This document discusses using big data and social media signals to understand consumers at an individual level. It advocates moving beyond metrics and numbers to humanize data by understanding people's interests, passions, behaviors and how they engage with brands across multiple touchpoints. The key points discussed are: - Leveraging data signals to gain actionable insights about individuals and at scale. - Understanding consumers holistically by what they pay attention to online, not just transactions. - Mapping social data like interests, behaviors and recommendations to identify addressable audiences for brands. - Using tools like network analysis and interest mapping to better understand audience communities and engagement. The overall message is that brands can architect more personalized and relevant engage

1. If you got to know me…
Jonathan Lyon, Global Director of Strategic Insight, LBi
#dmaemail
Sponsored by

2. IF YOU GOT TO
KNOW ME…
Jonathan Lyon
Global Director of Strategic Insight

4. people are more than the
actions we ask them to take

5. we need to understand them
beyond the context in which we
asked them to act

6. the math and the music

7. the pixel and the portrait

8. It’s about data driven
storytelling to uncover truth

9. mining and mapping digital
desire paths

10. not charting customer
journeys

11. It’s about going beyond the
analysis of impressions

12. and mapping expressions

13. of intent, desire, passion and
interest

14. mining the big data flows to
create a representation…

15. not of all of us

16. but each of us

17. think, feel, say and do

18. With a more granular and forensic
understanding of people as people we can
architect new brand engagements...
engineered serendipity
anticipatory advertising
personalised persuasion

19. “I AM THE QUERY”

20. Hit me with me some serendipity.
Given data about me, find new things I will
like. If I like a thing, find more of it, or
remove the thing I don’t.

21. the new imperative
• Leverage data derived signals to uncover actionable
insight
• Understand people better, in depth, individually and at
scale
• Interrogate evidenced based behaviour to provide
actionable intelligence that shapes, guides and informs
strategy at scale and pace

22. the web is changing

23. big data landscape
Implicit and explicit
signals of
- Behaviour
- Interest
- Lifestyle
- Perception
- Consideration
- Recommendation
- Advocacy
- Purchase Propensity

24. evidenced insight through real data
provides a unique opportunity to understand what
people are paying attention to and engaging with.
Not by asking them, but by measuring moment by
moment what they engage with, when, where,
with who for how long, and how it makes them
feel and how it makes them behave.

25. our approach
• Our approach is to provide a forensic understanding of consumers beyond
transactional metrics and performance
• By understanding the ‘whole’ consumer we
provide an acute understanding of how best to drive
engagement
• We believe in moving beyond numbers and
humanising data to understand people as people,
not metrics
• In today's omni-channel, multi-device ecosystem,
our marketing promise needs to be "right place,
right time, right offer"
• This requires forensic insight at scale
Think
Feel
Say
Do

26. big data implications
It’s not about
BIGGER spread
sheets, it’s
about bigger
ideas

27. data distinction
social media is the set
of applications and
platforms allowing
people to participate
in online social activities
social data
is the collective
information produced by
millions of people as they
actively participate in online
activities
Vs

28. social data DNA
social
data
demographic
product
intention
psychographic
Interest
behavioural
location
recommendation

29. Data approach
• We focus not just on collecting data on historical behavior, but on
connecting data to anticipate how, where and when to engage
consumers
• We go beyond transactional and online behaviour
• The true significance of the massive digital and big data flows is our
ability to uncover the interests and passions through which brands
can engage consumers

30. SO HOW DO WE THIS?

31. How?
• Massive ingestion of social signals from across the social web
• We classify, categorise and map all behaviours and actions to
entities, people, places, cultural references and brands
• We create interest maps and relationship networks for each identified
profile
• We then cluster these to create tribes with behavioural markers and
augment and enrich prospect and customer profiles with this data

32. addressable audiences
Identifying
addressable
audiences beyond
the base is key.
Knowing who they
are, where they are
and how to engage
them is today’s
marketing
imperative.
Brand
Connected
Brand
Affinity
Brand
Referenced

33. Objective
Identify prospects across social touch points and
map interests, likes, behaviour, to better
understand key drivers to improve conversion with
context sensitive, relevant messaging across
display, email, social and DM
Addressable Audience Profiling

34. Match Addressable Audience to Social Identities
+ name@email.com
+ additional known
data points
Social Identity Resolution
Circa 25% match rate to
social identity
Recursive Iterative Identity Resolution
Circa 75% match rate to
social identity

35. Profile Addressable Audience with Social Data
Brand, app, tv, music page
likes, engagement and
sharing
Following who classified by
interest and engagement
levels
Pins pinned, on which
boards, from where, which
categories
Brand / product tagged
photos
Following, circles,
engagement by brand,
interest, topic
Channel subscriptions,
video likes and comments
by theme, subject area
Check-ins by brand centric
location
interest graph mapping
passions, interests, consumer tribe
social touch point behaviour
social data ingestion
At scale in real time
social touch point behaviour
engage, share, like, comment, contribute

36. experience continuation
interest
mapping
display
CRM
configurator

37. “mapping audiences –
fashion retailer”

38. Audience Interest Mapping
• Clustered Network Analysis for community
detection using algorithmic approach to identify
‘communities’ of interests
• Three can clearly be seen:
- Football (blue)
- Popular culture (largely females, yellow)
- General sports and sport news channels (red)
This gives us a solid foundation upon whi to understand at a higher level, what our audience is intersted in.

39. Interest Engagement
0%
5%
10%
15%
20%
25%
30%
BBCSporf
piersmorgan
GaryLineker
Joey7Barton
footballacca
UberFacts
SkySportsNews
MarioBaloltelli
rioferdy5
BBCSport
YouTube
themichaelowen
frankieboyle
RobbieSavage8
FootyAccums
FootballFunnys
rickygervais
RoyCropperNOT
timlovejoy
Lord_Sugar
sickipediabot
Footy_Jokes
SkySports
GazGShore
WayneRooney
JodieMarsh
GNev2
JeremyClarkson
Comedy/ banter
Football players/ pundits
Facts & news
Celebrities

40. Venue Identification

41. Content Engagement (video)

42. A FINAL THOUGHT

43. digital information is just
people in disguise

45. THANK YOU