Janssen Pharmaceuticals conducted social media netnography research to understand patient discussions about schizophrenia in order to improve their website. Netnography is a research methodology that analyzes publicly available user-generated online content. Janssen analyzed social media conversations to learn about patient segments, symptoms discussed, information sources, and opportunities to start conversations to empower patients. This helped Janssen enhance their website with different landing zones tailored to different patient needs.

1. expect great answers
Conversation Research Leveraging the power of Social Media
November 13, 2014 Kent Institute of Medicine & Surgery
@robert_dossin
http://uk.linkedin.com/in/robertdossin

2. The world as it used to be

3. Research has changed
From asking questions...
...to having a conversation

4. Conversation research
‘Passive’ Listening
‘Active’ Listening

5. Passive
Active
Input
Look smart
You have listened
Fill in gaps
Only spontaneous feedback
Natural language
Find where people talk

6. Tapping into ACTIVE online conversations
Social Media
Nethnography
Social Media
Dashboards / Monitoring
exploratory for
enhanced quality
6

7. Social media netnography
= research methodology that makes use of publicly available user-generated- content in order to answer a research question
7

8. 24x7 Case Study
8

9. Business Objectives & Approach
To empower patients and carers to initiate conversations with HCPs, and each other and to raise awareness of the benefits of continuous medication, the research needed to identify what patients discussed, how they discussed it, in what context and what were opportunities for Janssen to start the conversation with patients suffering from Schizophrenia, but also carers and HCPs.

10. EMEA Schizophrenia 24 x 7

11. How understanding patients helped Janssen to improve its website using Social Media Netnography Research Outcomes
Healthcare Janssen Pharma – EMEA Schizophrenia 24 x 7
Corinne Pilgrim, EMEA Product Director Psychiatry,
Janssen Pharmaceuticals,
•Different landing zones for different patient segments
•In 16 countries/5 languages
•200K unique visitors
•20% revisit rate

12. 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
Reversed research process

13. 13
1. Universe detection

14. Representativeness
‘It’s the end of the world as we know it’
14

15. Sampling is still key
15

16. Visitors
# sources
Small #
Large influence
Medium influence
Specialized in topics
Long tail
16

17. Visitors
# 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/
17

18. Good definition of a universe
18

19. Keywords for sampling
Conversations on
epilespy
Conversations on
Epilepsy brands
19
Selecting the right keywords

20. Conversations on
doctor
Analysis
Conversations on
epilespy
Conversations on
Epilepsy brands
20
Selecting the right keywords

21. Google keywords
Thesaurus
Keywords for search engine optimization
21

22. Conversations are the new unit of analysis

23. 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
About profile information

24. 24
2. Data collection

25. 25

26. Data structuring is important
All doubles, headers & footers eliminated
One post can only appear once!

27. 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%
27

28. Public & fan pages only
Becoming friends
28

29. 29
3. Framework development

30. Top down
analysis
Bottom-up
analysis
Two core principles

31. Text analytics is the process of extracting knowledge and information from text
The power of text analytics

32. 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
Sentiment analysis

33. Emotions
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

34. 34
4. Analysis

35. Quartile 1
Quartile 2 & 3
Quartile 4
Quartile 1
Quartile 2 & 3
Quartile 4
Main conversation themes

36. Sentimeter
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
Frequency and duration seizures
Seizure triggers
Medication unloyalty
Treatment
Specific triggers
knowledge
Molecules
Polytherapy
Alternative treatment
Other treatments
Volume
Themes in epilepsy

37. 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?

38. Digital strategy
Netnography can result in an integrated communication & conversations strategy in terms of who to target, with which content, on which platform.
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
Applications

39. In Summary
………………………………………………………………………………………………….…….
………………………………………………………………………………………………….…….

40. Social Media helps you listen!
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?

41. 41
Social media netnography: benefits
Access to highly involved patient
and difficult topics
Many conversations
Most on relevant topics
Ideal to explore new
TAs/topics

42. 42
Social media netnography: limitations
Less of the uninvolved
patient
No probing
Only what is relevant for them
Internet has no boundaries

43. Thoughts to hold on to
A key element of marketing is listening, before joining online discussions Netnography is a great method to mine user generated content from YOUR patientr Patient want to be engaged, because they are engaged. We should reinvent ourselves, using social media to engage with our consumers where they are and when they want Not just send our tradional messages via new channels But by starting a conversation with them!

44. Robert Dossin | Client Solutions Director R.Dossin@skimgroup.com
+44 7904 288898 (mob) +44 208 222 7703 (direct)
@robert_dossin
uk.linkedin.com/in/robertdossin/
@robert_dossin
http://uk.linkedin.com/in/robertdossin