MindTime case studies 1:12:12

®

Te c h n o l o g y t o H e l p P e o p l e U n d e r s t a n d P e o p l e

8
Case
Studies

Details
in
these
case
studies
have
necessarily
been
obscured

in
order
to
protect
client
conﬁden5ality.

Case
Studies
2

We
are
presen5ng
you
with
a
small
sample
of
work
undertaken
using
the
MindTime
Cogni5ve

Framework.
These
studies
were
conducted
using
two
MindTime
technology
plaWorms,
one
for

internal
HR/OD
use
and
one
for
marke5ng
and
audience
segmenta5on.
If
you
are
interested
in

learning
more
MindTime
and
its
many
uses
please
ask
us
for
more
informa5on.

1. Building
high-‐performing
teams
One
of
the
world's
leading
financial
management
companies
is
worried.
.
.

page

3

2. Understanding
composi9on
of
survey
panel
popula9on
A
top
provider
of
brand
research
communi5es
suspected
.
.
.

page

6

3. Gaining
ac9onable
insights
from
customer
sa9sfac9on
survey
A
top
MBA
university
knew
that
not
all
students
believed
.
.
.

page

9

4. Understanding
brand
sen9ment
within
communi9es
A
revealing
look
at
how
brands
s5mulate
(or
don’t)
.
.
.

page
14

5. Enabling
effec9ve
self-‐ini9ated
global
collabora9on
The
Chairman
had
fiKy-‐two
heads
flying
in
from
around
the
world
.
.
.

page
19

6. Correla9ng
thinking
styles
with
Web
traffic
paIerns
Who
are
all
of
these
people
really?
Is
there
not
a
beQer
way
.
.
.

page
22

7. Effec9ve
messaging
using
MindTime
audience
segmenta9on
Brand
favorability
study
reveals
how
deeply
thinking
drives
opinion

page
25

8. Ad
effec9veness
study
conducted
in
the
EU
and
North
America
Adver5sing
effec5veness
study
reveals
huge
variance
explained
by
MindTime

page
32

®
© 2012 MindTime Technologies Inc. Patent Pending.

3

CASE
STUDY:
Building
high-‐performing
teams.
The
problem:

One
of
the
world's
leading
ﬁnancial
management
companies
is
worried
aKer
recently

deciding
that
it
would
allow
their
brokers
to
work
in
teams
sharing
resources
in
the
form
of

administra5ve
assistance
and
junior
staﬀ.

As
these
teams
of
brokers
started
to
form
across
the
US,
a
few
disquie5ng
problems
began
to

emerge.
Some
teams
seemed
to
‘click’
whereas
others
did
not;
burning
through

administra5ve
assistants
and
even
quickly
ending
in
ugly
feuds.

The
Na5onal
Head
of
High
Net
Worth
(NHW)
teams
asked
MindTime
Inc.
to
evaluate
the

underlying
issues,
prescribe
solu5ons
and
improve
system-‐wide
performance.

The
plan
was
to
measure
success
based
on
direct
impact
on
revenue.

®

4

CASE
STUDY:
Building
high-‐performing
teams.

Measuring
the
Baseline
• The
Na5onal
Head
NHW
already
had
data
that
allowed
him
to
chart
the
performance
of
teams

na5onally.
Performance
was
measured
by
revenue
by
individual
and
by
team.
For
our
project

the
firm
discounted
any
increase
by
the
increase
in
the
na5onal
average.

Assessment
• We
mapped
20
teams.

• We
tagged
each
team
with
their
performance
data.

• We
then
looked
for
correla5ons
in
paQerns
of
team
make-‐up
and
performance
using
our
maps.

• We
iden5fied
the
op5mal
make-‐up
for
a
team
based
on
this
early
data
and
hypothesized
as
to

how
they
were
collabora5ng
with
their
thinking
to
create
this
success.

Performance
analysis
• We
choose
a
seven
team
sample:
2
poor
performers,
2
mediocre,
and
3
of
the
best.
• We
spent
a
total
of
seven
days
over
a
period
of
two
months
with
each
of
the
teams.

• We
observed,
interviewed,
discussed
and
evaluated
how
they
were
integra5ng
team

members’
thinking.

• We
also
coached
the
teams
on;
roles,
interpersonal
empathy,
workflow
and
other
dynamics

making
team
members
aware
of
the
impact
of
their
thinking
at
work.

®

5

CASE
STUDY:
Building
high-‐performing
teams.
The
Solu.on:

Knowledge
transfer
and
best
prac9ces
implementa9on
• MindTime
developed
an
Op5mal
Thinking
Style
distribu5on
for
High
Net
Worth
Teams
• We
mapped
each
of
the
teams
against
this
and
recommended
changes
for
some
teams
• We
also
developed
a
set
of
best
prac5ces
for
collabora5on
and
informa5on
sharing
based
on

MindTime
principles
• In
concluding
the
project
we
held
a
teams
forum
off
site
bringing
teams
in
from
around
the

country
• We
also
shared
with
each
team
what
we
had
learned
from
the
other
teams
• This
resulted
in
the
development
of
an
informal
informa5on
network

among
teams
across
the
country.
The
purpose
of
this
network
was
to
share
insights
and
best

prac5ces,
support
and
discuss
issues
and
foster
a
culture
of
team
collabora5on
across
the

organiza5on.

Results
• Within
two
months
we
had
started
to
see
significant
improvement
• Revenue
increased
between
14-‐23%
over
the
na5onal
baseline
average
for
the
period.

• The
most
improved
performance
came
from
the
best
teams.
While
they
were
already
top

performers
the
added
knowledge
and
confidence
of
knowing
why
they
were
succeeding
had

them
push
even
harder
in
all
the
right
ways.

• The
MindTime®
method
was
then
deployed
across
more
than
60
of
the
firm’s
top
teams.
®

6

CASE
STUDY:
Understanding
composi9on
of
survey
panel
popula9on.
The
problem:

A
top
provider
of
brand
research
communi5es
suspected
that
any
one
of
their
given

communi5es
did
not
necessarily
represent
the
popula5on
at
large.
Their
concern
remained

despite
the
fact
that
they
had
gone
to
great
pains
to
recruit
(an
on-‐going
task)
people
who,

by
all
other
demographics,
seemed
to
represent
the
popula5on
at
large.

®

7

CASE
STUDY:
Understanding
composi9on
of
survey
panel
popula9on.

Assessment
• All
par5cipants
(255)
were
asked
to
complete
the
GPS
for
the
Mind.
• Other
client
specific
data
was
captured.
• Analysis
of
the
data
is
on
going,
but
we
have
used
our
MAP
to
show
some
very
early
basic

findings
from
a
quick
evalua5on
of
the
distribu5on
of
thinking
styles.

Parameters
• The
surveyed
popula5on
is
a
general
community
and
not
5ed
specifically
to
one
brand.

®

8

CASE
STUDY:
Understanding
composi9on
of
survey
panel
popula9on.

Brief
analysis
• The
panel
popula5on
is
showing
a
marked
skew

towards
Past
&
Present
thinking.
• Even
integrated
thinking
is
showing
a
strong
bias

Present towards
Past
&
Present
perspec5ves.
• The
sample
is
small
(255)
but
that
is
the
average
(low)

size
of
a
marke5ng
panel,
this
bias
should
be
taken

255
people seriously,
it
could
fundamentally
affect
results
of
any

research
conducted.
• Community
member
responses
in
any
study
conducted

will
show
a
bias
towards
conserva5sm,
risk
aversion,

need
for
informa5on,
organiza5on,
tradi5onalism,

process
orienta5on,
and
an
aQrac5on
to
authority
or

Past Future
the
educa5onal
qualifica5ons
of
people.
• The
thinking
styles
most
represented
in
the
survey

Survey
panel
at
research
company panel
are
more
likely
to
belong
to
this
kind
of
brand

research
community
in
the
first
place.
• Future
thinkers
would
likely
not
be
aQracted
to
belong

to
these
kinds
of
community.
They
might
sign
up,
but

they
would
not
likely
show
up.

®

9

CASE
STUDY:
Gaining
new
ac9onable
insights
from
a
customer
sa9sfac9on
survey.
The
problem:

A
top
MBA
university
knew
that
not
all
students
believed
that
they
were
receiving
a
good

educa5on
given
its
cost.
Certain
feedback
from
students
had
indicated
that
some
felt
it
sub

standard,
but
because
of
their
exis5ng
investment
tended
to
s5ck
it
out.
The
university
grew

concerned
that
their
reputa5on
would
suﬀer
in
the
local
community
from
bad
word
of

mouth.
Given
the
5ghtly
knit
nature
of
the
business
community
this
concern
was
probably

warranted.
Their
biggest
fear
was
that
student
reten5on
would
suﬀer
in
the
face
of

compe55on
who
were
rumored
to
be
accep5ng
transfers
from
other
MBA
programs.

®

10

CASE
STUDY:
Gaining
new
ac9onable
insights
from
a
customer
sa9sfac9on
survey.

Assessment
• We
asked
all
students
in
two
MBA
programs
(74)
to
complete
the
GPS
for
the
Mind.
• We
also
captured
the
following
data:
Professor,
age
bracket,
gender
• We
used
MindTime
Maps
capability
to
collect
amtudinal
data
from
the
par5cipants.
A
panel
of

items
was
developed
to
look
at
various
aspects
of
their
experience
at
the
university.

Analysis
• We
mapped
all
par5cipants
in
a
Map
of
the
World
of
thinking.

Present

• Our
MAP
revealed
nothing
special
about
the

distribu5on
of
this
group
of
students.
• A
fairly
typical
picture
of
middle
management
thinking

styles
from
both
engineering
and
business

backgrounds

Past Future

®

11

CASE
STUDY:
Gaining
new
ac9onable
insights
from
a
customer
sa9sfac9on
survey.

Analysis
con9nued
.
.
.

• Analysis
of
responses
on
the

ques5on
of
perceived
value
of

the
educa5on
did
not
show
any

correla5on
between
class
they

were
enrolled
in
or
gender
or

age.

®

12

CASE
STUDY:
Gaining
new
ac9onable
insights
from
a
customer
sa9sfac9on
survey.

*

*

• Analysis
of
responses
on
the
ques5on
of
perceived
value
of
the
educa5on

did
show
marked
correla5on
with
thinking
style.

* • Past
thinkers
were
clearly
the
most
(and
only)
dissa5sﬁed
group
of

students.

* • Present/Futures
showed
the
greatest
sa5sfac5on
with
value
delivered.

®

13

CASE
STUDY:
Gaining
new
ac9onable
insights
from
a
customer
sa9sfac9on
survey.

Analysis
con9nued
.
.
.

Present
• A
second
look
at
our
MAP
analysis
revealed
the
likely

cause
of
student
dissa5sfac5on.

* • The
Professor
(who
taught
both
MBA
classes)
had
a

Future
thinking
style.
• On
further
inves5ga5on
(through
conﬁden5al

conversa5ons
with
Past
thinking
respondents)
it

became
clear
that
the
professors
thinking
style
did
not

*
align
with
Past
thinkers
needs,
nor
did
it
feel

authorita5ve,
thus
undermining
students’
conﬁdence.
• Further,
Past
thinking
students
reported
that
the

curriculum
was
presented
in
a
style
which
precluded

Past Future them
from
gaining
a
deep
grasp
of
the
subjects
being

taught.
“Too
much
talk
and
not
enough
hard
facts,”

said
one
respondent.

®

14

CASE
STUDY:
Understanding
brand
sen9ment
within
communi9es.
The
problem:

A
major
brand
research
community
provider
asked
us
to
help
them
test
whether
people’s

percep5ons
and
thoughts
had
an
effect
on
the
sen5ments
they
expressed
about
various

brands.
At
the
core
of
this
study
were
two
ques5ons.

Does
a
person’s
thinking
style
significantly
drive
their
sen5ments
on
a
given
brand?
Is
it
possible
to
iden5fy
the
fundamental
values
(as
iden5fied
by
the
MindTime
framework)
of

people
who
most
resonate
with
a
given
brand?

®

15

CASE
STUDY:
Understanding
brand
sen9ment
within
communi9es.

Assessment
• 255
people
were
mapped
using
the
GPS
for
the
Mind.
• All
par5cipants
were
asked
to
respond
with
a
favorability
ra5ng
for
10
separate
brands
on
a

scale
of
1-‐5
(1
being
least
and
5
being
most
favored).
• Gender,
age
and
race
were
known
data
about
this
community
and
were
provided
to
us
for

analysis.

Data
analysis
-‐
Group
composi9on
and
sen9ment
• A
series
of
standard
sta5s5cal
techniques
(ANOVA,
regression,
variance,
etc)
was
used
to

analyze
the
data.
• It
was
noted
that
there
were
not
enough
respondents
in
the
sample
to
be
able
to

consistently
show
sta5s5cal
signiﬁcance
in
all
demographic
groups
(race,
age,
gender).

®

16

CASE
STUDY:
Understanding
brand
sen9ment
within
communi9es.

Findings

We
used
data
on
the
Volkswagen
brand
data
as
our
example Across
a
majority
of
brands
tested

thinking
style
was
found
to
have
a

sta5s5cally
signiﬁcant
impact
on

people’s
ra5ng
of
brands.
Favorability by Thinking Style In
this
excerpted
example
we
can

see
that
Future
Present
people

rated
the
brand
most
favorably,

and
Past
thinkers
least
favorably.

* Extroverted,
posi5ve,
organized,

deliberate,
liberal,
social,

energe5c,
inven5ve
people
liked

VW.
They
were
Future/Present

thinkers

* Introverted,
studious,
bookish,

informed,
analy5cal,
risk
averse,

knowledgable,
detailed
people

were
less
sold

®

17

CASE
STUDY:
Understanding
brand
sen9ment
within
communi9es.

Findings
con9nued
.
.
.

* Where
men
exhibit
higher

favorability
ra5ngs
than
women

the
influence
of—image,
novelty,

Females fun,
hip,
extraversion,
trend

Males
semng,
speedy—is
strongest.

* Where
women
exhibit
higher

favorability
ra5ngs
than
men
the

influence
of—prac5cal,

affordable,
recommended
by

other
consumers,
well
built

(German),
trendy,
social,

“right”—is
strongest.

$ If
this
data
were
SmartSliced

by
age
and
socio-‐economic

status
we’d
really
be
zeroing
in

on
some
very
potent
insights.

®

18

CASE
STUDY:
Understanding
brand
sen9ment
within
communi9es.

Findings
con9nued
.
.
.

* 1.1)
Volkswagen

1.2)
BMW

Variance
Explained
5.90%
12.40% * This
chart
shows
the
amount
of
variance
in

favorability
among
respondents
that
can
be

1.3)
Hyundai
6.80%
explained
by
thinking
profile
data
over
and

above
the
influence
of
all
other
demographic

1.4)
Apple
6.20%
factors
1.5)
MicrosoL
2.00%
1.6)
Coca
Cola
1.70%

*
We
know
from
other
studies
that
opinions,

1.7)
Dunkin’
Donuts
1.80%
beliefs,
amtudes
and
values
are
also
driven

1.8)
Tropicana
4.20%
by
these
same
influences
1.9)
Levis
3.40%
1.10)
Southwest
Airlines
6.90%
1.11)
UPS
0.90% If
MindTime
is
explaining
this
amount
of

1.12)
Heinz
1.50% variance
in
sen5ment
data,
we
can

1.13)
Budweiser
1.70% reasonably
speculate
that
thinking
style
is

1.14)
JC
Penny
2.40% having
a
very
large
impact
on
all
other

1.15)
Amazon
2.80% aspects
of
a
brand’s
messaging.

®

19

CASE
STUDY:
Enabling
effec9ve
self-‐ini9ated
global
collabora9on.
The
problem:

The
Chairman
had
fiKy-‐two
heads
flying
in
from
around
the
world,
the
top
bosses
of
his

global
divisions,
for
the
annual
pow-‐wow
of
the
global
brass.
The
issue
he
presented
to
us

was
as
follows.

While
each
and
every
one
of
these
highly
paid,
educated
and
experienced
individuals
was

performing
at
a
superla5ve
level,
there
was
a
lack
of
collabora5on
between
them
on
a
global

basis.
The
Chairman
of
the
Board
and
CEO
felt
that
his
‘team’
weren't
fully
apprecia5ng
the

value
each
could
bring
to
the
others
in
managing
their
divisions.
They
were
not

leveraging

opportuni5es
collabora5vely.
He
asked
if
we
could
help
raise
the
level
of
their
awareness
to

see
that
it
was
more
than
just
sales
opportuni5es
they
needed
to
share
with
each
other.
He

wanted
all
of
his
top
management
to
understand
that
there
was
huge
opportunity
in
sharing

their
knowledge
and
experience
from
the
point
of
view
of
their
thinking
style
driven

perspec5ves.

®

20

CASE
STUDY:
Enabling
eﬀec9ve
self-‐ini9ated
global
collabora9on.

Assessment
• We
asked
all
par5cipants
(56)
to
complete
the
GPS
for
the
Mind.
• We
also
captured
data
on
length
of
service,
posi5on
held,
we
also
asked
par5cipants
to
rank
their

peers
by
whom
they
spoke
to
most
frequently
(1st,
2nd,
3rd.)
• We
developed
a
series
of
maps
that
showed
the
overall
make-‐up
of
global
senior
management,

by
country,
by
frequency
(rank)
of
inter-‐personal
contact,
and
by
posi5on.

The
Solu.on:

Knowledge
Transfer
• We
designed
and
facilitated
a
half-‐day
workshop
delivered
in
Florida
at
their
annual
mee5ng.
• During
the
workshop
we
asked
all
par5cipants
to
list
at
least
three
instances
when
the
thinking

perspec5ve
they
were
most
resistant
to
(the
perspec5ve
they
had
the
least
of)
had
goQen
them

in
trouble.
• We
then
went
through
a
standard
presenta5on
of
MindTime
highligh5ng
the
role
of
the
thinking

perspec5ves
in
business
and
life.
• We
shared
the
maps
we
had
prepared
with
par5cipants
and
had
a
broad
and
open
discussion.
• Par5cipants
were
asked
to
work
in
groups
of
diverse
thinking
styles
sharing
their
three
failure

scenarios
and
listening
to
each
other’s
input.

®

21

CASE
STUDY:
Enabling
eﬀec9ve
self-‐ini9ated
global
collabora9on.

Results
• It
was
obvious
to
par5cipants
that
they
were
communica5ng
on
a
far
more
frequent
basis
with

peers
who
shared
their
own
perspec5ve.
• These
‘like
minded’
conversa5ons
were
more
in-‐depth
and
covered
a
broader
range
of

topics.
• Data
showed
that
geography
had
no
bearing
on
the
frequency
of
people’s

communica5on;
no
maQer
how
geographically
dispersed
from
one
another
they

discovered
they
had
been
reaching
out
to
peers
of
like
thinking
style.
• Par5cipants
overwhelmingly
reported
gaining
an
apprecia5on
for
how
others
saw
reported

situa5ons
and
how
nega5ve
impacts
might
have
been
avoided
if
a
broader
set
of
thinking
skills

being
applied
at
the
outset.
• Each
par5cipant
iden5ﬁed
four
individuals
in
the
group
who
held
a
perspec5ve
which
was
least

like
their
own.
Over
the
course
of
the
next
three
days
they
spent
“immersion”
5me
gemng
to

know
these
others
in
conversa5on
and
meals
together.
• An
overall
map
of
the
senior
management
team
revealed
that
there
was
no
imbalance
of

thinking
perspec5ves
across
the
group.
However,
the
Chairman
did
reveal
that
divisions
led
by

Future
thinkers
were
more
likely
to
have
erra5c
but
stunning
results,
while
those
led
by
Present

and
Past
leaders
had
beQer
long-‐term
and
more
consistent
successes.

®

22

CASE
STUDY:
Correla9ng
thinking
styles
with
Web
traﬃc
paIerns.
The
problem:

Who
are
all
of
these
people
really?
Is
there
not
a
beQer
way
to
understand
why
they
do
what

they
do
in
Web
sites?
Hundreds
of
millions
of
dollars
are
spent
developing
sophis5cated
Web

environments
with
only
the
most
primi5ve
models
of
human
behavior
being
used
to

understand
the
users
they
serve.

We
set
about
crea5ng
an
internal
case
study
to
explore
what
the
data
would
show
if
we
did

even
a
cursory
analysis
of
the
web
traﬃc
in
our
own
site.
The
results
are
very
encouraging

that
MindTime
will
provide
new
predic5ve
and
rela5onal
analy5c
capability
for
building

beQer
Web
experiences
for
users.

®

23

CASE
STUDY:
Correla9ng
thinking
styles
with
Web
traffic
paIerns.

Assessment
• We
asked
visitors
(222)
to
our
web
site
to
complete
the
GPS
for
the
Mind.
• We
used
Google
Analy5cs
custom
variable
fields
to
import
MindTime
data
into
Google
Analy5cs

applica5on.
• We
separated
the
data
into
the
ten
archetype
MindTime
model.
• We
then
ran
the
system
for
a
few
days
and
collected
the
data.
• Analysis
was
done
using
Google
Analy5cs
PlaWorm.

Parameters
• We
used
our
18
item
version
of
the
GPS
for
the
Mind
(a
9
item
version
is
available).
• Our
audience
tends
to
be
skewed
towards
Future
and
Future/Present
thinkers.
This
is
a
func5on

of
the
business
audience
who
traffics
our
site.

®

24

CASE
STUDY:
Correla9ng
thinking
styles
with
Web
traffic
paIerns.

NEW DATA

Analysis
• There
is
clear
behavioral
differen5a5on
between
thinking
styles.
• There
is
clear
difference
between
the
ten
archetypes
in
avg.
number
of
pages
visited,
avg.
5me

on
site,
and
the
bounce
rate.

®

25
CASE
STUDY:
Effec9ve
messaging
using
MindTime
audience
segmenta9on

The
Test
An
interna5onally
Telcom
brand
wanted
to
understand
how
well
two
compe5ng
sets
of
adver5sing
ideas
—one
designed
to
conform
with
MindTime
audience
segmenta5on
and
one
not—would
be
received
by

small
business
decision
makers
(10-‐100
employees)
in
the
USA.

Beyond
simply
wan5ng
to
understand
how
the
two
sets
of
compe5ng
ad
ideas
were
received—if
one
of

the
sets
of
ad
ideas
liKed
the
audience’s
sen5ments
on
specific
differen5a5ng
brand
aQributes
more

than
the
other—the
client
also
wanted
to
gain
insight
into
how
the
audience’s
thinking
was
being

influenced
by
the
ad
ideas
presented.
And,
they
wanted
to
know
why
the
ads
might
be

influencing’
(s5mula5ng
and
changing
percep5ons)
in
certain
kinds
of
people—driving
higher
sen5ment

responses—while
leaving
others
unaffected
by
the
ad
ideas—with
resul5ng
low
or
no
liK
in
sen5ment.

To
put
all
of
this
more
straighWorwardly.
The
brand
wanted
to
understand
how
targe5ng
people’s

thinking,
through
using
MindTime
audience
segmenta5on,
ad
design
and
messaging
principles,
can

influence
brand
sen5ment
and
behavioral
outcomes.

®

26
CASE
STUDY:
Effec9ve
messaging
using
MindTime
audience
segmenta9on

Our
hypothesis
• We
hypothesized
that
small
business
decision
makers
are
most
driven
by
Present
and
Future
thinking—
using
the
nomenclature
of
our
model.
Years
of
mapping
audiences
and
businesses
bears
this
hypothesis

out.
Thus
an
adver5sement
designed
with
the
needs
of
these
thinking
perspec5ves
in
mind
would
create

more
liK
in
the
targeted
audience
than
an
ad
not
specifically
designed
for
this
target
audience.
Research
design
• A
na5onal
market
research
firm
was
engaged
to
conduct
the
study,
this
included
recrui5ng
the
panel

audience
(specifically
filtering
for
small
business
decision
makers)
and
running
the
study.
• Six
adver5sement
ideas
were
prepared
by
the
adver5sing
agency
that
represents
the
brand.
All
ads

targeted
small
business
decision
makers.
Three
were
designed
with
no
thinking
style
bias
(“Calling
Card”

Concept
A).
Three
were
especially
designed
using
MindTime
design
principals
to
influence
Future
and

Present
thinkers
(“Outcomes”
Concept
B).
• 525
people
were
recruited
and
surveyed,
353
of
the
respondents
were
used
in
the
study
(not
all

conformed
with
the
client’s
desired
demographic
mix).
• The
panel
was
randomly
split
into
two
roughly
equal
groups.

• Respondents
in
both
groups
were
first
profiled
with
the
MindTime
profile,
then
both
groups
were
asked

to
react
to
11
brand
aQributes
that
were
deemed
to
be
of
importance.
• Half
the
respondents
were
then
shown
the
three
versions
of
the
‘MindTime
guided
design’
ad
idea

(Concept
B),
the
other
half
were
shown
the
non-‐MindTime
ad
idea
(Concept
A).
Having
seen
the

‘s5mulus’
material
they
were
all
asked
to
give
their
reac5on
again
to
the
same
11
brand
aQribute

ques5ons.
• An
8
point
Likert
scale
was
used
to
measure
par5cipants
responses
to
brand
aQribute
ques5ons.

®

27
CASE
STUDY:
Eﬀec9ve
messaging
using
MindTime
audience
segmenta9on
The
ad
concepts

Concept
A
“Calling
Card”

Client protection Client protection Client protection

Concept
B
“Outcomes”
Designed
using

MindTime
Design

Principals

Client protection Client protection Client protection

®

28
CASE
STUDY:
Eﬀec9ve
messaging
using
MindTime
audience
segmenta9on

The
research
panel
audience
composi9on

Pr

Pa Fu

®

29
CASE
STUDY:
Eﬀec9ve
messaging
using
MindTime
audience
segmenta9on

Visualiza9on
of
audience
li[
in
sen9ment
using
MindTime®
thermo
maps™

Increased
favorability
in
brand
aQribute
“Enables
the
Flexibility
I
want”
(concept
B)

Pr Pr

The
hypothesized
target
audience

of
small
business
decision
makers

Pa Fu Pa Fu

Pre Exposure Post Exposure

Intensity
and
size
of
popula5on
engaging
with
“Outcomes”
(Concept
B)
increased
drama5cally.

®

30
CASE
STUDY:
Eﬀec9ve
messaging
using
MindTime
audience
segmenta9on

How
much
did
thinking
style
drive
people’s
percep9ons?
Percent variance explained by thinking perspective on the 11 business related items both before (pre) and after (post) exposure to
Concept 1 and Concept 2.

Brand attribute measured Pre- Exposure to Concept Post-Exposure to Concept
Concept 1 Concept 2 Concept 1 Concept 2

Provides solutions for a business like mine .072 .050 .070 .076*

Is an advocate for my small business .065 .080* .035 .085*

Understands my priorities .054 .088* .048 .121*

Helps me realize new opportunities .086* .079* .065* .099*
Has the best selection .067 .065 .081* .086*

Recognizes my business objectives .064 .100* .056 .082*
Enables the flexibility want .066 .058 .056 .093*

Has quality products and services .057 .061 .049 .082*
Is a brand/company I trust .043 .059 .038 .042

Will be there for me. .063 .073 .035 .094*

Helps me feel confident .048 .071 .048 .088*

®

31
CASE
STUDY:
Effec9ve
messaging
using
MindTime
audience
segmenta9on

Charts
of
li[
by
thinking
style
(pre
and
post
ad
exposure)

Increased
favorability
in
brand
aQribute
“Enables
the
Flexibility
I
want”
(concept
B)

Enables the flexibility I want (Concept B) Enables the flexibility I want (Concept B)

Pre Post

The
hypothesized
target
audience
of
small
business
decision
makers

®

32
CASE
STUDY:
Ad
effec9veness
study
conducted
in
Germany,
France
and
North
America

Does
thinking
maIer?
While we all can readily understand how being a man or a woman, being young or older, or being rich or
poor might impact our decisions, it is perhaps not so immediately obvious how our thinking style affects
our perceptions and the choices we make.

In the following case study MindTime Technologies participated with a global ad planning company, a
global digital research company and a global advertising company to asses the degree to which
MindTime archetype was accounting for people’s behaviors in an advertising effectiveness study
conducted on behalf of a client in Germany, France and North America.

®

33
CASE
STUDY:
Ad
eﬀec9veness
study
conducted
in
Germany,
France
and
North
America

Methodology
Survey respondents were recruited online. They were divided into those who had
been exposed to the advertisement and those who had not (control group).
Opinions, intent, brand favorability, and thinking style were then measured in a
survey.
Respondents were segmented using MindTime’s 8 archetype model.

• Map shows distribution of audience sample of
1,500 (North America data) people who
participated in the study
• Target audience CTO/decision makers in start-ups
and small businesses
• Target thinking style presumed to be Past/Present

Target audience

®

34
CASE
STUDY:
Ad
eﬀec9veness
study
conducted
in
Germany,
France
and
North
America

Resonance
While the target audience was Past/Present in make up, the ads resonated
with Future thinkers, and did so very well. The ads were deemed to be oﬀ
market and were redesigned using MindTime design principals.

Ad target

Ad resonance

* Statistically significant difference between control and exposed group at a 90% confidence level
- Insufficient Sample for Reporting
®

35
CASE
STUDY:
Ad
eﬀec9veness
study
conducted
in
Germany,
France
and
North
America

Variance Explained in People’s Opinions (North American Data)

How$would$you$describe$your$overall$opinion$about$.net$
Propor6on$of$total$variance$explained$
Exposure,*0.00%*
Work*Status,*17.24%*

TimeStyle*
Age*
Gender*
Income*
Work*Status*
Income,*24.14%*
Exposure*

TimeStyle,*58.62%*

Age,*0.00%*
Gender,*0.00%*

• Total amount of people’s responses explained by all measured variables: 5.8%
• Of the above, thinking style explained: 58.62%
• The amount of people’s responses explained due to interactions between thinking style
and the other measured variables: 19.70%

®

36
CASE
STUDY:
Ad
eﬀec9veness
study
conducted
in
Germany,
France
and
North
America

Variance Explained in People’s Intent (North American Data)

The$next$(me$you$are$planning$to$register$a$website,$$
how$likely$are$you$to$consider$.net$
Propor(on$of$total$variance$explained$
Exposure,*2.67%*


TimeStyle,*41.33%*
TimeStyle*
Age*
Gender*
Income*
Work*Status*
Exposure*

Income,*22.67%*

Gender,*0.00%* Age,*12.00%*

• Total amount of people’s responses explained by measured variables: 7.5%
• Of the above, thinking style explained the following proportion: 41.33%
• The amount of people’s responses explained due to interactions between thinking style
and the other variables: 22.85%

®

37
CASE
STUDY:
Ad
eﬀec9veness
study
conducted
in
Germany,
France
and
North
America

Variance Explained in Brand Attributes (North America Data)

How$strongly$do$you$agree$that$.net$is$[brand$a5ribute]$
Propor9on$of$total$variance$explained$(average)$

Exposure,*20.22%*

TimeStyle,*35.96%*

TimeStyle*
Age*
Gender*
Income*
Work*Status*
Exposure*

Age,*6.74%*
Income,*24.72%* Gender,*2.25%*

• Total amount of people’s responses explained by measured variables: 8.9%.
• Of the above, thinking style explained the following proportion: 35.96%
• The amount of people’s responses explained due to interactions between
thinking style and the other variables: 9.61%

®

38

Try it . . .
Visit
our
mapping
site
to
learn
about
your
own
thinking
style
and

how
it
aﬀects
your
life— www.mindtimemaps.com

To
learn
more
about
business
opportuni5es,
contact:
John
Furey,
CEO
MindTime
Technologies
Inc.
john@mindtimetech.com

Thank
you.

®

MindTime case studies 1:12:12

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (19)

Andere mochten auch

Andere mochten auch (6)

Ähnlich wie MindTime case studies 1:12:12

Ähnlich wie MindTime case studies 1:12:12 (20)

MindTime case studies 1:12:12