Raymond Chau discusses the importance and benefits of digital analytics. He explains that digital analytics involves collecting data from websites, apps, social media, and other online sources to better understand user behavior and make improvements. Some key benefits include optimizing marketing spending, fixing issues on websites to reduce bounce rates, running A/B tests to optimize pages, and personalizing the user experience through recommendations and targeted advertising. While traditional marketing can be difficult to measure and optimize, digital analytics allows for real-time data collection, targeted messaging, and faster iteration to improve performance.

1. WHY
DIGITAL
ANALYTICS?
Raymond
Chau
Nov
2013
1

2. About
me
• Building
web
site
for
10
years
• Working
in
isobar,
a
full
serviced
digital
agency
around
the
globe
• My
blog:
http://www.whymeasurethat.com
2

3. WHAT
IS
DIGITAL
ANALYTICS?
3

4. What
is
digital
analytics?
“Collect
and
use
data
to
make
things
better”
4

5. How
do
we
collect
data?
Data
PRIVATE
Data
logs
tracking
(e.g.
server
logs) (e.g.
Google
Analytics)
survey
(e.g.
iPerception)
PUBLIC
Data
free
(e.g.
Google
Trends,
forums)
paid
(e.g.
Hitwise,
Compete)
5

6. Example:
Google
Analytics
Free
tool
offered
by
Google
to
monitor
user
activities
on
their
web
sites
or
mobile
apps
6

7. Example:
Facebook
Insight
Allows
developers
and
Page
owners
to
see
how
their
app
/
page
perform
7

8. Example:
Google
Trends
Public
available
data
that
allows
user
to
see
how
a
particular
search-­‐term
performs
over
a
time
period
on
different
regions
8

9. Example:
TripAdvisor
Forum
is
one
of
the
best
(and
mostly
free)
source
of
qualitative
data
from
your
customers!
See
how
honest
are
they!!
9

10. WHAT
CAN
DIGITAL
ANALYTICS
DO?
10

11. Improve
advertising
spending
effectiveness
ROI
can
be
calculated
and
see
which
channel
is
more
effective
11

12. Fix
the
entrance
of
the
site
75%
of
visitors
immediately
leave
the
site
after
seeing
the
page.
What’s
wrong?
12

13. Optimize
check
out
process
Only
36%
people
checkout
after
adding
things
to
cart,
what’s
wrong?
Where
do
people
go
if
they
quit
from
billing
page?
Are
they
looking
for
shipping
details?
13

14. Experimenting
(A/B
Testing)
14

15. Personalisation
• Movie:
Minority
Report
(2002)
15

16. Personalisation
e.g.
email
marketing
using
user
behaviour
data
16

17. Personalisation
e.g.
recommendations
based
on
purchase
history
data
17

18. Personalisation
e.g.
advertisement
based
on
facial
expression
data
http://www.cenique.com/cenique/advertising_Platform.php
18

19. Recommendations
Provide
recommendations
using
crowd-­‐sourced
data
(e.g.
Netflix,
Amazon)
19

20. Re-­‐marketing
/
re-­‐targeting
4.
visitor
goes
back
to
your
site
because
of
the
promo,
and
may
possibly
purchase
3.
visitor
goes
to
a
popular
site,
promotional
ad
targeted
to
the
product
the
visitor
just
read
is
displayed
1.
visitor
enters
your
site
2.
visitor
doesn’t
buy
anything
and
leaves,
but
you
know
he
has
seen
a
particular
product
and
put
it
into
the
cart
20

21. TRADITIONAL
MARKETING
V.S.
DIGITAL
MARKETING
21

22. Measurability
Traditional
Digital
• Very
difficult
to
measure
• Can
be
very
expensive
to
measure
• Cannot
measure
how
viewers
engage
with
the
content
• Very
easy
to
measure
• Almost
free
to
measure
• Can
measure
how
viewers
engage
or
even
interact
with
the
content
!
!
22

23. Message
Delivery
Traditional
Digital
• Message
deliver
to
as
many
audiences
as
possible
• Have
no
knowledge
on
audiences
• Less
likely
to
respond
• Message
deliver
only
to
your
target
audiences
• Know
who
the
audiences
exactly
are
• More
likely
to
respond
as
the
message
is
relevant
!
!
23

24. Example:
Non-­‐target
ad
v.s.
target
ad
Non-­‐target
Ad
-­‐
TV
Target
Ad
-­‐
Facebook
• Can’t
target
audiences
that
are
really
relevant
to
your
product
• For
example,
you
can’t
target
those
who
really
have
acne
problems
• Can
target
visitors
in
finest
level
• For
example,
you
can
target
based
on
country,
city,
gender,
age
range,
interests,
etc
!
!
24

25. Speed
Traditional
Digital
• Data
takes
time
to
collect
and
analyse
• Cannot
respond
to
audience
immediately
• Marketers
spend
longer
time
+
more
money
to
get
insights
and
adapt
• Data
are
collected
or
even
processed
at
real
time
• Can
respond
and
give
tailored
response
to
audience
real
time
• Allows
marketers
to
fail
cheap
and
fast
!
!
25

26. LATEST
TOPIC
ON
DIGITAL
ANALYTICS
26

27. BIG
DATA!!!
Abacus
(old
method)
Calculator
(new
method)
Calculation
Excel
(old
method)
Big
Data
(new
method)
Data
Storage
&
Analysis
27

28. We’re
generating
more
and
more
data
• Example:
facebook
• 699
million
people
login
Facebook
daily
• 300
million
photos
are
uploaded
daily
• Every
60
seconds
• 510
comments
are
posted
• 293,000
statuses
are
updated
• 136,000
photos
are
uploaded
28

29. Example:
Obama
2012
election
campaign
• Collect
1
database
that
factors
80
pieces
of
information
about
voters:
(e.g.
age,
race,
sex
and
even
voting
history)
• Target
right
audience:
focus
on
voters
who
might
change
their
mind
based
on
voters’
‘persuasive
score’
• Personalisation:
deliver
policy
messages
or
fund
raising
event
tailored
for
individual
voters
29

30. Example:
Disneyland
1.
Opt-­‐in
for
a
wireless
tracking
bracelet
‘MagicBand’
which
links
to
the
system
My
Magic+
3.
Mickey
Mouse
now
knows
a
lot
about
YOU!!!
2.
Visitors’
real
time
location,
riding
patterns
&
purchases
are
all
recorded
30

31. SUMMARY
31

32. Data:
to
use
or
not
to
use?
TARGET
ad
reveals
teen’s
pregnancy
http://bit.ly/1b3u5k5
32

33. Want
to
know
more?
Google
+
page
+RaymondChau
facebook
fan
page
WhyMeasureThat
ME
LinkedIn
linkedin.com/in/raymondchau
blog
www.whymeasurethat.com
twitter
@raymondchau
33

34. THANK
YOU!
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