 11
week 12
brand 1 65% 82% 64% 63% 50% 25% 23% 35% 40% 45% 48% 49%
Market 75% 55% 55% 48% 29% 54% 58% 60% 65% 63% 68% 70%
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Observational
research
Public & fan pages only
Becoming friends
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Observational
research
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Observational
research
3. Framework development
Top down analysis
Bottom-up analysis
Observational
research
Two core principles
Text analytics is the process of
extracting knowledge and
information from text
Stage 1: Extraction of terms
What do I want to use?
Stage 2: Group terms in higher level
concepts or categories
Observational
research
The power of text analytics
3.Qualitative analysis
2.Associative pattern
recognition
1. Descriptive taxonomy detection
To what extent do we find our research
topics back?
Which terms often co - occur? Which
concept are often mentioned bottom - up?
Analyse original verbatims via qualitative
content analysis
Observational
research
Analysis process
Sentiment of the
conversation Sentiment of a
brand / topic
'I had a terrible day. I used brand x and felt better'
'I had a terrible day. I used brand x and felt better'
Conversation level Sentence level
1 positive – 1 negative 1 positive
Observational
research
Sentiment analysis
Emo
tio
ns
Excitement
Relaxed
Social
Beauty
Violence
Swear words
Despair
Weak
Loneliness
Elated, Excited, Enthusiastic
Contented, Relaxed, Satisfied
Happiness
Happy Joyful Cheerful Satisfied
Proud Trust, Love, Respect
Beautiful, Admired, Attractive
Aggressive, Abusive, Dominating
Agony, Despair, Ashamed
Tired , Bored, Weak
Lonely, Rejected, Alienated
Surprise
Amazed Surprised Astonished
Fear
Afraid Nervous Tense Worried
Insecure
Anger
Angry Furious Mad Irritated
Resentful
Sadness
Sad Disappointed Regretful Gloomy
Pessimistic
Disgust
Disgust Contempt Nasty
Observational
research
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Observational
research
4. Analysis
Methodology
– Different clusters of words in the buzz are found that refer
to different themes
– For each theme, we determine the size of the cluster and
the sentiment of the cluster
Interpretation
– The themes are divided into different quadrants, based
on quartiles in volume and sentimeter.
– The different quadrants thus need to be interpreted in a
relative way, and within a certain language. E.g. themes
in quadrant are relatively more positive than themes in
quadrant but can still have a negative sentiment.
– Meaning of different quadrants
• 1: Act: themes that are often mentioned with a negative
sentiment
• 2: Develop: themes that are often mentioned with a positive
sentiment
• 3: Threats: themes with negative sentiment that are
currently not often mentioned but that are explicitely
negative for certain niches
• 4: Potential: themes with mixed sentiment that are often
mentioned. In the future, we can try to influence the
sentiment of those themes positively
1
2
3
4
Qu
art
ile
1
Qu
art
ile
2 &
3
Qu
art
ile
4
Quartile 1 Quartile 2 & 3 Quartile 4
2
1
Main conversation themes
Observational
research
Observational
research
Sen
tim
ete
r family
seizures
stakeholders
symptoms
medication brands
medication
epilepsy
diagnosis
types epilepsy
social impact children
administration
medication
Success
treatment
(no) control
surgery
side effects
budget
diet
generic medication
Frequency and
duration seizures
Seizure triggers
Medication
unloyalty
Treatment
Specific triggers
knowledge Molecules
Polytherapy
Alternative
treatment
Other treatments
Volume
Main conversation themes in epilepsy
Observational
research
21%
15%
9%
9%
7%
7%
6%
6%
6%
6%
5%
4%
4%
4%
3%
3%
3%
1%
sleep issues and fatigue
stress and anxiety
emotional and mood
dizziness
pain
other psychological
other
headache
memory issues
symptoms
cardiovascular
confusion
weight issues
muscles
vision
respiratory
gastro
tumor
What symptoms are most often mentioned in
online conversations?
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Observational
research
Product evaluation
&
branding
Share of brands in total amount of
conversations
Total sample
N = 42469
Brands
14%
N = 5836
30%
N = 12754
Pharmaceutical treatment
Total sample
100%
N = 42469
2% (832 conversations)
are about generic
products
Observational
research
Brands for epilepsy
treatment are
mentioned in about
14% of online
conversations
Observational
research
0,00%
1,00%
2,00%
3,00%
4,00%
5,00%
6,00%
7,00%
8,00%
9,00%
10,00%
June July August September October November
Keppra 5,74% 4,73% 5,81% 4,92% 4,49% 3,45%
Lamictal 4,90% 4,33% 5,02% 3,91% 3,54% 3,40%
Topamax 2,23% 1,58% 1,29% 1,45% 0,86% 1,57%
Depakote 0,95% 1,10% 1,47% 1,76% 1,72% 0,83%
Trileptal 1,96% 1,47% 1,41% 1,45% 0,77% 0,61%
Vimpat 1,61% 1,72% 1,01% 0,86% 0,41% 0,31%
What is the share of voice for the different
treatments for epilepsy?
The number of conversations about
Keppra and Vimpat decreased over the
last half year.
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
Sentimeter Brands for treatment of Epilepsy (top 10 brands with most buzz)
Comparison with sentiment across brands vs top 10 Significantly higher than average No significant difference with average Significantly lower than average
N = 281
Vimpat
0,38
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 156
Epilim
0,33
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 221
Trileptal
0,28
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 1037
Lamictal
0,25
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 341
Topamax
0,25
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 138
Lamotrigine
0,23
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 306
0,41
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 1341
Keppra
0,21
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 129
Diastat
0,19
Depakote
0
-20
10
-10
-40
-30
20
30
40
50
60
70
80
90
-50
N = 192
Dilantin
0,14
Observational
research
Sentiment about Depakote is significantly more positive in comparison with other brands.
Comparing the current results with the results of last year (different calculation method),
we observe that sentiment on Keppra decreased relatively compared to other brands.
Patient
language
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Observational
research
Petit mal
Also called ‘absence’
People just stand and stare vacantly
My mind was wandering, blank, in a daze
When asked to speak, would talk then just go blank and lose my
entire train of thought and having no idea what I had implied
My eyes would blink rapidly and then I would go blank as if I were
daydreaming and my mind would be shot
Observational
research
Applications
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Observational
research
Typical management objectives
InSites Consulting has performed many Social Media Netnography studies in several
therapeutic areas: Parkinson’s disease, Restless Leg Syndrome, Epilepsy and
Rheumatoid Arthritis.
The main objectives of these studies were to…
1. …get insights directly from patients based on their spontaneous online discussions
2. …increase the effectiveness of the brand plans
Typical research questions
Get insights directly from patients based on their spontaneous online discussions
1. Which are the main topics that are discussed by patients and their caregivers?
2. Which language do patients use when talking about these themes?
3. What is the emotionality of the different topics? How can these emotions be explained?
4. What are the main information sources consulted by patients & caregivers?
Increase the effectiveness of the brand plans
1. How big is the buzz about product brands (you and competitors)? How did this change over time?
2. What is the tone of voice of the buzz about product brands ? Which sentiments are used?
3. Is this in line with the desired brand positioning?
Digital strategy Netnography study that results in an integrated communication & conversations
strategy in terms of who to target, with which content, on which platform.
(Reporting will be based on our activation model.)
Consumer insightment
Netnography study that results in insights and ideas on unmet consumer needs,
buying decision processes & product category usage.
Campaign evaluation tracker Netnography study that results in an ad-hoc evaluation or tracking of a campaign
Online Brand audit Netnography study that results in a 360° view on your brand
and its main competitors
Product evaluation netnography / tracker Netnography study that results in ad-hoc evaluation or tracking of a product
All Applications
Definitions
In Summary
………………………………………………………………………………………………….…….
………………………………………………………………………………………………….…….
53
Social media netnography: benefits
Access to highly involved patient and difficult topics Many conversations Most on relevant topics Ideal to explore new TAs/topics/countries
53
54
Social media netnography: limitations
Less of the uninvolved patient No probing Only what is relevant for them Internet has no boundaries
54
Cases
Cases
UCB – Social Media as the central nervous system for learning about epilepsy
Patients at the Heart
The next slides illustrate cases to demonstrate different area‟s of patient research
CASE 2 – Janssen – Diabetes (II)
3 steps to get to a new strategy using a mix of contemporary observation methods with patients
CASE 3 – Danone – Breast Feeding Community
Drivers, barriers & opportunities for formula feeding
CASE 4 – Janssen – And they lived happily ever after
Analysing user generated content on social media to increase the elderly‟s quality of life
CASE 5 – Janssen - Schizophrenia 24 x 7
How understanding patients helped Janssen to improve its website using Social
Media Netnography Research in 5 languages
Thoughts to hold on to Patients are consumers, “consumers of health” ; their discussions
are what they perceive the truth
Netnography is both a quantitative as well as a qualitative method
that requires domain knowledge to mine the user generated content
from patients
Patients want to be engaged, „cause they are engaged!
We should reinvent ourselves, engage with them where they are
& support Pharma companies in their patient conversations
Not just send our tradional messages via new channels
Not just by becoming a new channel checklist company
Stay tuned!
We believe in sharing knowledge with
all of our stakeholders.
Become friends with us, visit our blogs,
download our papers and presentations,
order our books…
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InSites Consulting blog
The Conversation Manager blog
How cool brands stay hot blog
Robert’s experience:
Robert is MD in the UK and Global head of Life Sciences & Healthcare at InSites Consulting and is
responsible for the market research and consulting offerings for all clients in the Healthcare sector
Before joining InSites Consulting, Robert worked at IMS Health, the worlds leading information provider in
the pharmaceutical industry. In the six years that he worked at IMS, as VP Marketing he has been
responsible for raising awareness of IMS high value products & services
Robert started his career at Nissan, at the European HQ of the Japanese car manufacturer as Market
Researcher and has had various marketing roles with increasing levels of responsibility.
Also, he was a marketing director at Forrester Research for 5 yrs, the European HQ of the worlds leading
Internet Technology Research firm and thought-leader in Information Technology advice.
Robert’ expertise and project experience:
Robert is used to partner with commercial teams, business units heads and chief marketing officers on
strategy development and implementation – and is an expert in launching new products, (digital) marketing
and customer understanding. He works with many Pharma & Health companies such as AstraZeneca,
GSK, J&J and is a regular speaker at Healthcare and marketing conferences..
Educational background:
Robert studied Business Economics with a major in Market Analysis and Business Statistics at the Erasmus
University, Netherlands, hold a Masters in Science (MSc) degree in Marketing and a Postgraduate Diploma
in Marketing (DipM) from the Chartered Institute of Marketing in the UK, where he is also a Chartered
Marketer and elected Fellow. In addition, he sits on the medical marketing industry group of the CIM and on
the editorial board of the Journal of Medical Marketing.
Robert Dossin Managing Director UK
Bio