The AIMIA Big data event took place on the 25th of June and it addressed the issue of big data hype. Here are some points to take away from the event.

1. >
Big
data
in
marke.ng
<
What
the
heck?
What
does
it
all
mean
and
how
does
it
help
me?

2. >
Using
data
to
widen
the
funnel
Media
A:ribu.on
&
Modeling
Maximise
reach,
awareness
&
increase
ROI
Tes.ng
&
Op.misa.on
Remove
barriers,
drive
sales
Boos.ng
ROMI
Targe.ng
&
Merchandising
Improve
engagement,
boost
loyalty
“Turning
data
into
ac.onable
insights
to
widen
the
conversion
funnel”
June
2013
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Datalicious
Pty
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2

3. >
Clients
across
all
industries
June
2013
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Datalicious
Pty
Ltd
3

4. >
Wikipedia:
Big
data
In
informaAon
technology,
big
data
consists
of
datasets
that
grow
so
large
that
they
become
awkward
to
work
with
using
on-­‐hand
database
management
tools.
DifficulAes
include
capture,
storage,
search,
sharing,
analyAcs,
and
visualizing.
Big
data
are
high
volume,
high
velocity,
and/or
high
variety
informa.on
assets
that
require
new
forms
of
processing
to
enable
enhanced
decision
making,
insight
discovery
and
process
opAmizaAon.
June
2013
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Datalicious
Pty
Ltd
4

5. June
2013
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Datalicious
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5
Big
data
=
Bo:lenecks

6. >
Big
data
analy.cs
bo:lenecks
June
2013
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Datalicious
Pty
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6
Fast
laptops
now
have
up
to
8GB
of
RAM,
that
means
you
can
compute
up
to
6GB
of
raw
data
very
fast
in
memory
thus
bypassing
the
biggest
boTleneck:
I/O

7. >
Power
vs.
distributed
compu.ng
June
2013
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Adding
more
supercomputers
is
difficult
as
they
are
complex
and
expensive
but
adding
machines
to
a
distributed
compuAng
network
is
fairly
cheap
and
‘easy’.

8. June
2013
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Datalicious
Pty
Ltd
8
Big
data
=
Structure?

9. >
Does
big
data
need
structure?
June
2013
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Datalicious
Pty
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9
Volume,
velocity,
variety,
sexy
Structure,
maintenance,
boring

10. >
Big
data
s.ll
needs
structure
June
2013
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Datalicious
Pty
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10
Volume,
velocity,
variety,
sexy
Structure,
maintenance,
boring

11. June
2013
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Datalicious
Pty
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11
Big
data
=
Hype?

12. >
Importance
of
research
experience
June
2013
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12
The
consumer
decision
process
is
changing
from
linear
to
circular.
Considera.on
set
now
grows
during
(online)
research
phase
which
increases
importance
of
user
experience
during
that
phase
(Online)
Research

13. Offer
Issue
Offer
>
Design
and
test
experiences
June
2013
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Pty
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13
Email
Live
chat
Phone
call
Phone
call
Le:er
Email
Issue
All
customers
Segment
A,
B,
C
Segment
D,
E
Influencers
High
valu
Display
Postcard
Display
FAQs

14. >
The
consumer
data
journey
June
2013
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To
reten.on
messages
To
transac.onal
data
From
suspect
to
To
customer
From
behavioural
data
From
awareness
messages
Time
Time
prospect

15. Transac.onal
data
>
Combining
data
sources
is
key
June
2013
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Pty
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15
3rd
party
data
+
The
whole
is
greater
than
the
sum
of
its
parts
Behavioural
data

16. June
2013
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Example:
Phone
call
data

17. June
2013
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Example:
Website
data

18. June
2013
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Example:
Social
media
data

21. >
Maximise
iden.fica.on
points
20%
40%
60%
80%
100%
120%
140%
160%
0
4
8
12
16
20
24
28
32
36
40
44
48
Weeks
−−−
Probability
of
idenAficaAon
through
Cookies
June
2013
21
©
Datalicious
Pty
Ltd

22. Customer
data
exposed
in
page
or
URL
on
login
and
logout
CustomerID=12345&
Demographics=M|25&
CustomerSegment=A1&
CustomerValue=High&
ProductHistory=A6&
NextProduct=A7&
ChurnRisk=High&
[...]
>
Registra.on
and
login
pages
June
2013
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Datalicious
Pty
Ltd
22

23. hTp://www.acme.com/email-­‐landing-­‐page.html?
CampaignID=12345&
CustomerID=12345&
Demographics=M|25&
CustomerSegment=A1&
CustomerValue=High&
ProductHistory=A6&
NextProduct=A7&
ChurnRisk=High&
[...]
>
Email
click-­‐through
iden.fica.on
June
2013
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Datalicious
Pty
Ltd
23

24. acme.com/chris.anbartens
redirects
to
amp.com.au?
CampaignID=12345&
CustomerID=12345&
Demographics=M|25&
CustomerSegment=A1&
CustomerValue=High&
ProductHistory=A6&
NextProduct=A7&
ChurnRisk=High&
[...]
>
Personalised
URLs
for
direct
mail
June
2013
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Datalicious
Pty
Ltd
24
Catch
on
acme.com
404
error
page

25. >
Combine
data
across
devices
June
2013
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Pty
Ltd
25
Mobile
Home
Work
Tablet
Media
Etc

26. >
Indirect
combina.on
of
data
June
2013
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Datalicious
Pty
Ltd
26
Social
IDs
Client
ID
Web
data
Address
Geo
segment
Roy
Morgan
Etc
MOSAIC
Hitwise
Social
data

29. June
2013
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Pty
Ltd
29
Contact
us
cbartens@datalicious.com
Learn
more
blog.datalicious.com
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us
twi:er.com/datalicious

30. Smart
data
driven
marke.ng
June
2013
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Datalicious
Pty
Ltd
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