2. Study of marketers
a recent CEB study of nearly
800 marketers at Fortune
1000 companies found the
vast majority of marketers
still rely too much on intuition
— while the few who do use
data aggressively for the most
part do it badly.
4. Information used to make
decisions were based on
● Previous experience or intuition
● conversations with managers and colleagues
● expert advice
● one-off customer interactions.
● Data from previous years
5. Judgment built from past experience is increasingly
unreliable.
example
Assumptions such as
older consumers don’t
use Facebook or send
text messages can
quickly become
outdated.
8. Some are dangerously distracted by data
Data smitten marketers severly
underperformer
9. WHY?
They tend to lose sight of end goals and chang
their direction as soon as there is a blip in the
dashboard which can magnifying the probl
because dashboards often capture respon
based metrics such as clicks and aren’t ti
more important measures such as custom
loyalty or lifetime value
10. The best focus on goals
and filter out noise
The profile of top performing
marketers as rated by the
managers are called “Focusers”.
11. Traits of “Focusers”:
Ability to ask
Strategic
questions based
on dataability to
ask
Narrow focus
on higher-order
goals.
comfort with
ambiguity
12. Marketers get better access to raw
numbers and big data keeps growing,
the importance of
this filtering ability
will only intensify.
T
i
p
W
h
e
n
a
n
u
m
b
e
r
i
s
t
o
o
l
a
r
g
e
o
r
Source: travel.trade.gov
13. The bad news:
10% 90%
Only 10% of marketers succeed in
filtering process
.
.
.
The rest 90% fails
.
November 2015
The bad news for marketing leaders is that ability to
filter out noise is rare and hard to teach.
14. The good news:
The good news is that a well-guided team
environment can protect noise chasers from
themselves.
.
15. Managerial
Relevence
To drive effective data use, the manager
should reiterate critical business goals
constantly (to keep them front-of-mind
despite distractions), teach marketers to put
data front and center in their decision
making, and sensitize marketers to common
data interpretation mistakes.This enables
even the most distractible data lovers to
overachieve.