The presentation illustrates and describes media attribution across channels.

1. >
Media
a(ribu,on
<
Media
a'ribu+on
or
when
tracking
the
last
click
is
just
not
enough

2. >
About
Datalicious
§ Datalicious
was
founded
in
November
2007
§ Official
Adobe
&
Google
Analy+cs
partner
§ 360
data
agency
with
team
of
data
specialists
§ Combina+on
of
analysts
and
developers
§ Blue
chip
clients
across
all
industry
ver+cals
§ Carefully
selected
best
of
breed
partners
§ Driving
industry
best
prac+ce
with
ADMA
§ Turning
data
into
ac+onable
insights
§ Execu+ng
smart
data
driven
campaigns
October
2012
©
Datalicious
Pty
Ltd
2

3. >
Smart
data
driven
marke,ng
“Using
data
to
widen
the
funnel”
Media
A(ribu,on
&
Modeling
Op,mise
channel
mix,
predict
sales
Targe,ng
&
Merchandising
Increase
relevance,
reduce
churn
Tes,ng
&
Op,misa,on
Remove
barriers,
drive
sales
Boos,ng
ROMI
October
2012
©
Datalicious
Pty
Ltd
3

4. >
Clients
across
all
industries
October
2012
©
Datalicious
Pty
Ltd
4

5. Media
a(ribu,on
=
Giving
credit
where
credit
it
is
due
October
2012
©
Datalicious
Pty
Ltd
5

6. >
The
ideal
media
dashboard
Channel
Investment
ROMI
Return
Brand
equity
($100)
n/a
$40
Baseline
Offline
$7
330%
$30
TV,
print,
outdoor,
etc
Direct
$1
400%
$5
Direct
mail,
email,
etc
Online
$2
1150%
$25
Search,
display,
social,
etc
October
2012
©
Datalicious
Pty
Ltd
6

7. >
Channels
influence
each
other
=
Paid
media
Organic
PR,
WOM,
search
events,
etc
=
Viral
elements
=
Sales
channels
YouTube,
Home
pages,
Paid
TV,
print,
blog,
etc
portals,
etc
search
radio,
etc
Direct
mail,
Landing
pages,
Display
ads,
email,
etc
offers,
etc
affiliates,
etc
CRM
Facebook
program
Twi(er,
etc
POS
kiosks,
Website,
call
loyalty
cards,
etc
center,
retail
October
2012
©
Datalicious
Pty
Ltd
7

8. >
Success
a(ribu,on
models
Banner
Paid
Organic
Success
Last
channel
Search
Ad
Search
$100
$100
gets
all
credit
Banner
Paid
Email
Success
First
channel
Ad
$100
Search
Blast
$100
gets
all
credit
Paid
Banner
Affiliate
Success
All
channels
get
Search
Ad
Referral
$100
$100
$100
$100
equal
credit
Print
Social
Paid
Success
All
channels
get
Ad
Media
Search
$33
$33
$33
$100
par,al
credit
October
2012
©
Datalicious
Pty
Ltd
8

9. >
First
and
last
click
a(ribu,on
Chart
shows
percentage
of
channel
touch
points
that
lead
Paid/Organic
Search
to
a
conversion.
Neither
first
Emails/Shopping
Engines
nor
last-­‐click
measurement
would
provide
true
picture
October
2012
©
Datalicious
Pty
Ltd
9

10. >
Ad
clicks
inadequate
measure
Only
a
small
minority
of
people
actually
click
on
ads,
the
majority
merely
processes
them
(if
at
all)
like
any
other
adver+sing
without
an
immediate
response
so
adver+sers
cannot
rely
on
clicks
as
the
sole
success
measure
but
should
instead
focus
on
impressions
delivered
October
2012
©
Datalicious
Pty
Ltd
10

11. >
Indirect
display
impact
October
2012
©
Datalicious
Pty
Ltd
11

12. >
Indirect
display
impact
October
2012
©
Datalicious
Pty
Ltd
12

13. >
Indirect
display
impact
October
2012
©
Datalicious
Pty
Ltd
13

14. >
Full
purchase
path
tracking
Introducer
Influencer
Influencer
Closer
$
Paid
Display
Organic
Direct
Online
search
ad
clicks
search
site
visits
sales
Display
Affiliate
Social
Emails,
Offline
ad
views
clicks
referrals
direct
mail
sales
TV/print
Organic
Social
Retail
Life,me
responses
search
buzz
visits
profit
October
2012
©
Datalicious
Pty
Ltd
14

15. >
Full
purchase
path
tracking
Introducer
Influencer
Influencer
Closer
$
Paid
Display
Organic
Direct
Online
search
ad
clicks
search
site
visits
leads
Display
Affiliate
Social
Emails,
Offline
ad
views
clicks
referrals
direct
mail
sales
TV/print
Organic
Social
Retail
Life,me
responses
search
buzz
visits
profit
October
2012
©
Datalicious
Pty
Ltd
15

16. >
Path
across
different
segments
Introducer
Influencer
Influencer
Closer
$
Product
Channel
1
Channel
2
Channel
3
Channel
4
A
vs.
B
Clients
vs.
Channel
1
Channel
2
Channel
3
Channel
4
prospects
Brand
vs.
Channel
1
Channel
2
Channel
3
Channel
4
direct
resp.
October
2012
©
Datalicious
Pty
Ltd
16

17. >
Purchase
path
example
October
2012
©
Datalicious
Pty
Ltd
17

18. >
Purchase
path
data
example
U123
1/1/12
12:00
RED
AD
YAHOO
NEWS
$20
U123
1/1/12
12:05
RED
AD
SMH
FINANCE
$20
U123
1/1/12
12:10
GOOGLE
BRAND
TERM
-­‐
U123
1/1/12
12:11
WEBSITE
VISIT
-­‐
U123
1/1/12
12:12
WEBSITE
EVENT
-­‐
U123
3/1/12
14:00
GOOGLE
GENERIC
TERM
$20
U123
3/1/12
14:01
WEBSITE
VISIT
-­‐
U123
7/1/12
17:00
EMAIL
OPEN
$20
U123
8/1/12
15:00
GOOGLE
BRAND
TERM
$20
U123
8/1/12
15:01
WEBSITE
CONVERSION
$100
October
2012
©
Datalicious
Pty
Ltd
18

19. >
Full
vs.
par,al
purchase
path
data
Display
Display
Email
Search
impression
impression
response
response
$
✖
✔
✔
✔
Display
Display
Display
Direct
impression
impression
impression
visit
$
✖
✖
✔
✔
Display
Display
Display
Display
impression
impression
impression
response
$
✖
✖
✔
✔
Display
Display
Search
Search
impression
impression
response
response
$
✖
✔
✔
✔
October
2012
©
Datalicious
Pty
Ltd
19

20. >
Full
vs.
par,al
purchase
path
data
Display
Display
Email
Search
impression
impression
response
response
$
✖
✔
✔
✔
Display
impression
5%
to
65%
variance
Display
impression
Display
impression
Direct
visit
$
✖
in
conversion
a(ribu,on
✖
✔
✔
Display
for
different
channels
due
to
Display
Display
Display
$
impression
par,al
purchase
path
data
impression
impression
response
✖
✖
✔
✔
Display
Display
Search
Search
impression
impression
response
response
$
✖
✔
✔
✔
October
2012
©
Datalicious
Pty
Ltd
20

21. >
Tracking
offline
sales
online
§ Email
click-­‐through
– Include
offline
sales
flag
in
1st
email
click-­‐through
URL
aler
offline
sale
to
track
an
‘assisted
offline
sales’
conversion
§ First
login
aler
purchase
– Similar
to
the
above
method,
however
offline
sales
flag
happens
via
JavaScript
parameter
defined
on
1st
login
§ Unique
phone
numbers
– Assign
unique
website
numbers
to
responses
from
specific
channels,
search
terms
or
even
individual
visitors
to
match
offline
call
center
results
back
to
online
ac+vity
§ Website
entry
survey
for
purchase
intent
– Survey
website
visitors
to
at
least
measure
purchase
intent
in
case
actual
offline
sales
cannot
be
tracked
October
2012
©
Datalicious
Pty
Ltd
21

22. >
Offline
sales
driven
by
online
Adver,sing
Phone
Fulfilment,
campaign
sales
CRM,
etc
Retail
Confirma,on
sales
email,
1st
login
Website
Online
Online
sales
Virtual
sales
research
sales
confirma,on
confirma,on
Cookie
October
2012
©
Datalicious
Pty
Ltd
22

23. >
Tracking
offline
responses
online
§ Search
calls
to
ac+on
for
TV,
radio,
print
– Unique
search
term
only
adver+sed
in
print
so
all
responses
from
that
term
must
have
come
from
print
§ PURLs
(personalised
URLs)
for
direct
mail
– Brand.com/customer-­‐name
redirects
to
new
URL
that
includes
tracking
parameter
iden+fying
response
as
DM
§ Website
entry
survey
for
direct/branded
visits
– Survey
website
visitors
that
have
come
to
site
directly
or
via
branded
search
about
their
media
habits,
etc
§ Combine
data
sets
into
media
a'ribu+on
model
– Combine
raw
data
from
online
purchase
path,
website
entry
survey
and
offline
sales
with
offline
media
placement
data
in
tradi+onal
(econometric)
media
a'ribu+on
model
October
2012
©
Datalicious
Pty
Ltd
23

24. >
Search
call
to
ac,on
for
offline
October
2012
©
Datalicious
Pty
Ltd
24

25. >
Personalised
URLs
for
direct
mail
ChrisBartens.company.com
>
redirect
to
>
company.com?
CampaignID=DM:123&
Demographics=M|35&
CustomerSegment=A1&
CustomerValue=High&
CustomerSince=2001&
ProductHistory=A6&
NextBestOffer=A7&
ChurnRisk=Low
[...]
October
2012
©
Datalicious
Pty
Ltd
25

26. October
2012
©
Datalicious
Pty
Ltd
26

27. What
promoted
your
visit
today?
q Recent
branch
visit
q Saw
an
ad
on
television
q Saw
an
ad
in
the
newspaper
q Recommenda+on
from
family/friends
q […]
How
likely
are
you
to
apply
for
a
loan?
q Within
the
next
few
weeks
q Within
the
next
few
months
q I
am
a
customer
already
October
2012
q […]
©
Datalicious
Pty
Ltd
27

28. >
Website
entry
survey
De-­‐duped
Campaign
Report
Greatest
Influencer
on
Branded
Search
/
STS
}
Channel
%
of
Conversions
Channel
%
of
Influence
Straight
to
Site
27%
Word
of
Mouth
32%
SEO
Branded
15%
Blogging
&
Social
Media
24%
SEM
Branded
9%
Newspaper
Adver+sing
9%
SEO
Generic
7%
Display
Adver+sing
14%
SEM
Generic
14%
Email
Marke+ng
7%
Display
Adver+sing
7%
Retail
Promo+ons
14%
Affiliate
Marke+ng
9%
Referrals
5%
Conversions
a'ributed
to
search
terms
Email
Marke+ng
7%
that
contain
brand
keywords
and
direct
website
visits
are
most
likely
not
the
origina+ng
channel
that
generated
the
awareness
and
as
such
conversion
credits
should
be
re-­‐allocated.
October
2012
©
Datalicious
Pty
Ltd
28

29. >
Adjus,ng
for
offline
impact
-­‐5
-­‐15
-­‐10
+5
+15
+10
October
2012
©
Datalicious
Pty
Ltd
29

30. >
Tradi,onal
modelling
to
fill
gaps
Use
of
tradi+onal
econometric
modelling
to
measure
the
impact
of
communica+ons
on
sales
for
offline
channels
where
it
cannot
be
measured
directly
through
smart
calls
to
ac+on
online
(and
thus
cookie
level
purchase
path
data).
October
2012
©
Datalicious
Pty
Ltd
30

31. >
Purchase
path
vs.
a(ribu,on
§ Important
to
make
a
dis+nc+on
between
media
a'ribu+on
and
purchase
path
tracking
– Not
the
same,
one
is
necessary
to
enable
the
other
§ Tracking
the
complete
purchase
path,
i.e.
every
paid
and
organic
campaign
touch
point
leading
up
to
a
conversion
is
a
necessary
requirement
to
be
able
to
actually
do
media
a'ribu+on
or
the
alloca+on
or
conversion
credits
back
to
campaign
touch
points
– Purchase
path
tracking
is
the
data
collec+on
and
media
a'ribu+on
is
the
actual
analysis
or
modelling
October
2012
©
Datalicious
Pty
Ltd
31

32. >
Media
a(ribu,on
example
Even/weighted
a'ribu+on
Last
click
a'ribu+on
COST
PER
CONVERSION
October
2012
©
Datalicious
Pty
Ltd
32

33. >
Media
a(ribu,on
example
?
TV/Print
Even/weighted
a'ribu+on
?
Internal
?
ads
Website
content
?
Email
?
Last
click
a'ribu+on
Direct
mail
COST
PER
CONVERSION
October
2012
©
Datalicious
Pty
Ltd
33

34. >
Media
a(ribu,on
models
Display
Display
Display
Search
impression
impression
response
response
$100
Last
click
0%
0%
0%
100%
a(ribu,on
Even
25%
25%
25%
25%
a(ribu,on
Weighted
X%
X%
Y%
Z%
a(ribu,on
October
2012
©
Datalicious
Pty
Ltd
34

35. >
Media
a(ribu,on
models
Introducer
Influencer
Influencer
Closer
$
Product
?%
?%
?%
?%
A
vs.
B
Prospects
?%
?%
?%
?%
vs.
clients
Brand
vs.
?%
?%
?%
?%
direct
resp.
October
2012
©
Datalicious
Pty
Ltd
35

36. >
Media
a(ribu,on
example
Publisher
1
Publisher
2
TOTAL
CONVERSION
VALUE
Increase
Publisher
3
spend
[…]
Reduce
Increase
spend
spend
Publisher
N
ROI
FULL
PURCHASE
PATH
October
2012
©
Datalicious
Pty
Ltd
36

37. >
Media
a(ribu,on
case
studies
§ Suncorp:
Implementa+on
of
ad
server
data
collec+on
tags
via
SuperTag
to
facilitate
the
collec+on
of
full
purchase
path
data
in
the
company’s
DoubleClick
ad
server.
Followed
by
a
manual
one-­‐
off
data
analysis
including
a'ribu+on
model
development
in
phase
1
as
well
as
report
automa+on
in
a
dedicated
Splunk
environment
in
phase
2.
– 2,078%
project
ROI
from
implementa+on
of
ini+al
quick
wins
only
by
reducing
media
waste
respec+vely
cost
for
a
limited
set
of
brands
in
phase
1.
§ Telstra:
Implementa+on
of
ad
server
data
collec+on
tags
via
SuperTag
to
facilitate
the
collec+on
of
full
purchase
path
data
in
the
company’s
Atlas
ad
server.
Followed
by
a
manual
one-­‐off
data
analysis
including
a'ribu+on
model
development.
– 403%
project
ROI
from
implementa+on
of
ini+al
quick
wins
only
by
reducing
media
waste
respec+vely
cost.
October
2012
©
Datalicious
Pty
Ltd
37

38. Datalicious
Op,maHub
October
2012
©
Datalicious
Pty
Ltd
38

39. >
Op,maHub
plaoorm
architecture
SuperTag
app
JavaScript
SuperTag
JS
JavaScript
Client
pages
Tags
Browser
genera,ng
JS
hosted
by
client
referencing
execu,ng
app.supert.ag
or
on
c.supert.ag
SuperTag
JS
SuperTag
JS
Requests
Addi,onal
3rd
party
data
(i.e.
CRM,
ad
server
POS,
social,
etc)
data
collec,on
Data
Data
Splunk
saved
Dedicated
Splunk
Data
SuperTag
searches
and
client
Splunk
processing
DataCollector
dashboards
server(s)
Server(s)
d.supert.ag
October
2012
©
Datalicious
Pty
Ltd
39

40. 101011010010010010101111010010010101010100001011111001010101
010100101011001100010100101001101101001101001010100111001010
010010101001001010010100100101001111101010100101001001001010
>
About
Datalicious
October
2012
©
Datalicious
Pty
Ltd
40

41. >
Short
but
sharp
history
§ Datalicious
was
founded
in
November
2007
§ Official
Adobe
&
Google
Analy+cs
partner
§ 360
data
agency
with
team
of
data
specialists
§ Combina+on
of
analysts
and
developers
§ Blue
chip
clients
across
all
industry
ver+cals
§ Carefully
selected
best
of
breed
partners
§ Driving
industry
best
prac+ce
with
ADMA
§ Turning
data
into
ac+onable
insights
§ Execu+ng
smart
data
driven
campaigns
October
2012
©
Datalicious
Pty
Ltd
41

42. >
Smart
data
driven
marke,ng
“Using
data
to
widen
the
funnel”
Media
A(ribu,on
&
Modeling
Op,mise
channel
mix,
predict
sales
Targe,ng
&
Merchandising
Increase
relevance,
reduce
churn
Tes,ng
&
Op,misa,on
Remove
barriers,
drive
sales
Boos,ng
ROMI
October
2012
©
Datalicious
Pty
Ltd
42

43. >
Wide
range
of
data
services
Data
Insights
Ac,on
Plaoorms
Analy,cs
Campaigns
Data
collec,on
and
processing
Data
mining
and
modelling
Data
usage
and
applica,on
Adobe,
Google
Analy,cs,
etc
Tableau,
Splunk,
SPSS,
etc
Alterian,
SiteCore,
Inxmail,
etc
Web
and
mobile
analy,cs
Customised
dashboards
Targe,ng
and
merchandising
Tag-­‐less
online
data
capture
Media
a(ribu,on
analysis
Marke,ng
automa,on
Retail
and
call
center
analy,cs
Media
mix
modelling
CRM
strategy
and
execu,on
Data
warehouse
solu,ons
Social
media
monitoring
Data
driven
websites
Single
customer
view
Customer
segmenta,on
Tes,ng
programs
October
2012
©
Datalicious
Pty
Ltd
43

44. >
Over
50
years
of
experience
Chris+an
Bartens
Elly
Gillis
Michael
Savio
Chaoming
Li
Founder
&
Director
General
Manager
Head
of
Insights
Head
of
Data
§ Bachelor
of
Business
§ Bachelor
of
§ Bachelor
of
Arts
&
§ Bachelor
of
Management
with
Communica+ons
with
Science
with
applied
Technology
with
marke+ng
focus
print
and
digital
focus
mathema+cs
focus
microelectronics
focus
§ Web
analy+cs
and
§ Digital
marke+ng
and
§ CRM
and
marke+ng
§ Solware
and
website
digital
marke+ng
project
management
research
and
analy+cs
development
work
work
experience
work
experience
work
experience
experience
§ Space2go,
E-­‐Lol,
§ M&C
Saatchi,
Mark,
§ ANZ
Bank,
Australian
§ Standards
Australia,
Tourism
Australia
Holler,
Tequila,
IAG,
Bureau
of
Sta+s+c,
DF
Securi+es,
Globiz,
§ SuperTag
founder,
OneDigital,
Telstra
DBM
Consultants
Etang
ADMA
Analy+cs
Chair,
§ Australian
gold
medal
§ ADMA
lecturer
on
§ Developing
his
own
I-­‐COM
Board
Member
in
surf
boat
rowing
marke+ng
tes+ng
CMS
plazorm
LinkedIn
profile
LinkedIn
profile
LinkedIn
profile
LinkedIn
profile
October
2012
©
Datalicious
Pty
Ltd
44

45. >
Best
of
breed
partners
October
2012
©
Datalicious
Pty
Ltd
45

46. >
Clients
across
all
industries
October
2012
©
Datalicious
Pty
Ltd
46

47. >
Great
customer
feedback
“[…]
Datalicious
quickly
earned
our
respect
and
confidence
[…]
understand
our
business
needs,
deliver
value,
push
our
thinking
[…].
Likeable,
transparent
and
trustworthy.
I
would
be
happy
to
recommend
Datalicious
to
anyone.”
Murray
Howe,
Execu+ve
Manager,
Suncorp
Group
"[…]
Datalicious
brought
with
them
best
prac>ce
analy>cs
to
demonstrate
the
true
value
of
our
marke>ng
dollars
[…]
have
become
a
criBcal
business
partner
[…]
provided
great
insights
which
have
driven
key
business
decisions.”
Trang
Young,
Senior
Marke+ng
Manager,
E*Trade
Australia
“The
Datalicious
guys
are
great
to
work
along
side
[…]
'no
stone
unturned'
approach
to
finding
solu>ons
to
challenges
[…]
knowledge
and
passion
for
web
analy>cs
and
best
of
breed
web
opBmizaBon
was
second
to
none”
Steve
Brown,
Senior
Business
Analyst,
Vodafone
“[…]
The
Vodafone
implementa>on
of
SiteCatalyst
is
one
of
the
most
impressive
I
have
seen
and
ranks
in
the
top
10
[…].
It
is
an
amazing
founda>on
for
taking
ac>on
on
the
data
and
improving
ROI.”
Adam
Greco,
Consul+ng
Lead,
Omniture
October
2012
©
Datalicious
Pty
Ltd
47

48. >
Great
customer
feedback
"[…]
Datalicious
understand
the
value
of
informa>on
and
how
to
leverage
it
using
best
of
breed
soEware.
I
would
recommend
the
team
without
hesita>on
[...]."
James
Fleet,
Marke+ng
Director,
Appliances
Online
"[...]
Datalicious
have
been
inBmately
involved
in
building
our
analyBcs
soluBon.
Most
importantly
their
knowledge
of
best
prac>ce
combined
with
innova>ve
solu>ons
has
allowed
our
business
to
remain
nimble
and
current.
They
are
also
nice
guys."
Tzvi
Balbin,
Group
Digital
Marke+ng
Lead,
Catch
of
the
Day
"[...]
Datalicious
are
helping
us
to
move
from
a
last
click
campaign
measurement
model
to
a
more
accurate
media
aFribu>on
approach.
[...]
potenBal
to
significantly
change
our
media
planning
[...].
Highly
recommended."
Keith
Mirgis,
Senior
Digital
&
Social
Media
Marke+ng
Manager,
Telstra
"We
engaged
Datalicious
to
support
a
strategic
change
in
our
business
[...]
understand
our
customers
[and
their
transac>ons]
beFer
to
ensure
we
retained
as
many
as
possible
[...]"
Natalie
Farrell,
Direct
Marke+ng
Manager,
Luxo}ca
October
2012
©
Datalicious
Pty
Ltd
48

49. Contact
us
cbartens@datalicious.com
Learn
more
blog.datalicious.com
Follow
us
twi(er.com/datalicious
October
2012
©
Datalicious
Pty
Ltd
49

50. Data
>
Insights
>
Ac,on
October
2012
©
Datalicious
Pty
Ltd
50