The document discusses social influence analysis in marketing, highlighting the significance of qualitative data and contextual understanding in identifying influencers and trends. It emphasizes that social influence transcends mere numbers and is rooted in relationships within online communities. Case studies from various companies illustrate how contextualized influence analysis has informed marketing strategies and enhanced engagement with target audiences.

1. SOCIAL INFLUENCE ANALYSIS:
A NEW INSIGHT TERRITORY
Anthony Fradet - Linkfluence
UK Chief Operating Officer
@anthonyfradet
Luis Fernandes - Expedia
EMEA Research and Consumer
Insights Director

2. The mission of the researcher

3. QUANT QUAL
The traditional toolkit

4. QUAL
The new toolkit
SOCIALQUANT

5. Qualitative data
on a quantitative scale
In vivo (vs in vitro)

6. Social data: qualitative data on a quantitative scale
Vast collection
of individual opinions
Identification of major trends
and weak signal
Wide possibilities
from social KPI measurement
to in-depth content analysis

7. Social data: in vivo (vs in vitro)
Untamed, spontaneous material
Opinions expressed reach
an audience, triggering tangible
influence mechanisms
No interrogation bias

9. What makes research methodologies fit
for insight generation?

10. Framed Analysis
Business Question
Traditional research
Quotas
Samples
Representativeness
Discussion guides
Valid Insight
Structured / bias-controlled data

11. Quotas
Samples
Representativeness
Discussion guides
Unstructured / biased data
Framed Analysis
Social media research (for him)
“Lack of control on
key parameters”
Business Question
Valid Insight

12. Social media research
Structured
data
Unstructured
data
Business Question
Valid InsightFramed Analysis

14. 1) Definition of the data universe
(semantic profiles)
2) Data segmentation
3) Data contextualisation
through relevant social analysis frames

15. 1) Definition of the data universe
(semantic profiles)
2) Data segmentation
3) Data contextualisation
through relevant social analysis frames

16. Social influence is
an element of context unique to social data

17. Social influence?
An individual’s ability to affect other people's
thinking in an online community

18. Numbers?

19. We are in the age of the tyranny of numbers

20. Numbers are good liars

21. Social influence goes beyond numbers,
it is 100% contextual and based on
relationships and influence dynamics

22. Understand
the context

24. TECHNOLOGY
(RADARLY)
CLIENT
SERVICES
MARKETING
INTELLIGENCE

25. 01
UK POLITICAL WEB OBSERVATORY
HOW NETWORK ECOSYSTEM ANALYSIS
PREDICTED THE EU REFERENDUM RESULT

26. Published early June 2016
www.politicalweb.co.uk

27. www.politicalweb.co.uk
Colours refer to
communities
Nodes are websites
Links are hypertext
links between two
websites
(inbound/outbound)
Node size indicates
the level of
influence of a
website

31. 02
DANONE CITIES
HOW SOCIAL AUDIENCE MAPPING HELPS
UNDERSTAND CONSUMER MINDSET

32. 2 objectives
Identify the key communities of interest
structuring the social landscape in 4 major cities
Recommend smart actions to engage
these communities in a meaningful way

33. How to capture the social conversation
happening in a city and put it into context?

34. Can we trust individuals to tell the truth
about what they are influential on?

35. Good proportion of what I post
Good proportion of what I post
Almost never post
Post rarely
Interest is not influence

36. To make sense of audiences,
content analysis at scale is necessary

37. The key
Organising individuals in communities based
on the topics they really talk about
(not what they say they are)

38. Topic Drops

39. Key outcomes for Danone
Sharp understanding of cultural background
Identification of relevant content area
Food for innovation in brand initiative

40. 03
EXPEDIA - DIGITAL FOOTPRINT
HOW HIGHLY CONTEXTUALISED INFLUENCE
ANALYSIS INFORMED EXPEDIA’S
INFLUENCER STRATEGY
Luis Fernandes - Expedia
EMEA Research and Consumer
Insights Director

41. Modes
&
context

42. 121

43. Business objective
Increase site visits
and number of transactions

44. How to achieve this?
Increase brand presence throughout
the decision making process prior to booking
Identify the right influencers
for the right mode at the right time

45. How is the travel ecosystem structured
in different markets?

46. The UK Travel Ecosystem
Colours refer to
communities
Nodes are websites
Links are hypertext
links between two
websites
(inbound/outbound)
Node size indicates
of the level of
influence of a
website

47. Travel Online Ecosystem UK vs Germany
1,685 websites
25 sub-communities
2,051 websites

48. Travel Online Ecosystem UK vs Germany
Travel News
1%
Sports
2%
Family
4%
Innovation & Tech
4%
Business & Finance
5%
Food & Drinks
10%
Lifestyle
11%
Travel
12%
Beauty & Fashion
15%
Online Media
22%
Travel
31%
Online Media
15%
Lifestyle 9%
Food & Drinks
7%
Family
5%
Beauty & Fashion
4%
Business & Finance
4%
Culture &
Entertainment 3%

49. Travel Online Ecosystem UK vs Germany
Travel News
1%
Sports
2%
Family
4%
Innovation & Tech
4%
Business & Finance
5%
Food & Drinks
10%
Lifestyle
11%
Travel
12%
Beauty & Fashion
15%
Online Media
22%
Travel
31%
Online Media
15%
Lifestyle 9%
Food & Drinks
7%
Family
5%
Beauty & Fashion
4%
Business & Finance
4%
Culture &
Entertainment 3%

50. Travel Online Ecosystem UK vs Germany
Travel News
1%
Sports
2%
Family
4%
Innovation & Tech
4%
Business & Finance
5%
Food & Drinks
10%
Lifestyle
11%
Travel
12%
Beauty & Fashion
15%
Online Media
22%
Travel
31%
Online Media
15%
Lifestyle 9%
Food & Drinks
7%
Family
5%
Beauty & Fashion
4%
Business & Finance
4%
Culture &
Entertainment 3%

51. How to integrate context into affluence
and make it operational?

52. Contextualised influencer identification
Social audience
Monthly visits and
views
Potential
for working
with
brands
Relevance for
Expedia
Influence
score*
*Influence score: Score (from 0 to 100) based on the inbound links received by the websites within the ecosystem.
Blogs with a
high influence
score*
Sites with
strong social
following
Identification of
matching
Expedia Travel
Mode

53. Travel modes
in the UK travel ecosystem
• TRAVEL MODE A, B & D are the three main travel
modes in the Travel Ecosystem, with 83% of the
top influencers within the UK Travel ecosystem.
• These three travel modes provided most traffic.
Travel mode B gathers the stronger follower base,
with an average 880k followers.
• The most influential opinion leaders:
AVERAGE MONTHLY VISITS AVERAGE SOCIAL FOLLOWERS
TRAVEL MODE A 368K 197K
TRAVEL MODE B 35,5k 880K
TRAVEL MODE C 71,4k 84,9K
TRAVEL MODE D 103K 295K
TRAVEL MODE E 13,8K 18,1K
TRAVEL MODE F 95,3K 46,2K
Key influencers
Cumulated
social audience
Dominant Travel
Mode
25.5m à TRAVEL MODE A
4.2m à TRAVEL MODE B
1.8m à TRAVEL MODE C
1.5m à TRAVEL MODE B
1.4m à TRAVEL MODE D
31%
26%
26%
10%
10%
7%
Share of influencers
by travel mode

54. Travel mode C
What kind of content do they produce?
• Visual posts, documenting breaks that are largely relaxation,
culture or luxury focused (e.g. warm destinations, spa days,
boutique hotels)
Place of travel within their life
Travels to relax mentally and physically
Booking Behaviour
• Destination is less important than an ideal resort. Likely to book all
inclusive packages, sometimes offline
• Want hassle-free booking
Other interests
Food | Fashion | Style | Weekend breaks |
Health
103k MONTHLY SITE VISITS ON AVERAGE
295k SOCIAL FOLLOWERS PER INFLUENCER (AGGREGATED AVERAGE)

55. Outcome for Expedia:
Involvement in contextual conversations
- Opportunities to develop more relevant content for specific
context or simply to share it in the right place…
- Key influencers to work with beyond number of followers

56. Two things to remember…

57. QUAL
The new toolkit
SOCIALQUANT

58. One thing to remember
Context
is
everything

59. Anthony Fradet - Linkfluence
UK Chief Operating Officer
@anthonyfradet
Luis Fernandes - Expedia
EMEA Research and Consumer
Insights Director