Latest / Omni Talk Retail / Walmart Presses Its ‘Advantage,’ ALDI Recruits Teens & E.L.F. Goes Down A New Rhode | Fast Five

Transcript

Walmart Presses Its ‘Advantage,’ ALDI Recruits Teens & E.L.F. Goes Down A New Rhode | Fast Five · Omni Talk Retail

0:00
The
0:00
Omnich
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Fast
0:01
5
0:01
is
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brought
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to
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you
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by
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the
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A
0:02
and
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M
0:03
Consumer
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and
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Retail
0:04
Group.
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The
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A
0:05
and
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M
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Consumer
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and
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Retail
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Group
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is
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a
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management
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advances
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clients,
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people
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communities
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toward
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their
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CRG
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brings
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consumer
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companies
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Miracle,
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dropship
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media
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succeed.
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without
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lifting.
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holding
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you
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back?
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Visit
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Miracle.com
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to
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learn
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M
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I
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R
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A
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K
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L.com
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and
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Simbi
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Simbi
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powers
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the
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banners
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in
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the
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with
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today's
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only
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in
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store
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Albertsons,
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1:00
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@
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they
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unite
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1:04
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into
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a
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seamless,
1:05
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1:07
helps
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stay
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promise
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to
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delivery
1:10
and
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every
1:11
step
1:11
in
1:12
between.
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To
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learn
1:13
more,
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visit
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infios.com
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Clear
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Demand
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pricing
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shouldn't
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happen.
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more@cleardemand.com
1:32
omnitalk
1:33
and
1:33
finally,
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Ocampo
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Capital.
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Ocampo
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Capital
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is
1:36
a
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venture
1:36
capital
1:36
firm
1:37
founded
1:37
by
1:37
retail
1:38
executives
1:38
with
1:38
the
1:39
aim
1:39
of
1:39
helping
1:39
early
1:40
stage
1:40
consumer
1:40
businesses
1:41
succeed
1:41
through
1:42
investment
1:42
and
1:42
operational
1:43
support.
1:44
Learn
1:44
more@ocampo
1:45
capital.com
1:47
hello,
1:47
you're
1:48
listening
1:48
to.
1:48
Omnitalk's
1:49
Retail
1:49
Fast
1:50
Five
1:50
ranked
1:50
in
1:50
the
1:51
top
1:51
10%
1:51
of
1:51
all
1:51
podcasts
1:52
globally
1:52
and
1:53
currently
1:53
the
1:53
only
1:53
retail
1:54
podcast
1:54
ranked
1:55
in
1:55
the
1:55
top
1:55
100
1:55
of
1:56
all
1:56
business
1:56
podcasts
1:57
on
1:57
Apple
1:57
Podcasts.
1:58
The
1:58
Retail
1:59
Fast
1:59
Five
1:59
is
1:59
the
1:59
podcast
2:00
that
2:00
we
2:00
hope
2:00
makes
2:01
you
2:01
feel
2:01
a
2:01
little
2:02
smarter,
2:02
but
2:02
most
2:02
importantly,
2:03
a
2:03
little
2:03
happier
2:04
each
2:04
week
2:04
too.
2:05
And
2:05
the
2:05
Fast
2:05
5
2:06
is
2:06
just
2:06
one
2:06
of
2:06
the
2:06
many
2:07
great
2:07
podcasts
2:08
you
2:08
can
2:08
find
2:08
from
2:09
the
2:09
Omnitok
2:09
Retail
2:10
Podcast
2:10
Network
2:11
alongside
2:11
our
2:11
Retail
2:12
Daily
2:12
Minute,
2:13
which
2:13
brings
2:13
you
2:13
a
2:13
curated
2:14
selection
2:14
of
2:15
the
2:15
most
2:15
important
2:15
retail
2:16
headlines
2:16
every
2:16
morning
2:17
and
2:17
our
2:17
Retail
2:18
Technology
2:18
Spotlight
2:19
series,
2:19
which
2:19
goes
2:20
deep
2:20
each
2:20
week
2:20
on
2:21
the
2:21
latest
2:21
retail
2:22
technology
2:22
trends.
2:23
It's
2:23
June
2:24
4,
2:24
2025.
2:25
I'm
2:25
one
2:25
of
2:25
your
2:25
hosts,
2:26
Anne
2:26
Mazinga.
2:27
And
2:27
I'm
2:27
Chris
2:27
Walton,
2:28
and
2:28
we
2:28
are.
2:28
Here
2:29
once
2:29
again
2:29
to
2:29
discuss
2:30
all
2:30
the
2:30
top
2:30
headlines
2:31
from
2:31
the
2:31
past
2:31
Week
2:32
making
2:32
waves
2:32
in
2:33
the
2:33
world
2:33
of
2:33
omnichannel
2:34
retailing.
2:34
And,
2:35
Chris,
2:35
we
2:36
are
2:36
coming
2:36
to
2:36
you
2:37
live
2:37
from
2:37
Barcelona
2:38
for
2:38
Shop
2:39
Talk
2:39
Europe.
2:41
What's
2:41
been
2:41
your
2:42
best
2:42
moment?
2:43
What
2:44
best
2:44
thing
2:44
that
2:44
you've
2:45
learned
2:45
or
2:46
done
2:47
so
2:47
far
2:47
in
2:47
your
2:47
time
2:48
here
2:48
in
2:48
Espana?
2:50
Oh,
2:50
man.
2:50
There's
2:51
been
2:51
a
2:51
couple
2:51
standout
2:52
moments
2:52
for
2:52
me,
2:52
and
2:53
honestly,
2:54
both
2:54
of
2:54
them
2:54
have
2:54
very
2:55
little
2:55
to
2:55
do
2:55
with
2:55
retail.
2:56
One
2:56
of
2:56
them
2:56
has
2:56
to
2:56
do
2:57
with
2:57
our
2:57
podcast,
2:57
but
2:58
the
2:58
first
2:58
one
2:59
is
2:59
the
2:59
better
2:59
one,
2:59
which
2:59
is
3:00
we
3:00
were
3:00
at
3:00
dinner
3:01
the
3:01
other
3:01
night,
3:01
and.
3:04
We.
3:04
Were
3:04
listening
3:04
to
3:05
a
3:05
Swedish
3:05
person
3:05
regale
3:06
us
3:06
about
3:07
how
3:08
moose,
3:09
particularly
3:09
moose,
3:09
are
3:10
dangerous
3:10
to
3:10
drivers
3:11
in
3:11
Sweden.
3:11
And
3:11
not
3:12
for
3:12
the
3:12
reasons
3:12
you'd
3:12
expect,
3:13
I
3:13
guess.
3:14
When
3:14
you
3:14
hit
3:14
a
3:14
moose
3:15
in
3:15
Sweden,
3:16
what
3:16
can
3:16
happen
3:16
is
3:17
the
3:17
moose
3:17
can
3:17
go
3:17
on
3:18
the
3:18
top
3:18
of
3:18
your
3:18
car
3:19
and
3:19
that
3:19
it
3:20
contains
3:20
so
3:21
much
3:21
blood
3:21
that
3:22
people
3:22
actually
3:22
drown
3:23
and
3:23
die
3:24
from
3:24
the
3:24
blood
3:25
seeping
3:25
into
3:25
the
3:26
vehicle.
3:26
Yeah.
3:27
This
3:27
is
3:27
a
3:27
real
3:27
thing
3:28
that
3:28
happens
3:28
in
3:28
Sweden
3:29
that
3:29
you
3:29
and
3:29
I
3:29
were
3:29
unaware
3:30
of.
3:30
And
3:30
it's
3:30
become
3:30
the
3:31
running
3:31
joke
3:31
of
3:32
the
3:32
show
3:32
amongst
3:32
all
3:33
of
3:33
us
3:33
and
3:33
our
3:33
friends
3:34
at
3:34
Shop
3:34
Stock.
3:34
So
3:35
drive
3:35
through
3:35
any
3:36
animal
3:36
if
3:37
you're
3:37
driving,
3:37
except
3:38
for
3:38
a
3:38
moose,
3:39
you
3:39
stop
3:39
for
3:39
the
3:40
moose,
3:40
because
3:40
you
3:40
can
3:40
drown
3:41
in
3:41
moose
3:41
blood.
3:42
The
3:42
more
3:42
you
3:42
know,
3:42
Omnitok
3:43
retail
3:44
fans,
3:44
the
3:44
more
3:45
you
3:45
know.
3:47
Yeah.
3:48
What
3:49
was
3:49
the
3:49
other
3:49
thing?
3:50
The
3:50
other
3:50
one
3:50
was.
3:51
I
3:51
was
3:51
sitting.
3:51
I
3:51
was
3:51
talking
3:52
to
3:52
Rachel.
3:52
We
3:52
were.
3:52
I
3:53
was
3:53
at
3:53
a
3:53
table
3:53
yesterday
3:54
getting
3:54
ready
3:54
for
3:55
doing
3:55
some
3:55
work,
3:56
and
3:56
I
3:56
was
3:56
sitting
3:56
at
3:56
a
3:56
table
3:57
with
3:57
people
3:57
getting
3:57
ready
3:57
to
3:57
go
3:58
on
3:58
stage,
3:58
and.
3:58
And
3:59
I
3:59
was
3:59
sitting
3:59
next
3:59
to
3:59
Rachel,
3:59
tippograph
4:00
of
4:00
Mick
4:00
Mac.
4:01
And
4:01
I
4:01
was
4:01
just
4:02
talking
4:02
to
4:02
her,
4:03
and.
4:03
And
4:03
there's
4:04
a
4:04
woman
4:04
next
4:04
to
4:04
me,
4:04
but
4:05
she
4:05
couldn't
4:05
see
4:05
my
4:05
badge.
4:05
My
4:06
badge
4:06
was,
4:06
like,
4:06
under
4:06
the
4:06
table.
4:07
She
4:07
couldn't
4:07
see
4:07
who
4:07
I
4:07
was.
4:08
And
4:08
she's
4:08
like,
4:09
wait,
4:09
do
4:09
you
4:09
do
4:09
a
4:10
podcast?
4:10
And
4:10
I'm
4:10
like,
4:11
yes,
4:11
I
4:12
do.
4:12
And
4:12
she's
4:13
like,
4:13
I
4:13
recognize
4:14
your
4:14
voice.
4:14
And
4:15
I
4:15
was
4:15
like,
4:15
wow,
4:16
that's
4:17
so
4:17
great.
4:17
I've
4:18
never
4:18
heard
4:18
that
4:18
before.
4:19
You
4:19
know,
4:19
usually
4:19
we
4:19
get,
4:19
like,
4:20
in
4:20
the
4:20
elevator,
4:20
we'll
4:20
be
4:21
like,
4:21
hey,
4:21
why
4:21
do
4:22
I
4:22
know
4:22
you?
4:22
Like,
4:22
have
4:22
I
4:23
seen
4:23
you
4:23
on
4:23
social
4:23
media?
4:24
I've
4:24
never
4:24
gotten.
4:25
I
4:25
recognized
4:26
your
4:26
voice.
4:27
I
4:27
don't
4:27
know
4:27
if
4:27
that's
4:27
a
4:27
good
4:28
thing
4:28
or
4:28
a
4:29
bad
4:29
thing.
4:29
I
4:30
think
4:30
you
4:30
make
4:30
it.
4:30
You
4:31
make
4:31
it
4:31
whatever
4:31
you
4:31
want,
4:31
Chris.
4:32
Yeah.
4:32
She
4:32
called
4:33
out.
4:33
She's
4:33
like,
4:33
did
4:33
you
4:33
guys
4:34
do
4:34
the
4:34
podcast
4:34
on.
4:35
On
4:35
ev
4:35
charging
4:36
at
4:36
convenience
4:36
stores?
4:37
I
4:37
was
4:37
like,
4:37
yes,
4:37
we
4:37
did.
4:38
You
4:38
know,
4:38
we
4:38
talk
4:38
about
4:39
all
4:39
kinds
4:39
of
4:39
stuff.
4:39
And
4:39
she's
4:40
like,
4:40
yeah,
4:40
I
4:40
listen
4:40
to
4:40
you
4:40
guys
4:40
regularly.
4:41
I
4:41
love
4:41
the
4:41
shorts.
4:42
She
4:42
loves
4:42
how
4:42
we
4:42
clip
4:43
it
4:43
out
4:43
too.
4:43
So
4:43
our
4:44
Fast
4:44
5
4:44
shorts,
4:44
for
4:44
those
4:44
that,
4:45
you
4:45
know,
4:45
don't
4:45
want
4:46
to
4:46
listen
4:46
to
4:46
the
4:46
whole
4:47
episode.
4:47
You
4:47
can
4:47
just
4:48
take
4:48
what
4:48
you
4:48
want
4:49
because
4:49
she
4:49
said,
4:50
you
4:50
know,
4:50
you
4:50
know,
4:50
sometimes
4:51
there's
4:51
topics,
4:51
you
4:51
know,
4:51
that
4:52
I'm
4:52
not
4:52
interested
4:52
in
4:53
shorts.
4:53
Just
4:53
let
4:53
me
4:54
get
4:54
right
4:54
to
4:54
the
4:54
point.
4:55
So,
4:55
yeah,
4:55
so
4:55
I
4:55
thought
4:55
that
4:56
was
4:56
cool.
4:56
Man.
4:56
That
4:57
is
4:57
so
4:57
cool,
4:57
Chris.
4:57
So
4:58
did
4:58
you
4:58
get
4:58
her
4:58
name?
4:59
Like,
4:59
do
4:59
you
4:59
know
4:59
who
4:59
this.
5:00
Yeah,
5:00
yeah,
5:00
for
5:00
sure.
5:00
Yeah.
5:01
No,
5:01
yeah,
5:01
I
5:01
should,
5:01
should.
5:02
I
5:02
meant
5:02
to
5:02
shout
5:02
out
5:02
her
5:03
name.
5:03
It's
5:03
Jillian
5:04
from
5:04
Deloitte.
5:04
Yeah,
5:05
Jillian
5:05
from
5:05
Deloitte.
5:06
So
5:06
shout
5:06
out
5:06
to
5:06
Jillian.
5:06
Hope
5:07
she's
5:07
listening.
5:07
She's
5:07
probably
5:08
not.
5:08
She's
5:08
probably
5:08
just
5:08
listening
5:09
to
5:09
the
5:09
shorts.
5:09
We
5:09
don't
5:10
do
5:10
the
5:10
intro
5:10
in
5:10
the
5:10
shorts,
5:11
but.
5:12
But
5:12
who
5:12
knows?
5:12
But
5:12
yeah,
5:13
so,
5:13
yeah,
5:13
so
5:13
shout
5:13
out
5:13
to
5:14
Jillian.
5:14
So,
5:14
yeah,
5:15
it's
5:15
been
5:15
a
5:15
fun
5:15
week
5:15
so
5:16
far.
5:16
It's
5:16
been
5:16
a
5:16
good,
5:16
good,
5:16
good
5:17
conference
5:17
and
5:18
we
5:18
got
5:18
a
5:18
lot
5:18
of
5:18
interesting
5:19
headlines.
5:19
So
5:19
should
5:20
we
5:20
get
5:20
to
5:20
it?
5:20
Let's
5:20
see.
5:21
Do
5:21
it.
5:22
All
5:22
right.
5:22
In
5:22
this
5:22
week's
5:23
Fast5,
5:23
we've
5:23
got
5:23
news
5:24
on
5:24
Elf's
5:24
acquisition
5:25
of
5:25
Haley
5:26
Bieber's
5:26
beauty
5:26
brand
5:27
for
5:27
a
5:27
billion
5:28
dollars.
5:28
That's
5:29
billion
5:29
with
5:29
a
5:29
b.
5:30
Billion
5:30
dollar
5:31
Bieber.
5:32
Billion
5:32
dollar
5:32
Bieber.
5:33
Ooh,
5:33
I
5:33
like
5:33
what
5:33
you
5:33
did
5:33
there.
5:34
I
5:34
know,
5:34
I
5:34
know.
5:35
That
5:35
was,
5:35
that
5:35
was.
5:36
That
5:36
was
5:36
cool.
5:36
All
5:36
right.
5:37
Victoria's
5:37
Secret's
5:38
website
5:38
shut
5:38
down
5:39
last
5:39
week.
5:40
Aldi's
5:40
new
5:41
digital
5:41
work
5:41
experience
5:42
program
5:42
for
5:43
teens
5:43
in
5:43
the
5:43
uk,
5:44
David
5:45
Bridle's
5:45
new
5:45
store
5:46
concept,
5:46
Diamonds
5:47
and
5:47
Pearls.
5:48
And
5:48
Infios's
5:49
Eugene
5:49
Amood
5:50
stops
5:50
by
5:50
for
5:51
five
5:51
insightful
5:52
min.
5:53
How
5:53
AI
5:54
will
5:54
impact
5:54
order
5:55
management
5:55
systems
5:56
in
5:56
the
5:56
future.
5:56
A
5:57
topic
5:57
that
5:57
is
5:58
near
5:58
and
5:58
dear
5:58
to
5:58
the
5:59
retail
5:59
geek
6:00
in
6:00
me.
6:01
All
6:01
right,
6:01
but
6:01
we
6:01
begin
6:02
today
6:02
with
6:02
news
6:03
on
6:03
a
6:03
trend
6:03
we
6:03
are
6:03
hearing
6:04
more
6:04
and
6:04
more
6:04
about
6:05
every
6:05
week.
6:06
Food
6:06
as
6:06
medicine.
6:07
Ann.
6:08
Chris.
6:08
Headline
6:09
number
6:09
one
6:09
is
6:10
exactly
6:10
that.
6:11
Walmart
6:12
has
6:12
introduced
6:12
a
6:13
virtual
6:13
badge
6:14
to
6:14
help
6:14
Medicare
6:14
Advantage
6:15
Advantage
6:16
members
6:16
identify
6:17
items
6:17
they
6:17
can
6:17
buy
6:18
with
6:18
their
6:18
OTC
6:19
benefits.
6:19
According
6:20
to
6:20
Retail
6:20
Dive,
6:21
people
6:21
can
6:21
add
6:21
their
6:22
benefit
6:22
cards
6:22
to
6:22
their
6:22
virtual
6:23
Walmart
6:23
wallets
6:24
to
6:24
access
6:25
a
6:25
digital
6:25
experience
6:26
that
6:26
includes
6:26
a
6:26
product
6:27
badge
6:27
and
6:27
search
6:28
filter
6:28
to
6:28
identify
6:29
items
6:30
that
6:30
are
6:30
eligible
6:31
for
6:31
those
6:31
benefits
6:32
when
6:32
shopping
6:32
in
6:33
stores.
6:33
The
6:33
badge
6:33
will
6:33
appear
6:34
when
6:34
people
6:34
scan
6:35
eligible
6:35
items
6:36
barcodes
6:36
with
6:36
the
6:36
Walmart
6:37
app,
6:37
the
6:38
retailer's
6:39
Quote
6:39
Benefits
6:40
program
6:41
eligible
6:42
badge
6:43
appears
6:43
on
6:43
a
6:44
wide
6:44
variety
6:44
of
6:44
over
6:45
the
6:45
counter
6:45
food
6:45
and
6:46
wellness
6:46
products
6:46
such
6:47
as
6:47
meal
6:47
replacement
6:48
shakes,
6:48
ground
6:48
coffee,
6:49
vitamins,
6:50
and
6:50
cold
6:51
and
6:51
flu
6:51
medication.
6:52
Customers
6:53
can
6:53
also
6:53
access
6:53
a
6:54
tracker
6:54
that
6:54
lets
6:55
them
6:55
monitor
6:55
their
6:55
unused
6:56
benefits.
6:57
Walmart
6:57
said
6:58
the
6:58
Everyday
6:58
Health
6:58
Signals
6:59
platform
7:00
can
7:00
enhance
7:01
the
7:01
well
7:01
being
7:01
of
7:02
Medicare
7:02
Advantage
7:03
customers
7:03
by
7:03
providing
7:04
information
7:04
that
7:05
can
7:05
help
7:05
them
7:05
make
7:05
healthier
7:06
choices
7:06
by
7:07
analyzing
7:07
their
7:07
Walmart
7:08
purchases.
7:08
The
7:08
AI
7:09
powered
7:09
tool
7:09
can
7:10
provide
7:10
the
7:10
customer
7:10
with
7:11
the
7:11
nutrition
7:11
analysis
7:12
and
7:13
shopping
7:13
list.
7:13
Chris,
7:14
this
7:14
is
7:14
also
7:14
the
7:15
A
7:15
and
7:15
M
7:15
put
7:15
you
7:15
on
7:16
the
7:16
spot
7:16
right
7:16
away
7:16
here
7:17
bright
7:17
and
7:17
early
7:18
in
7:18
Barcelona.
7:19
A
7:19
and
7:19
M
7:20
wants
7:20
to
7:20
know
7:20
on.
7:21
Three
7:21
hours
7:21
of
7:21
sleep
7:21
in
7:22
Barcelona.
7:22
Yes,
7:22
let's
7:22
start
7:23
off
7:23
hot.
7:23
Yes.
7:25
A
7:25
and
7:25
M
7:25
says
7:26
we
7:26
recognize
7:26
and
7:27
applaud
7:27
Walmart's
7:27
efforts
7:28
to
7:28
help
7:28
Medicare
7:29
members
7:29
reduce
7:30
the
7:30
billions
7:30
of
7:30
dollars
7:31
of
7:31
their
7:31
annually
7:31
forfeited
7:32
over
7:32
the
7:32
counter
7:33
benefits.
7:33
Given
7:34
this
7:34
is
7:34
a
7:34
digital
7:35
only
7:35
virtual
7:36
wallet
7:36
and
7:37
barcode
7:37
scanning
7:38
discovery
7:39
process.
7:39
Is
7:40
the
7:40
overlap
7:40
big
7:41
enough
7:41
to
7:41
big
7:42
enough
7:42
yet
7:42
between
7:43
Medicare
7:43
members
7:43
and
7:44
digital
7:44
savviness
7:45
to
7:45
meaningfully
7:46
succeed
7:46
in
7:47
this
7:47
effort?
7:47
What
7:48
a
7:48
beautifully
7:48
worded
7:49
question.
7:49
And
7:50
now
7:50
I'll
7:51
let
7:51
you
7:51
take
7:52
take
7:52
the
7:52
stage
7:53
and
7:54
provide
7:54
an
7:54
answer.
7:55
Yeah,
7:56
thank
7:56
you
7:56
and
7:56
thank
7:57
you.
7:57
That's
7:57
so
7:57
kind
7:57
of
7:58
you.
7:59
So
7:59
yeah,
7:59
I
7:59
mean
7:59
my
8:00
answer
8:00
to
8:00
that
8:00
question
8:00
is
8:01
yes,
8:02
yes
8:02
it
8:02
does.
8:03
I
8:03
think
8:03
it
8:04
will
8:04
be
8:04
meaningful.
8:04
And
8:05
the
8:05
reason
8:05
I
8:05
say
8:05
that
8:05
from
8:06
Walmart's
8:06
perspective,
8:07
because
8:07
the
8:08
bar
8:08
is
8:08
incredibly
8:09
low.
8:09
All
8:10
you're
8:10
talking
8:10
about
8:10
here
8:10
is
8:11
software.
8:11
You're
8:11
deploying
8:12
software.
8:12
So
8:12
any
8:13
usage
8:13
you
8:13
get
8:13
on
8:13
this
8:14
is
8:14
gravy.
8:15
And
8:16
the
8:16
cost
8:16
of
8:16
trying
8:16
to
8:16
do
8:17
this
8:17
imagine
8:18
is
8:18
not
8:18
prohibitively
8:19
expensive.
8:20
And
8:21
the
8:21
upside
8:21
if
8:22
you
8:22
get
8:22
people
8:22
to
8:23
use
8:23
it
8:23
is
8:24
incredibly
8:25
credibly
8:25
high.
8:26
And
8:26
digital
8:26
wallets,
8:27
while,
8:27
while
8:27
still
8:28
new
8:28
for
8:28
some,
8:28
are,
8:28
you
8:29
know,
8:29
gaining
8:29
more
8:29
and
8:30
more
8:30
traction
8:30
each
8:30
and
8:30
every
8:30
day.
8:31
So
8:31
that's
8:31
why
8:31
I
8:31
laud
8:32
this
8:32
move
8:32
because
8:32
it's
8:33
a
8:33
trend
8:33
we
8:33
talked
8:33
about.
8:34
You
8:34
know,
8:34
I
8:34
said
8:34
at
8:35
the
8:35
outset
8:35
food
8:36
is
8:36
medicine
8:36
that
8:36
we're
8:37
only
8:37
going
8:37
to
8:37
hear
8:37
more
8:37
about
8:38
because
8:39
the
8:39
number
8:39
one
8:39
answer
8:40
to
8:40
everything
8:40
and
8:41
everything
8:41
in
8:41
the
8:41
world
8:42
is
8:42
money.
8:43
And
8:43
there's
8:43
a
8:43
lot
8:43
of
8:44
money
8:44
to
8:45
be
8:45
claimed
8:45
for
8:45
programs
8:46
like
8:46
these
8:47
that
8:47
is
8:47
just
8:48
going
8:48
unused
8:49
quite
8:49
frankly.
8:49
So
8:50
and
8:50
I've
8:50
been
8:50
talking
8:50
to
8:50
a
8:51
lot
8:51
of
8:51
companies
8:51
recently.
8:52
I've
8:52
been
8:52
talking
8:52
to
8:52
I
8:52
spending,
8:53
I've
8:53
actually
8:53
been
8:53
spending.
8:54
It's
8:54
funny
8:54
this
8:54
headline
8:54
came
8:55
up
8:55
because
8:55
I've
8:55
been
8:55
spending
8:55
a
8:55
lot
8:55
of
8:55
time
8:56
with
8:56
a
8:56
company
8:56
called
8:56
Sifter
8:57
Price
8:57
spent
8:57
four
8:58
hours
8:58
with
8:58
them
8:58
in
8:58
the
8:58
last
8:59
month
9:00
just
9:00
talking
9:00
about
9:01
this
9:01
topic.
9:02
And
9:02
they're
9:02
a
9:02
company
9:02
that
9:03
helps
9:03
retailers
9:03
identify
9:04
items
9:05
based
9:05
on
9:05
their
9:05
nutritional
9:07
ingredients
9:08
and
9:08
everything.
9:09
And
9:09
so
9:10
we
9:10
were
9:10
talking
9:10
about
9:10
like
9:11
this
9:11
similar
9:11
use
9:11
case
9:12
for
9:12
GLP1,
9:12
like
9:13
how
9:13
do
9:13
you
9:13
help
9:14
customers
9:14
identify
9:15
GLP1
9:16
friendly
9:16
items
9:17
very
9:17
quickly
9:17
and
9:17
there's
9:18
a
9:18
merchandising
9:18
use
9:18
case
9:19
in
9:19
that.
9:19
So
9:20
the
9:21
last
9:21
part
9:21
I'd
9:21
say
9:21
is
9:22
I
9:22
just
9:23
love
9:23
this
9:23
too
9:23
because
9:23
it
9:24
a
9:24
hundred
9:24
percent
9:24
aligns
9:25
with
9:25
Walmart's
9:25
brand
9:26
promise
9:26
of
9:27
save
9:27
money,
9:28
live
9:28
better
9:29
and
9:29
that's
9:30
what
9:30
the
9:30
world
9:30
needs
9:31
is
9:31
right
9:31
now.
9:31
And
9:32
so
9:32
I,
9:33
I
9:33
just
9:33
can't
9:33
do
9:34
anything
9:34
but
9:34
applaud
9:34
this.
9:34
I
9:35
think,
9:35
I
9:35
think
9:35
it's
9:35
a
9:35
great
9:35
move
9:36
and
9:36
they're
9:36
just
9:36
going
9:36
to
9:36
learn
9:37
from
9:37
doing
9:37
it
9:37
too.
9:37
That's
9:38
the
9:38
other
9:38
thing.
9:38
So
9:38
like
9:39
there's,
9:39
there's
9:39
no
9:39
risk
9:40
here.
9:40
Yeah,
9:41
no,
9:41
I,
9:41
I
9:41
agree.
9:42
I
9:42
think
9:42
it's
9:42
really
9:43
smart.
9:43
I
9:43
think
9:44
you,
9:44
you're,
9:44
you
9:45
hit
9:45
on
9:45
it
9:45
right
9:45
at
9:45
the
9:45
beginning
9:46
when
9:46
you
9:46
said
9:46
like
9:46
it's
9:47
all,
9:47
there's
9:47
only
9:48
benefit
9:48
that
9:48
comes
9:49
from
9:49
this.
9:49
Sure
9:50
they
9:50
might
9:50
not
9:50
see
9:51
the
9:51
adoption
9:51
early
9:52
on
9:52
that
9:52
they
9:52
were
9:52
hoping,
9:53
but
9:53
it
9:53
puts
9:53
them
9:53
in
9:53
a
9:54
really
9:54
good
9:54
position
9:55
to
9:55
be
9:56
prepared
9:56
for
9:56
even
9:57
the
9:57
next
9:57
generation,
9:58
which
9:58
may
9:58
be
9:58
in
9:59
a
9:59
year
9:59
or
9:59
two.
9:59
Even
10:00
where
10:00
people
10:01
are
10:01
starting
10:01
to
10:02
use
10:02
an
10:02
app
10:02
based
10:03
platform
10:04
to
10:04
do
10:04
shopping,
10:05
especially,
10:07
especially
10:07
as
10:08
search
10:08
behaviors
10:08
are
10:09
changing.
10:09
I
10:09
think
10:10
yes,
10:10
they
10:10
may
10:11
not
10:11
start
10:11
to
10:11
ad
10:12
some
10:12
of
10:12
the
10:13
apps
10:13
right
10:13
away
10:13
but
10:14
if
10:14
Walmart's
10:15
thinking
10:15
about
10:15
this
10:15
now,
10:16
it's
10:16
not
10:16
only
10:16
valuable
10:17
to
10:17
them,
10:17
I
10:18
think
10:18
in
10:19
an
10:19
app,
10:19
but
10:19
it
10:19
also
10:20
helps
10:20
their
10:21
ecosystem
10:21
prepare
10:22
for
10:23
searches
10:23
like
10:24
the
10:24
ones
10:24
you're
10:24
talking
10:24
about
10:25
where
10:25
people
10:25
are
10:25
saying
10:26
are
10:26
there
10:26
products
10:27
that
10:27
qualify
10:27
for
10:27
Medicare
10:28
Advantage
10:28
and
10:29
can
10:29
you
10:29
build
10:29
me
10:29
a
10:29
shopping
10:30
list
10:30
and
10:30
a
10:30
meal
10:31
planning
10:31
tool
10:32
for
10:32
the
10:32
week
10:32
that
10:33
includes
10:33
those
10:33
products?
10:33
Like
10:34
that's
10:34
a
10:35
very
10:35
real
10:35
search
10:36
term
10:36
that
10:36
anyone
10:37
could
10:37
be
10:37
searching
10:37
on
10:38
Walmart
10:38
right
10:38
now.
10:38
And
10:39
so
10:39
I
10:39
think
10:39
it's
10:39
natural,
10:40
the
10:40
natural
10:40
progression
10:41
is
10:42
yes,
10:42
now
10:42
you
10:42
go
10:42
to
10:42
the
10:43
Walmart
10:43
app
10:43
to
10:44
fulfill
10:44
that
10:44
shopping
10:45
journey.
10:46
And
10:46
finally
10:46
I
10:46
think
10:47
this
10:47
is
10:47
also
10:47
something
10:48
I
10:48
imagine
10:48
that
10:49
they
10:49
could
10:49
start
10:49
to
10:49
put
10:49
on
10:50
the
10:50
digital
10:50
shelf
10:50
labels
10:51
that
10:51
they're
10:51
going
10:51
to
10:51
be
10:51
rolling
10:52
out
10:52
soon
10:52
too.
10:52
Like
10:53
there's
10:54
a
10:54
place
10:54
there
10:54
where
10:55
potentially
10:55
they
10:55
could
10:56
be
10:56
putting
10:56
some
10:56
of
10:56
this
10:56
information.
10:57
I
10:57
know
10:57
they've
10:58
already
10:58
started
10:58
to
10:58
do
10:58
this
10:58
with
10:59
promos
10:59
or
11:00
even
11:00
snap
11:00
an
11:01
EBT
11:01
eligible
11:01
items.
11:02
So
11:02
I
11:02
think
11:02
there's
11:03
a
11:03
state
11:03
where
11:04
this
11:04
could
11:04
go.
11:05
And
11:05
so
11:06
the
11:06
key
11:07
point
11:07
here
11:07
is
11:08
they're
11:08
preparing
11:08
about
11:09
it,
11:09
they're
11:09
thinking
11:10
about
11:10
it
11:10
right
11:10
now
11:11
and
11:11
retailers
11:12
around
11:12
the
11:12
globe
11:13
should
11:13
really
11:13
be,
11:13
be
11:13
paying
11:14
attention
11:14
to
11:14
thinking
11:15
about
11:15
their
11:15
own
11:15
investments
11:16
here
11:17
in
11:17
this
11:17
type
11:18
of
11:18
data
11:18
about
11:19
the
11:19
products.
11:20
It's
11:20
now
11:20
no
11:21
longer
11:21
just
11:21
about
11:22
ingredients
11:22
anymore.
11:23
It's
11:23
about
11:23
the
11:24
other,
11:24
the
11:25
other
11:25
queries
11:25
that
11:26
will
11:26
be
11:26
coming
11:26
up
11:26
or
11:27
how
11:27
people
11:27
are
11:27
going
11:27
to
11:27
Be
11:27
searching
11:28
for
11:28
the
11:28
products.
11:29
Yeah,
11:29
no,
11:30
it's
11:30
a
11:30
great
11:30
point.
11:30
It's
11:30
about,
11:30
it
11:31
comes
11:31
back
11:31
to
11:31
item
11:31
data
11:31
and
11:31
getting
11:32
your
11:32
item
11:32
data
11:33
cataloged,
11:33
you
11:34
know,
11:34
in
11:34
similar
11:34
ways
11:35
like
11:35
this.
11:35
Because
11:35
you're
11:35
right.
11:35
Yeah.
11:36
I
11:36
mean,
11:36
ChatGPT's
11:37
usage
11:37
rates
11:38
are
11:38
through
11:38
the
11:38
roof
11:39
and
11:39
people
11:39
are
11:39
going
11:39
to
11:39
start
11:39
doing
11:40
searches
11:40
like
11:40
that,
11:41
whether
11:41
it's
11:41
on
11:41
Walmart
11:42
or
11:42
through,
11:42
through
11:43
the
11:43
generative
11:44
AI
11:44
interfaces.
11:45
The
11:45
other
11:45
point
11:45
I'd
11:46
make
11:46
in
11:46
closing
11:46
too,
11:46
and
11:47
we've
11:47
talked
11:47
a
11:47
lot
11:47
on
11:47
the
11:47
show
11:48
about,
11:48
you
11:48
know,
11:48
like
11:48
investments
11:49
in
11:49
in
11:49
store
11:49
clinics
11:50
and
11:50
things
11:50
like
11:50
that,
11:51
you
11:51
know,
11:51
I
11:51
think
11:52
this
11:52
is
11:52
a
11:52
much
11:52
simpler
11:53
way
11:53
to
11:53
go
11:53
about
11:53
it
11:54
and
11:54
to
11:54
make
11:54
a
11:54
palpably
11:55
diff,
11:55
you
11:55
know,
11:56
meaningful
11:56
difference
11:57
in
11:57
people's
11:57
lives,
11:58
relatively
11:58
speaking
11:59
too.
11:59
So
11:59
I
11:59
think,
12:00
you
12:00
know,
12:00
it's,
12:00
it's
12:00
smart.
12:01
I
12:01
think
12:01
we're
12:01
going
12:01
to
12:01
see
12:01
more
12:01
people
12:02
jumping
12:02
on
12:02
this
12:02
bandwagon.
12:03
Yeah,
12:04
that
12:04
makes
12:04
a
12:04
lot
12:05
of
12:05
sense.
12:05
I
12:05
hadn't
12:05
even
12:05
thought
12:06
about
12:06
that.
12:06
But
12:06
you're
12:06
absolutely
12:07
right.
12:07
Like
12:07
it's
12:07
a
12:07
way
12:07
that
12:08
they
12:08
can
12:09
get
12:09
back
12:09
to
12:09
your
12:09
live
12:10
better
12:10
part
12:10
of
12:10
their,
12:11
their
12:11
promise.
12:13
Yeah.
12:13
And
12:13
you
12:13
don't
12:13
have
12:13
to
12:13
spend
12:14
any
12:14
money
12:14
on
12:14
physical
12:14
infrastructure
12:15
to
12:15
make
12:15
this
12:16
happen,
12:16
you
12:16
know,
12:17
as
12:17
well,
12:17
which
12:17
is,
12:17
you
12:18
know,
12:18
a
12:18
very,
12:18
very
12:20
enticing
12:20
way
12:21
to
12:21
think
12:21
about,
12:21
you
12:22
know,
12:22
how
12:22
do
12:22
you
12:22
capture
12:22
the
12:22
money
12:23
from,
12:23
you
12:24
know,
12:24
that's
12:24
going
12:24
around
12:24
in
12:25
the
12:25
healthcare
12:25
and
12:25
the
12:25
food
12:26
is
12:26
medicine
12:26
trend.
12:27
All
12:27
right,
12:27
headline
12:27
number
12:28
two,
12:28
ELF
12:29
Beauty.
12:29
Last
12:29
week,
12:30
I
12:30
can't
12:30
wait
12:30
to
12:30
get
12:30
your
12:30
thoughts
12:31
on
12:31
this.
12:31
Agreed
12:31
to
12:31
buy
12:32
Haley
12:32
Bieber's
12:33
road,
12:34
which
12:34
I
12:34
had
12:34
to
12:34
ask.
12:35
And
12:35
how
12:35
you,
12:35
how
12:36
you
12:36
actually
12:36
say
12:36
that?
12:36
Because
12:37
it's
12:37
R
12:37
H
12:37
O
12:38
D
12:38
E
12:39
whose
12:39
trademark
12:40
look
12:40
is
12:40
its
12:41
glossy
12:41
dewy
12:42
skin,
12:43
AKA
12:43
glazed
12:44
donut.
12:45
Also
12:45
something
12:45
I
12:46
had
12:46
to
12:46
ask
12:46
Ann
12:46
about
12:47
that
12:47
I
12:47
learned
12:47
from
12:47
you
12:48
yesterday.
12:48
So
12:49
for
12:49
and
12:49
they
12:49
acquired
12:50
it
12:50
for
12:50
$1
12:51
billion.
12:51
Again,
12:52
according
12:52
to
12:52
Bloomberg
12:53
in
12:53
RDE,
12:53
Elf
12:54
is
12:54
betting
12:54
on
12:54
a
12:54
premium
12:55
range
12:56
containing
12:56
just
12:56
10
12:57
main
12:57
or
12:57
hero
12:57
products
12:58
including
12:59
Pocket
12:59
blush
13:00
and
13:00
Glazing
13:00
milk,
13:01
which
13:01
blur
13:02
the
13:02
boundaries
13:02
between
13:03
skincare
13:04
and
13:04
makeup.
13:05
This
13:05
looks,
13:06
this
13:06
looks
13:07
like
13:07
a
13:07
good
13:07
fit
13:07
with
13:08
Elf
13:08
selection,
13:08
which
13:09
is
13:09
more
13:09
focused
13:09
on
13:10
cosmetics
13:10
and
13:10
is
13:11
cheaper.
13:11
For
13:11
example,
13:11
Elf's
13:12
average
13:12
price
13:12
point
13:13
is
13:13
about
13:13
$6.50.
13:14
Anne,
13:15
I
13:15
didn't
13:15
know
13:15
that.
13:16
Compared
13:16
with
13:16
almost
13:17
$9.50
13:18
for
13:18
mass
13:19
market
13:19
cosmetics
13:20
brand.
13:21
Whereas
13:21
Rhodes
13:22
average
13:22
is
13:23
about
13:23
$29.
13:24
So
13:24
a
13:24
significant
13:25
increase.
13:26
But
13:26
Elf
13:26
is
13:26
also
13:27
paying
13:27
a
13:27
pretty
13:28
polished
13:28
price
13:29
for
13:29
Rode,
13:30
also
13:30
known
13:30
for
13:30
its
13:31
sleek
13:31
minimal
13:31
package.
13:32
I
13:32
can't
13:32
take
13:32
credit
13:32
for
13:32
that.
13:33
I
13:33
got
13:33
to
13:33
give
13:33
credit
13:33
to
13:33
Bloomberg
13:34
for
13:34
that
13:34
one.
13:35
The
13:35
$800
13:35
million
13:36
in
13:36
cash
13:36
and
13:37
stock
13:37
payable
13:37
at
13:37
the
13:37
close
13:38
of
13:38
the
13:38
deal
13:38
expected
13:38
before
13:39
September
13:39
equates
13:40
to
13:40
a
13:40
3.8
13:41
times
13:42
road
13:42
sales
13:43
of
13:43
212
13:43
million
13:44
in
13:44
the
13:44
year
13:45
that
13:46
went
13:46
and
13:46
concluded
13:47
on
13:47
March
13:47
31st
13:47
of
13:48
2025.
13:49
And
13:49
that
13:49
if
13:50
you
13:50
include
13:50
the
13:50
additional
13:51
$200
13:51
million
13:52
payable
13:52
based
13:52
on
13:52
road's
13:53
performance
13:53
over
13:53
the
13:53
next
13:51
3
13:54
years,
13:54
the
13:54
multiple
13:54
is
13:55
actually
13:55
4.7
13:56
times.
13:57
So,
13:57
Ann,
13:57
my
13:57
question
13:58
for
13:58
you
13:58
is
13:58
this.
13:59
Do
13:59
you
13:59
think
13:59
ELF
14:00
will
14:00
see
14:00
the
14:00
long
14:01
term
14:01
payoff
14:01
it
14:01
hopes
14:02
from
14:02
acquiring
14:03
road?
14:04
You
14:05
know,
14:05
I
14:05
think
14:05
that
14:06
it's
14:06
hard
14:06
to
14:06
say
14:07
whether
14:07
or
14:07
not
14:07
that
14:07
will
14:08
be.
14:08
No
14:08
one
14:08
has
14:08
the
14:08
crystal
14:09
ball.
14:09
However,
14:10
I,
14:10
you're
14:10
hedging.
14:11
I
14:11
think
14:11
this
14:11
is
14:11
a
14:11
really
14:12
good
14:12
move.
14:12
No,
14:12
I'm
14:13
not
14:13
hedging.
14:13
I
14:13
think
14:13
this
14:13
is
14:14
a
14:14
really
14:14
good
14:14
move
14:14
from
14:14
elf.
14:14
I'm
14:15
gonna
14:15
start
14:15
bringing
14:15
prune
14:16
shears
14:16
to,
14:16
to
14:16
the,
14:17
to
14:17
the,
14:17
to
14:17
the,
14:18
to
14:18
the
14:18
podcast
14:18
every
14:19
time
14:19
you
14:19
hedge.
14:20
Well,
14:20
I
14:20
mean,
14:20
I'm,
14:21
I
14:21
think
14:21
I'm
14:21
just
14:21
making
14:22
a,
14:22
a
14:23
reasonable
14:24
analysis
14:24
of
14:24
this,
14:25
of
14:25
this,
14:25
considering
14:26
both
14:26
sides
14:26
of
14:26
the
14:27
story.
14:27
It
14:27
sounds
14:28
like
14:28
you're,
14:28
it
14:28
sounds
14:28
like
14:28
you're
14:28
leading
14:29
one
14:29
way,
14:29
though,
14:29
so
14:29
I'm
14:29
curious
14:29
to
14:30
hear
14:30
what
14:30
it
14:30
is.
14:30
I
14:30
am,
14:30
Yeah.
14:31
I
14:31
mean,
14:31
I,
14:31
I,
14:31
I'm
14:32
certain
14:34
as
14:34
much
14:34
as
14:34
a
14:34
Bloomberg
14:35
reporter
14:35
who
14:35
wrote
14:36
this
14:36
article
14:36
is,
14:36
but.
14:37
Oh,
14:37
you
14:37
think
14:37
they
14:38
hated
14:38
it?
14:38
You
14:38
think
14:38
the
14:38
Bloomberg
14:39
reporter.
14:39
I
14:40
think
14:40
that
14:40
they
14:40
were
14:40
not
14:41
positive
14:41
on
14:42
this
14:42
and
14:42
I
14:43
certainly
14:43
can
14:44
realize
14:45
that.
14:45
Yeah.
14:45
I
14:45
mean,
14:45
it's
14:46
a,
14:46
it's
14:46
a
14:46
lot
14:46
of
14:47
money
14:47
going
14:47
into
14:48
a
14:48
category
14:49
that
14:49
hasn't
14:49
seen
14:49
a
14:50
lot
14:50
of
14:50
growth.
14:50
I
14:50
mean,
14:50
you
14:51
have
14:51
other
14:52
beauty,
14:54
like
14:54
we'll
14:54
say
14:54
influencer,
14:55
celebrity
14:56
led
14:56
beauty
14:56
companies
14:57
that
14:57
aren't
14:57
doing
14:57
as
14:58
well.
14:59
Cody
14:59
had
14:59
to
14:59
sell
15:00
Kylie
15:00
cosmetics
15:01
because
15:01
it
15:01
wasn't
15:02
or
15:02
sorry,
15:02
not
15:02
Kylie
15:03
Kim.
15:03
Kim
15:04
Kardashian's
15:05
makeup
15:05
line
15:06
and
15:06
fragrance
15:06
line
15:06
because
15:07
it
15:07
wasn't
15:07
doing
15:07
as
15:07
well.
15:08
Like,
15:09
this
15:09
has
15:09
not
15:09
been
15:09
the
15:10
time
15:10
for
15:10
celebrity
15:11
inspired
15:11
brands.
15:12
However,
15:13
I
15:13
think
15:13
that
15:14
Rhode
15:14
is,
15:14
is
15:15
different
15:15
here.
15:16
If
15:16
you
15:16
look
15:17
at
15:17
Hailey
15:18
Bieber's
15:18
involvement,
15:19
true
15:20
involvement,
15:20
we
15:20
had
15:20
this
15:20
discussion
15:21
yesterday
15:22
in
15:22
the
15:22
creation
15:23
of,
15:23
of
15:23
each
15:24
of
15:24
the
15:24
products.
15:24
She's
15:25
been
15:25
very
15:25
specific
15:26
to
15:27
only
15:27
be
15:27
releasing
15:28
a
15:28
small
15:28
number
15:29
of
15:29
products.
15:30
I
15:30
mean,
15:30
I
15:30
think
15:31
that
15:31
this
15:32
stands
15:32
a
15:33
better
15:33
chance
15:33
than
15:34
some
15:34
of
15:34
the
15:34
others
15:34
would.
15:35
And
15:35
it's
15:35
the
15:35
reason
15:36
why
15:36
ELF
15:36
is
15:37
buying
15:38
Road
15:38
Over.
15:39
You
15:39
know,
15:39
Selena,
15:40
Selena
15:40
Gomez's
15:41
rare
15:41
beauty
15:41
or
15:41
makeup
15:42
by
15:42
Mario
15:42
or
15:42
another
15:42
one.
15:43
I
15:43
know
15:43
you,
15:43
I
15:43
know
15:43
you
15:44
know
15:44
all
15:44
the
15:44
names
15:44
that
15:44
I'm
15:45
talking
15:45
about
15:45
right
15:45
now,
15:45
Chris,
15:46
but
15:47
I
15:47
actually
15:47
do
15:47
know
15:48
those.
15:48
In
15:48
fairness
15:48
to
15:49
me,
15:49
I
15:49
actually
15:49
do
15:49
Know
15:49
those?
15:50
Yeah,
15:50
I
15:51
just
15:51
didn't
15:51
know
15:51
ROAD
15:53
well.
15:53
But
15:53
I
15:53
think
15:54
that
15:54
the
15:54
benefit
15:55
here
15:55
is
15:55
really
15:56
going
15:56
to
15:56
be
15:56
on
15:56
elf's
15:57
side.
15:57
However,
15:58
I
15:58
think
15:58
they're
15:58
going
15:58
to
15:59
learn
15:59
a
15:59
lot
15:59
from
16:00
this
16:01
premium
16:02
line
16:02
bringing
16:02
them
16:02
in.
16:03
As
16:03
you
16:03
mentioned,
16:03
like,
16:03
ELF
16:04
started
16:04
out
16:04
as
16:05
a,
16:05
as
16:05
a
16:06
high
16:06
end,
16:07
approachable,
16:08
like
16:08
high
16:08
end
16:09
beauty
16:09
quality
16:09
products,
16:10
low
16:10
price
16:10
point.
16:11
Like
16:11
they
16:11
started
16:11
their
16:12
products,
16:12
I
16:12
think
16:12
it
16:12
was
16:12
at
16:12
like
16:13
1,
16:13
3
16:13
and
16:14
$5
16:14
when
16:15
they
16:15
came
16:15
out
16:15
three
16:15
years
16:16
ago.
16:17
So
16:17
I,
16:17
I
16:18
think
16:18
that
16:18
the
16:18
opportunity
16:19
here
16:19
for
16:20
ELF
16:20
is
16:20
really
16:20
to
16:21
start
16:22
to
16:22
attract
16:22
and
16:23
learn
16:23
from
16:24
ROAD
16:25
and
16:25
how
16:25
they
16:26
might
16:26
be
16:26
able
16:26
to
16:26
start
16:27
to
16:27
get
16:28
into
16:28
the
16:28
premiumization
16:29
of
16:29
their
16:30
products
16:30
because
16:31
it's
16:31
going
16:31
to
16:31
cost
16:32
them
16:32
more
16:32
to,
16:32
to
16:33
produce
16:33
them.
16:33
They
16:34
talked
16:34
last
16:34
week
16:35
at
16:35
the
16:35
same
16:35
time
16:35
they
16:36
bought,
16:36
they
16:36
made
16:36
this
16:36
deal
16:37
about
16:37
how
16:37
tariffs
16:38
are
16:38
going
16:38
to
16:38
increase
16:38
the
16:38
prices
16:39
of
16:39
their
16:39
products
16:39
by
16:40
a
16:40
dollar
16:40
per
16:40
product.
16:41
I
16:41
think
16:41
it
16:42
allows
16:42
them
16:43
to
16:43
start
16:43
to,
16:44
to
16:44
start
16:44
to
16:44
eke
16:45
into
16:45
that
16:45
upper
16:45
echelon
16:46
category
16:47
and
16:47
maybe
16:47
they
16:47
have
16:48
Hayley
16:48
like
16:48
inspire
16:49
a
16:49
collection
16:50
or
16:50
they
16:51
have
16:51
Hayley
16:51
partner
16:52
with
16:52
them
16:52
on
16:52
like
16:53
collection.
16:54
That
16:54
I
16:54
think
16:54
is
16:54
a
16:55
really
16:55
important
16:56
category
16:57
and
16:57
a
16:57
really
16:57
important
16:58
audience
16:58
to
16:58
try
16:59
to
16:59
get
16:59
after
16:59
right
16:59
now.
17:00
So
17:00
people
17:00
who
17:00
can,
17:01
who
17:01
maybe
17:01
can
17:01
spend
17:02
a
17:02
little
17:02
bit
17:02
more
17:02
than
17:02
the
17:02
ELF
17:03
price
17:03
point
17:03
but
17:03
aren't
17:03
ready
17:04
to
17:04
pay
17:04
$28
17:05
for
17:05
a,
17:05
for
17:05
a,
17:06
a
17:07
the
17:07
glazed
17:07
donut.
17:08
Look,
17:08
Chris.
17:09
So
17:09
I,
17:09
I
17:09
love
17:09
it.
17:10
I'm,
17:10
I'm
17:10
very
17:10
happy
17:11
with
17:11
this
17:11
move.
17:12
But
17:13
no.
17:13
So
17:13
now
17:13
you
17:13
love
17:13
it.
17:14
Okay,
17:14
good
17:14
to
17:14
know.
17:15
Good
17:15
to
17:15
know.
17:16
I
17:17
don't
17:17
know.
17:17
I
17:17
mean,
17:17
I,
17:18
I
17:18
have
17:19
no
17:19
idea
17:19
and
17:19
I
17:19
will
17:20
willingly
17:20
admit
17:20
to
17:21
the
17:21
audience,
17:21
but
17:22
I
17:22
know
17:22
literally
17:23
nothing
17:23
about
17:23
the
17:23
CPG
17:24
beauty
17:24
space.
17:25
So,
17:25
you
17:25
know,
17:25
I'm
17:25
not
17:26
gonna
17:26
have
17:26
much
17:26
to
17:26
say
17:26
here,
17:26
but
17:27
I
17:27
think,
17:27
you
17:27
know,
17:28
listening
17:28
to
17:28
you
17:28
talk,
17:29
there
17:29
are
17:29
a
17:30
lot
17:30
of
17:30
things
17:30
that
17:30
have
17:31
to
17:31
be
17:31
true
17:31
for
17:32
this
17:32
to
17:32
work
17:32
out.
17:32
And
17:33
every
17:33
time
17:33
I
17:33
hear
17:33
that,
17:34
I
17:34
get
17:34
a
17:34
little
17:34
concerned,
17:35
especially
17:35
when
17:36
the
17:36
price
17:36
point
17:36
is
17:36
that
17:37
different
17:38
from
17:38
what,
17:38
you
17:38
know,
17:39
the
17:39
acquiring
17:39
brand
17:40
typically
17:40
is
17:40
known
17:40
for
17:41
and
17:41
successful
17:41
for.
17:42
So
17:42
it's
17:42
a
17:42
different,
17:43
it's
17:43
a
17:43
different
17:43
muscle
17:44
that
17:44
elf's
17:44
gonna
17:44
have
17:45
to
17:45
use
17:45
to
17:45
make
17:45
this
17:45
successful.
17:46
So
17:47
I
17:47
think
17:47
that,
17:47
I
17:48
think
17:48
net.
17:48
Net
17:48
actually
17:49
hearing
17:49
you
17:49
talk,
17:49
I'm
17:49
actually
17:50
a
17:50
little
17:50
bit
17:50
more
17:50
skeptical
17:52
of
17:52
this
17:52
working
17:53
out,
17:55
to
17:55
say
17:55
nothing
17:55
of
17:55
the
17:56
fact
17:56
I
17:56
have
17:56
no
17:56
idea
17:56
how,
17:57
you
17:57
know,
17:58
Hailey
17:58
Bieber's
17:59
social
17:59
influence
17:59
is
18:00
going
18:00
to
18:00
continue
18:00
to,
18:01
you
18:02
know,
18:02
move
18:02
forward
18:02
over
18:03
the
18:03
next
18:03
decade,
18:04
but
18:04
which
18:05
is
18:05
a
18:05
real
18:05
factor
18:05
too.
18:06
You
18:06
have
18:06
to
18:06
factor
18:06
that
18:06
into
18:06
the
18:07
probability
18:07
of
18:07
success.
18:08
But.
18:08
Right.
18:08
But
18:08
I,
18:09
you
18:09
know,
18:09
My
18:09
last
18:09
shout
18:10
out
18:10
to
18:10
Haley,
18:10
fellow
18:11
stroke
18:11
survivor,
18:11
for
18:12
getting
18:12
her
18:12
B.
18:12
And
18:13
you
18:13
know,
18:13
she
18:13
got
18:14
her
18:14
B
18:14
like
18:15
she
18:15
got
18:15
her
18:15
two
18:15
bees.
18:16
Actually,
18:16
to
18:16
your
18:16
point,
18:17
she
18:17
got
18:18
the
18:18
Bieber
18:18
and
18:18
the
18:19
billions.
18:19
So.
18:19
Yeah,
18:20
I
18:20
think
18:20
the
18:20
billions
18:21
are
18:21
the
18:21
ones
18:21
that
18:21
I'd
18:22
hang
18:22
on
18:22
to
18:22
more
18:23
closely
18:24
than
18:24
the.
18:24
Other
18:24
than
18:25
the
18:25
Bieber
18:25
last
18:26
name.
18:26
But.
18:27
But
18:27
yeah,
18:27
yeah,
18:28
it
18:28
sounds
18:28
like
18:28
there's.
18:28
Been
18:28
some
18:28
friction
18:29
in
18:29
that,
18:29
in.
18:29
On
18:30
that
18:30
side
18:30
of
18:30
things
18:30
too.
18:31
Yeah.
18:31
I
18:31
mean,
18:31
yeah,
18:31
I
18:32
apologize.
18:32
Yes.
18:33
Yeah,
18:33
I
18:33
know
18:33
about
18:33
this
18:34
stuff.
18:34
Oh,
18:34
my
18:34
God.
18:35
I
18:35
do
18:35
think
18:35
that,
18:36
like,
18:36
you
18:37
have
18:37
to
18:37
give
18:37
Haley
18:38
credit
18:38
though.
18:38
Like
18:39
Glossier.
18:39
Glossier
18:40
couldn't
18:40
do
18:40
this.
18:41
And
18:41
they
18:42
were
18:42
this
18:42
also
18:42
a
18:42
direct
18:43
to
18:43
consumer
18:43
skincare
18:44
brand,
18:44
not
18:45
founded
18:45
on
18:45
a
18:45
celebrity.
18:46
Like
18:46
there
18:47
is
18:47
some
18:47
opportunity
18:48
here.
18:49
So
18:49
if
18:49
anyone
18:50
can,
18:50
can
18:51
make
18:51
this
18:51
work,
18:51
I
18:51
think
18:52
Haley's
18:52
the
18:52
right
18:52
person
18:53
to
18:53
bet
18:53
on.
18:53
But
18:54
you're
18:54
totally
18:54
right.
18:55
There's
18:55
a
18:55
lot
18:55
of
18:55
other
18:55
external
18:56
factors
18:56
that
18:56
could
18:57
impact
18:57
the
18:57
success
18:57
of
18:58
this
18:58
down
18:58
the
18:58
road.
18:59
Yeah.
18:59
But
18:59
in
18:59
fair.
18:59
In
18:59
fairness
19:00
to
19:00
Glossier,
19:00
Glossier
19:01
probably
19:01
had
19:01
offers
19:01
and
19:01
probably
19:02
either
19:02
didn't
19:02
take
19:02
them
19:03
or
19:03
has
19:03
chosen
19:04
not
19:04
to
19:04
take
19:04
them
19:04
too.
19:05
Because
19:05
typically
19:06
with
19:06
these,
19:06
like,
19:06
you
19:07
know,
19:07
typically
19:07
with
19:07
these
19:07
like,
19:08
celebrity
19:09
inspired
19:09
brands,
19:10
they're
19:10
built
19:11
to
19:11
do
19:11
exactly
19:11
this.
19:12
They're
19:12
built
19:12
to
19:12
get
19:13
acquired
19:13
at
19:13
a
19:13
high
19:13
multiple
19:14
very
19:14
quickly
19:15
because
19:15
generally
19:15
speaking,
19:16
they're
19:16
run
19:16
by
19:16
legal
19:16
teams
19:16
out
19:17
of
19:17
la.
19:18
I
19:18
don't
19:18
know
19:18
that
19:18
that's
19:19
the
19:19
case
19:19
here,
19:19
but
19:19
I
19:19
imagine
19:20
somebody
19:20
is
19:20
playing,
19:21
is
19:22
telling
19:22
Hayley
19:22
where
19:22
to
19:23
go
19:23
and
19:23
what
19:23
to
19:23
do
19:23
and
19:23
what.
19:24
What
19:24
products
19:25
to
19:25
evaluate,
19:26
you
19:26
know,
19:27
at
19:27
a
19:27
certain
19:27
time.
19:28
So,
19:28
you
19:28
know,
19:29
you
19:29
know
19:29
how
19:29
this
19:29
works.
19:30
Let's
19:30
just
19:30
say.
19:31
Let's
19:31
just
19:31
say
19:31
I
19:31
bet
19:31
Emily
19:32
Weiss
19:32
is
19:32
not
19:32
super
19:33
thrilled
19:33
right
19:33
now
19:34
that
19:34
this
19:34
just
19:35
happened.
19:35
And
19:36
of
19:36
all
19:36
the
19:36
work
19:36
she's
19:37
been
19:37
doing
19:37
for
19:37
the
19:37
last,
19:38
what,
19:38
10
19:38
years,
19:39
she.
19:39
She
19:40
didn't
19:40
quite
19:40
net
19:41
that.
19:42
Yeah,
19:42
I
19:42
bet.
19:42
I
19:42
bet
19:43
she's.
19:43
I
19:43
bet
19:43
she's
19:43
wishing.
19:44
Yeah,
19:44
I
19:44
mean,
19:44
I
19:44
have
19:44
no
19:45
idea,
19:45
but
19:45
I
19:45
bet
19:45
she's
19:46
wishing
19:46
she
19:46
sold
19:46
out
19:46
a
19:47
long
19:47
time,
19:47
potentially
19:48
wishing
19:48
she
19:48
sold
19:48
out
19:48
a
19:48
long
19:48
time
19:49
ago.
19:49
But
19:49
then
19:49
that's
19:49
not
19:49
true
19:50
to
19:50
her
19:50
ethos
19:50
of
19:50
her
19:50
brand
19:51
either.
19:51
So
19:51
who
19:51
knows?
19:52
But
19:52
who
19:52
knows?
19:53
All
19:53
right,
19:53
let's
19:54
go
19:54
to
19:54
headline
19:54
number
19:54
three,
19:55
Chris,
19:56
another
19:56
topic
19:57
that
19:57
you'll
19:57
be
19:57
very
19:57
familiar
19:58
with.
19:58
We're
19:58
talking
19:58
Victoria's
19:59
Secret.
20:00
No,
20:01
you
20:01
actually
20:01
are.
20:01
The.
20:02
You
20:02
actually
20:03
have
20:03
done
20:03
a
20:03
lot
20:03
of
20:03
work
20:03
on
20:04
this
20:04
headline
20:04
right
20:04
now,
20:05
so
20:05
I'm
20:05
excited
20:05
to
20:05
hear
20:05
your
20:06
perspective.
20:06
But
20:06
headline
20:07
number
20:07
three,
20:08
Victoria's
20:08
Secret
20:08
shut
20:09
down
20:09
its
20:09
website
20:09
in
20:10
response
20:10
to
20:10
a
20:10
security
20:11
incident
20:11
last
20:12
week.
20:12
According
20:12
to
20:13
cnet
20:13
on
20:13
Wednesday,
20:14
the
20:14
clothing
20:14
and
20:15
lingerie
20:15
company
20:16
replaced
20:16
its
20:16
regular
20:17
US
20:17
Retail
20:17
site
20:17
with
20:18
a
20:18
note
20:18
to
20:18
customers
20:19
saying
20:19
that
20:19
it
20:19
was
20:20
aware
20:20
of
20:21
and
20:21
dealing
20:22
with
20:22
the
20:22
incident,
20:22
adding
20:23
that
20:23
its
20:23
website
20:23
and
20:24
some
20:24
services
20:24
were
20:25
temporarily
20:25
shut
20:26
down
20:26
as
20:26
a,
20:26
quote,
20:27
a
20:27
precaution,
20:29
end
20:29
quote.
20:29
It
20:29
did
20:30
not
20:30
offer
20:30
details
20:31
about
20:31
what
20:31
kind
20:31
of
20:31
security
20:32
incident
20:32
occurred,
20:32
but
20:33
said
20:33
that
20:33
its
20:33
brick
20:33
and
20:33
mortar
20:34
Victoria's
20:34
Secret
20:35
and
20:35
Pink
20:35
stores
20:36
remained
20:36
open.
20:37
Chris,
20:38
should
20:39
Victoria's
20:40
Secret
20:40
site
20:40
outage
20:41
last
20:41
week
20:42
be
20:42
a
20:42
wake
20:42
up
20:42
call
20:43
for
20:43
American
20:43
retailers?
20:45
Oh
20:45
my
20:45
God,
20:45
100%
20:46
yes.
20:46
And
20:46
I
20:47
mean,
20:47
we
20:47
asked
20:47
Michael
20:47
Prendergast
20:48
this
20:48
two
20:48
weeks
20:48
ago
20:49
when
20:49
we
20:49
had
20:49
A
20:49
and
20:49
M
20:49
on
20:50
the
20:50
podcast
20:50
and
20:50
he,
20:51
you
20:51
know,
20:51
he
20:51
anecdotally
20:52
said
20:52
from
20:52
his
20:52
experience
20:52
as
20:53
interim
20:53
CEO
20:53
at
20:53
Joann's
20:54
that
20:54
he
20:54
would
20:54
put
20:54
the
20:54
estimate
20:55
at
20:55
20%
20:56
of
20:56
the
20:56
US
20:56
retailers
20:57
that
20:57
are
20:57
actually
20:57
prepared
20:58
for
20:59
cyber,
20:59
you
20:59
know,
21:00
for
21:00
cyber
21:00
crimes
21:01
to
21:01
deal
21:01
with
21:01
them
21:01
as
21:02
they
21:02
come.
21:02
And
21:02
I,
21:03
you
21:03
know,
21:03
for
21:04
the
21:04
last,
21:04
again,
21:05
for
21:05
like
21:05
about
21:05
the
21:05
last
21:06
month,
21:06
I've
21:06
been
21:06
asking
21:07
a
21:07
lot
21:07
of
21:07
people
21:08
about
21:08
this.
21:08
Both
21:08
at
21:09
this
21:09
conference
21:09
at
21:10
Zoom
21:10
Calls,
21:10
I've
21:10
talked
21:11
with
21:11
companies
21:11
like,
21:11
like
21:12
Bodify.
21:13
And
21:14
I
21:14
was
21:14
talking
21:14
to
21:15
Rochelle
21:16
Thielen,
21:16
the
21:17
CEO
21:17
of
21:18
Traject
21:18
Data
21:19
at
21:19
Shop
21:19
Talk
21:19
Europe.
21:20
And
21:20
what
21:21
I've
21:21
been
21:21
learning
21:21
is
21:22
that
21:22
we
21:23
are
21:23
only
21:23
going
21:23
to
21:23
see
21:23
more
21:24
of
21:24
these
21:24
incidents
21:25
incidences,
21:26
you
21:27
know,
21:27
which
21:27
makes
21:28
me
21:28
feel
21:28
good
21:28
about
21:28
our
21:28
show
21:29
because
21:29
we've
21:29
been
21:30
talking
21:30
about
21:30
this
21:31
and
21:31
then,
21:31
I
21:31
mean,
21:32
I
21:32
don't
21:32
feel
21:32
good
21:32
for
21:32
Victoria
21:32
Seeger,
21:33
but
21:33
I
21:33
feel
21:33
good
21:33
for
21:34
our
21:34
show
21:34
because
21:34
we
21:34
talked
21:34
about
21:35
this
21:35
before
21:35
it
21:35
happened
21:36
and
21:36
then
21:36
it
21:37
happened
21:37
and
21:38
there's
21:38
we're
21:38
going
21:38
to
21:38
see
21:39
more
21:39
of
21:39
it
21:39
because
21:39
of
21:39
the
21:40
rise
21:40
of
21:40
AI,
21:40
because
21:41
the
21:41
way
21:42
with
21:42
AI
21:43
proliferating
21:44
in
21:44
the
21:44
space,
21:44
in
21:45
the
21:45
retail
21:45
space,
21:45
the
21:46
way
21:46
it
21:46
is,
21:46
particularly
21:47
with
21:47
agentic
21:47
AI
21:48
coming
21:48
into
21:48
the
21:48
fold
21:48
now.
21:49
Yeah,
21:50
retailers
21:51
and
21:51
brands,
21:51
websites
21:52
are
21:52
going
21:52
to
21:52
see
21:52
more
21:53
and
21:53
more
21:53
bots
21:54
scraping
21:55
their
21:55
sites
21:55
each
21:56
and
21:56
every
21:56
day.
21:57
Which
21:57
means
21:57
when
21:58
you
21:58
think
21:58
about
21:58
it
21:58
from
21:58
an
21:59
operations
21:59
standpoint,
22:00
it's
22:00
going
22:00
to
22:00
become
22:01
more
22:01
and
22:01
more
22:02
difficult
22:02
for
22:03
the
22:03
retailers
22:03
to
22:03
understand
22:04
who
22:04
are
22:04
the
22:05
good
22:05
bots
22:05
and
22:06
who
22:06
are
22:06
the
22:06
bad
22:06
bots.
22:07
But
22:07
yet
22:07
the
22:07
overall
22:08
traffic
22:08
of
22:08
bots
22:09
to
22:09
the
22:09
site
22:09
is
22:09
going
22:10
to
22:10
increase
22:11
exponentially.
22:12
So
22:13
not
22:13
surprisingly,
22:13
when
22:14
that
22:14
happens,
22:14
more
22:15
of
22:15
the
22:15
sophisticated
22:16
threats
22:16
are
22:16
going
22:17
to
22:17
get
22:17
through
22:17
because
22:17
the
22:18
security
22:19
systems
22:19
are
22:19
having
22:20
to
22:20
watch
22:20
more
22:20
things.
22:21
So
22:21
the
22:21
cyber
22:22
criminals
22:22
are
22:22
smart
22:23
and
22:23
they
22:24
know
22:24
how
22:24
to
22:24
capitalize
22:24
on
22:25
recent
22:25
trends
22:25
better
22:25
and
22:26
faster
22:26
than
22:26
anyone.
22:27
And
22:27
so
22:27
the
22:27
retailers
22:27
are
22:27
going
22:28
to
22:28
be,
22:28
it's
22:28
going
22:28
to
22:28
be
22:28
difficult
22:28
for
22:29
them
22:29
to
22:29
stop
22:29
them.
22:29
So
22:30
I
22:30
Think
22:30
retailers
22:31
listening.
22:31
If
22:31
you're
22:32
in
22:32
this
22:32
space,
22:32
you
22:32
probably
22:33
already
22:33
know
22:33
this,
22:33
but,
22:34
you
22:34
know,
22:34
if
22:34
you're
22:35
an
22:35
executive
22:35
who's
22:35
deciding
22:36
budgets
22:36
and
22:37
you're
22:37
a
22:37
CFO
22:37
trying
22:38
to
22:38
figure
22:38
out,
22:38
you
22:38
know,
22:38
how
22:38
much
22:39
do
22:39
we
22:39
earmark
22:39
towards
22:39
what.
22:40
I
22:40
would,
22:40
I
22:41
would
22:41
probably
22:41
be
22:41
leaning
22:42
into
22:42
this
22:42
a
22:42
little
22:42
bit
22:43
more,
22:43
at
22:43
least
22:43
conversationally
22:44
in
22:44
the
22:44
boardrooms.
22:45
Yeah,
22:45
I,
22:46
I
22:46
think
22:46
that
22:46
was
22:47
an
22:47
awesome
22:48
overview,
22:48
Chris.
22:49
And
22:49
I
22:49
think
22:50
the
22:50
last
22:50
thing
22:50
that
22:51
I
22:51
would
22:51
just
22:51
say,
22:51
which
22:52
we,
22:52
you
22:52
know,
22:52
we
22:52
talked
22:53
about
22:53
with
22:53
Michael
22:53
Prendergrass
22:54
when
22:54
we
22:54
were
22:54
talking
22:55
about
22:55
the,
22:55
you
22:56
know,
22:56
the
22:56
teams
22:56
from
22:57
co
22:57
op
22:57
and
22:58
Harrods
22:59
and
22:59
others
22:59
that
22:59
have
22:59
been
23:00
hit
23:00
in
23:00
the
23:00
UK
23:01
recently
23:01
with
23:02
cyber
23:02
attacks.
23:03
The,
23:04
the
23:04
loss
23:04
to
23:05
customers
23:06
is
23:06
so
23:07
high,
23:07
like
23:07
when
23:08
you
23:08
talk
23:08
and
23:08
oh
23:09
yeah,
23:09
think
23:09
about
23:09
like,
23:10
even
23:10
the
23:10
reviews
23:11
in
23:11
and
23:11
some
23:12
of
23:12
the
23:12
commentary
23:12
that
23:12
they
23:13
got
23:13
for
23:13
this
23:13
Victoria
23:14
Secret
23:14
reporting.
23:14
Like,
23:15
they're
23:15
bad,
23:15
they're
23:16
bad.
23:16
They're
23:16
people
23:17
who,
23:17
once
23:17
you
23:17
lose
23:18
those
23:18
customers,
23:19
you're
23:19
already
23:19
doing
23:20
so
23:20
much
23:20
to
23:21
get
23:21
them
23:21
in
23:21
the
23:21
door
23:22
to
23:22
maintain
23:23
them
23:23
as
23:23
a
23:23
customer.
23:23
Especially
23:24
for
23:24
a
23:24
legacy
23:24
brand
23:25
like
23:25
Victoria's
23:26
Secret
23:26
or
23:26
like
23:26
Joanne
23:27
that
23:27
Michael
23:27
was
23:27
talking
23:27
about
23:27
last
23:28
week,
23:28
the
23:29
cost
23:29
to
23:29
acquire
23:30
those
23:30
customers,
23:31
again,
23:31
I
23:31
have
23:32
to
23:32
imagine
23:32
far
23:33
out
23:33
it
23:34
exceeds
23:34
the
23:34
cost
23:35
to
23:35
just
23:35
get
23:35
your
23:36
cybersecurity
23:36
house
23:37
in
23:37
order.
23:38
So
23:38
I
23:38
think
23:38
that's
23:39
the,
23:39
that's
23:39
the
23:39
thing
23:40
here
23:40
that
23:41
it's
23:41
not
23:41
just
23:41
the,
23:42
the
23:42
cost
23:42
of
23:43
the
23:43
loss
23:43
of
23:44
data
23:44
or
23:45
of
23:45
time
23:45
or
23:46
of,
23:46
you
23:46
know,
23:47
resour
23:47
put
23:47
towards,
23:48
towards
23:49
getting
23:49
the
23:49
site
23:49
back
23:49
up
23:49
online.
23:50
It's
23:50
really
23:50
the
23:50
cost
23:51
and
23:51
the
23:51
impact
23:52
that
23:52
this
23:52
has
23:53
on
23:53
your
23:53
customer
23:53
base
23:54
too,
23:54
that
23:54
I
23:54
think
23:54
people
23:55
need
23:55
to
23:55
be
23:55
putting
23:55
into
23:56
that
23:56
consideration
23:56
set
23:57
it.
23:57
Puts
23:58
in
23:58
the
23:58
mind
23:58
of
23:58
your
23:58
customer.
23:59
Do
23:59
I
23:59
want
23:59
to
23:59
switch?
24:00
Right.
24:01
And
24:01
that's
24:01
never
24:02
something
24:02
you
24:02
want
24:02
to
24:02
have
24:03
happen,
24:03
especially
24:03
after
24:04
a
24:04
purchase
24:04
like
24:05
is
24:05
happening
24:05
in
24:05
this
24:06
Victoria's
24:06
Secret
24:06
example
24:07
too.
24:07
And
24:07
let's
24:07
bring
24:08
Eugene
24:08
onto
24:08
the
24:08
show
24:09
now
24:09
to
24:09
talk
24:09
about
24:10
the
24:10
rise
24:10
of
24:11
AI
24:11
and
24:11
agentic
24:12
AI,
24:12
particularly
24:13
in
24:13
terms
24:13
of
24:13
how
24:14
it
24:14
relates
24:14
to
24:14
order
24:14
management
24:15
systems.
24:15
Foreigning
24:20
us
24:20
now
24:21
for
24:21
five
24:21
insightful
24:22
minutes
24:22
is
24:22
Eugene
24:22
Amigood,
24:23
the
24:23
Chief
24:24
Innovation
24:24
Officer
24:24
at
24:25
infios.
24:25
Eugene
24:26
is
24:26
here
24:26
to
24:26
help
24:26
us
24:26
separate
24:27
fact
24:27
from
24:28
fiction
24:28
when
24:28
it
24:28
comes
24:28
to
24:29
harnessing
24:29
AI
24:30
for
24:30
your
24:30
supply
24:31
chain.
24:31
Okay,
24:31
Eugene,
24:32
let's
24:32
start
24:32
with
24:33
this.
24:34
AI
24:34
is
24:34
freaking
24:35
everywhere.
24:36
But
24:36
as
24:36
the
24:36
Chief
24:36
Innovation
24:37
Officer,
24:38
how
24:38
do
24:38
you
24:38
think
24:38
about
24:39
deploying
24:39
across
24:39
the
24:40
supply
24:40
chain?
24:40
I
24:40
mean,
24:40
like,
24:41
I
24:41
get
24:41
bombarded
24:42
every
24:42
day
24:42
with
24:43
everything
24:43
from
24:43
predictive
24:44
algorithms
24:44
to
24:44
gentic
24:45
AI.
24:46
How
24:46
should
24:47
our
24:47
audience
24:47
think
24:48
about
24:49
separating
24:49
true
24:50
innovation
24:50
from
24:50
hype?
24:51
In
24:51
this
24:51
era,
24:52
we
24:52
think
24:52
about
24:53
purposeful
24:53
innovation
24:54
to
24:54
start
24:54
with,
24:55
right?
24:55
Again,
24:55
there
24:55
is
24:56
a
24:56
lot
24:56
of
24:56
AI
24:56
hype
24:57
and
24:58
the
24:58
way
24:58
kind
24:58
of
24:59
to
24:59
break
24:59
through
24:59
that
25:00
is
25:00
I
25:00
think
25:01
of
25:01
different
25:02
use
25:02
cases
25:03
and
25:03
the
25:03
right
25:04
technology,
25:05
right
25:05
approach
25:05
for
25:05
these
25:05
use
25:06
cases.
25:07
When
25:07
we
25:07
think
25:07
about
25:07
AI,
25:08
there
25:08
is
25:08
machine
25:09
learning
25:09
and
25:09
predictive
25:09
analytics,
25:10
there
25:10
are
25:11
optimizers
25:12
as
25:12
well
25:12
as
25:13
the
25:13
latest
25:13
and
25:13
greatest
25:14
gen
25:14
AI.
25:14
And
25:14
depending
25:15
on
25:15
the
25:15
use
25:15
case,
25:16
there's
25:16
the
25:16
right
25:16
kind
25:16
of
25:17
tool
25:17
to
25:18
address
25:18
it.
25:19
So
25:20
first
25:20
of
25:20
all
25:20
is
25:21
partner
25:22
with
25:22
customers
25:22
to
25:23
co
25:23
develop
25:23
on
25:24
specific
25:24
use
25:25
cases,
25:25
on
25:25
specific
25:26
needs,
25:26
instead
25:26
of
25:27
kind
25:27
of
25:27
thinking
25:27
it
25:28
within
25:28
the
25:28
black
25:28
box.
25:29
And
25:30
number
25:30
two,
25:32
many
25:33
of
25:33
us
25:33
already
25:33
have
25:34
existing
25:34
systems
25:34
deployed
25:36
and
25:37
the
25:37
innovation
25:38
has
25:38
to
25:38
be
25:38
augmentative,
25:39
meaning
25:40
that
25:40
I
25:40
may
25:41
create
25:41
a
25:41
new
25:42
module,
25:42
new
25:42
component
25:43
that
25:43
solves
25:44
my
25:44
specific
25:44
need,
25:45
drop
25:45
it
25:46
in,
25:46
realize
25:47
the
25:47
benefit
25:47
in
25:47
maybe
25:48
a
25:48
couple
25:48
weeks
25:49
to
25:49
a
25:49
couple
25:49
months
25:50
and
25:50
move
25:50
on.
25:51
I
25:51
have
25:51
no
25:51
more
25:52
time
25:52
to
25:52
deploy
25:52
these
25:53
capabilities
25:53
over
25:54
long
25:55
period
25:55
of
25:55
time.
25:56
So
25:56
again,
25:56
make
25:57
it
25:57
with
25:57
purpose,
25:58
use
25:58
case
25:58
based
25:59
as
25:59
well
25:59
as
26:00
making
26:00
it
26:00
augmentative.
26:01
Eugene
26:02
the
26:02
retail
26:02
industry
26:03
is
26:03
in
26:03
a
26:03
constant
26:04
state
26:04
of
26:04
disruption
26:05
right
26:05
now.
26:05
And
26:06
it's.
26:06
It
26:06
seems
26:06
like
26:07
staying
26:07
ahead
26:08
is
26:08
more
26:08
than
26:09
just
26:09
reacting
26:10
to
26:10
market
26:10
uncertainty.
26:11
It
26:11
means
26:12
designing
26:13
your
26:13
business
26:13
operation
26:14
for
26:14
adaptability.
26:15
How
26:16
would
26:16
you
26:16
say
26:17
that
26:17
infios
26:18
thinks
26:18
about
26:18
innovation
26:19
not
26:19
only
26:19
to
26:20
navigate
26:20
this
26:20
change,
26:21
but
26:21
really
26:21
to
26:21
predict
26:22
what's
26:22
ahead?
26:23
With
26:23
so
26:23
much
26:24
supply
26:24
chain
26:24
uncertainty
26:25
and
26:26
constant
26:27
changes,
26:27
right.
26:28
The
26:28
deterministic
26:29
rules
26:30
and
26:30
ability
26:30
to
26:30
configure
26:31
the
26:31
systems
26:31
becomes
26:33
almost
26:33
impossible,
26:34
right?
26:34
Again,
26:34
during
26:34
COVID
26:36
there
26:36
was
26:36
a
26:36
lot
26:36
of
26:36
disruption,
26:37
but
26:37
over
26:37
time
26:38
people
26:38
thought,
26:38
well,
26:38
maybe
26:39
it
26:39
will
26:39
stabilize.
26:40
And
26:40
now
26:40
we
26:41
all
26:41
understand,
26:41
right,
26:42
that
26:42
this
26:42
uncertainty
26:43
does
26:43
not
26:43
go
26:44
away.
26:44
If
26:44
anything,
26:45
it
26:45
becomes
26:45
more
26:45
and
26:45
more
26:46
complex,
26:46
right?
26:47
And
26:47
so
26:47
how
26:47
do
26:48
you
26:48
react
26:48
to
26:49
this
26:49
uncertainty?
26:49
So
26:50
historically
26:50
you
26:50
would
26:50
kind
26:51
of
26:51
set
26:51
up
26:51
all
26:51
these
26:52
different
26:52
rules,
26:52
configurations
26:53
in
26:53
your
26:53
systems
26:54
or
26:55
deploy
26:55
the
26:55
entire
26:55
system
26:56
to
26:56
address
26:56
it.
26:57
But
26:57
now
26:58
it
26:58
has
26:58
to
26:58
be
26:59
a
26:59
lot
26:59
more
27:00
dynamic.
27:00
It
27:00
has
27:01
to
27:01
be
27:01
a
27:01
lot
27:01
more
27:01
aligned
27:02
with
27:02
the
27:02
business
27:03
needs
27:04
versus
27:05
the
27:05
systems,
27:06
right?
27:06
So
27:06
again,
27:06
if
27:07
I
27:07
have
27:07
a
27:07
labor
27:08
strike
27:08
in
27:08
my
27:09
port,
27:09
how
27:09
do
27:09
I
27:10
comprehensively
27:10
address
27:11
it?
27:11
If
27:11
I
27:11
have
27:11
a
27:12
strategy
27:12
to
27:12
get
27:12
close
27:12
to
27:13
my
27:13
customers,
27:13
how
27:14
do
27:14
I
27:14
comprehensively
27:15
address
27:15
it
27:15
and
27:15
how
27:15
do
27:15
I
27:15
react
27:16
to
27:16
these
27:16
uncertainties?
27:17
And
27:17
that's
27:18
where
27:18
AI
27:18
and
27:18
ML
27:19
come
27:19
in,
27:19
where
27:19
it
27:20
can
27:20
look
27:20
at
27:20
historical
27:21
data,
27:21
right?
27:22
And
27:23
being
27:23
able
27:23
to
27:23
react
27:24
based
27:25
on
27:25
that
27:25
historical
27:25
data
27:26
and
27:26
make
27:26
some
27:26
predictions
27:27
on
27:28
it.
27:28
However,
27:29
historically
27:31
the
27:31
planning
27:31
systems
27:32
used
27:32
to
27:32
look
27:32
at
27:32
years
27:33
and
27:33
years
27:33
worth
27:34
of
27:34
data.
27:34
But
27:35
what
27:35
we're
27:35
seeing
27:35
now
27:36
from
27:36
planning
27:37
perspective,
27:37
right,
27:38
look
27:38
at
27:38
tariffs
27:38
that
27:38
change
27:39
pretty
27:39
much
27:39
daily,
27:40
or
27:40
the
27:41
labor
27:41
strikes
27:41
et
27:42
CETERA
27:42
you
27:43
have
27:43
to
27:43
react
27:43
so
27:43
much
27:44
faster.
27:44
So
27:45
now
27:46
the
27:46
scope
27:47
becomes
27:47
so
27:47
much
27:48
more
27:48
important
27:48
to
27:48
kind
27:49
of
27:49
look
27:49
at
27:49
the
27:49
near
27:50
real
27:50
time
27:50
data
27:50
and
27:51
to
27:51
be
27:51
able
27:51
to
27:51
react
27:52
accordingly.
27:53
You
27:53
know,
27:53
the
27:53
one
27:53
thing
27:53
you
27:53
guys
27:54
always
27:54
talked
27:54
about
27:54
to
27:55
me
27:55
was
27:55
like
27:55
this
27:56
idea
27:56
of
27:56
a
27:57
quote
27:57
unquote
27:57
brain
27:58
or
27:58
a
27:58
decision
27:59
engine.
28:01
Given
28:01
what
28:01
you're
28:01
describing,
28:04
is
28:04
that
28:04
concept
28:05
still
28:05
in
28:05
play
28:05
here
28:06
or
28:06
how
28:06
should
28:06
we
28:06
think
28:07
about
28:07
that?
28:08
Yeah.
28:09
Realigning
28:10
the
28:11
system
28:11
capabilities
28:12
to
28:13
be
28:13
closer
28:13
to
28:13
the
28:14
kind
28:14
of
28:14
functional
28:14
solutions
28:15
that
28:15
business
28:16
needs
28:16
is
28:16
absolutely
28:17
key.
28:17
And
28:17
the
28:17
decision
28:18
engine
28:18
sits
28:19
at
28:19
the
28:19
core
28:19
of
28:19
it.
28:20
Historically,
28:21
these
28:21
decisioning
28:21
engines
28:22
used
28:22
to
28:22
be
28:22
within
28:23
transportation
28:24
or
28:24
within
28:24
order.
28:25
What's
28:25
the
28:25
most
28:26
effective
28:26
way
28:26
to
28:26
fulfill
28:27
an
28:27
order?
28:27
What's
28:27
the
28:28
most
28:28
cost
28:28
effective
28:29
way
28:29
to
28:30
ship
28:30
a
28:30
load
28:30
across
28:31
the
28:31
country?
28:33
Now
28:34
all
28:34
of
28:34
those
28:35
need
28:35
to
28:35
be
28:35
tied
28:35
together
28:36
to
28:36
be
28:36
able
28:36
to
28:37
react
28:37
to
28:37
those
28:37
disruptions.
28:38
And
28:38
the
28:38
decisioning
28:39
engine
28:40
sits
28:40
kind
28:40
of
28:41
outside
28:42
and
28:43
makes
28:43
all
28:43
this
28:44
kind
28:44
of
28:44
both
28:44
deterministic
28:45
as
28:46
well
28:46
as
28:46
AI
28:46
based
28:47
decisions.
28:48
Looking
28:48
at
28:49
all
28:49
this
28:49
holistically,
28:50
which
28:50
is
28:51
not
28:51
really
28:51
possible
28:51
in
28:52
the
28:52
old
28:52
world
28:52
when
28:53
those
28:53
decision
28:53
engines
28:54
used
28:54
to
28:54
be
28:54
isolated.
28:56
Got
28:56
it.
28:56
So,
28:57
so
28:57
if
28:57
I
28:57
say
28:58
that
28:58
back
28:58
to
28:58
you,
28:58
then
28:58
you're
28:58
saying
28:59
that
28:59
there's
28:59
basically
29:00
there's
29:01
like
29:01
going
29:01
to
29:01
the
29:01
decision
29:02
engine
29:02
still
29:02
matters,
29:03
but
29:03
there's
29:03
almost
29:03
a
29:03
module
29:04
in
29:04
and
29:04
of
29:04
itself
29:05
that
29:05
is
29:05
going
29:05
to
29:05
command
29:05
and
29:06
control
29:06
everything
29:06
else
29:07
that's
29:07
going
29:07
on,
29:07
Is
29:08
that
29:08
right?
29:09
Exactly.
29:09
So
29:10
this
29:10
module
29:10
is
29:11
the
29:11
key,
29:11
Chris,
29:12
as
29:12
you
29:12
mentioned,
29:12
because
29:13
if
29:13
it's
29:13
an
29:13
independent
29:14
module,
29:14
you
29:14
can
29:14
deploy
29:15
it
29:15
fast,
29:16
you
29:16
can
29:16
realize
29:16
the
29:16
benefits,
29:17
the
29:18
intelligence
29:18
of
29:18
each
29:19
individual
29:19
system
29:19
you
29:20
rely
29:20
on
29:20
less.
29:21
But
29:21
now
29:21
this
29:22
kind
29:22
of
29:22
consolidated
29:22
decisioning
29:23
engine
29:23
can
29:24
come
29:24
up
29:24
with
29:24
the
29:24
most
29:24
comprehensive
29:25
and
29:26
kind
29:26
of
29:26
cost
29:27
effective
29:28
whatever
29:29
you're
29:29
optimizing
29:29
on
29:30
solutions
29:31
that
29:31
you
29:31
would
29:32
need.
29:33
What's
29:33
a
29:33
breakthrough
29:34
that
29:34
you
29:34
see
29:34
happening
29:35
on
29:35
the
29:35
horizon?
29:35
Something
29:36
that
29:36
you
29:36
believe
29:36
is
29:37
going
29:37
to
29:38
fundamentally
29:39
redefine
29:39
commerce
29:40
in
29:40
the
29:40
next
29:40
three
29:41
to
29:41
five
29:41
years.
29:42
Again,
29:42
there
29:43
are
29:43
two
29:43
parts
29:43
and
29:43
I
29:44
think
29:44
they're
29:44
both
29:44
aligned.
29:45
So
29:45
business
29:46
is
29:46
moving
29:46
from
29:46
again,
29:47
this
29:47
systematic
29:48
approach
29:48
of
29:49
buying
29:49
individual
29:50
systems
29:51
like
29:51
OMS
29:52
or
29:53
front
29:53
end
29:54
or
29:55
payment,
29:55
et
29:55
cetera,
29:56
to
29:56
kind
29:56
of
29:56
solving
29:57
business
29:57
needs.
29:58
And
29:58
on
29:59
the
29:59
other
29:59
side
29:59
from
30:00
technology
30:01
is
30:02
again,
30:02
as
30:02
I
30:03
was
30:03
mentioning,
30:03
from
30:03
this
30:04
microservice
30:04
to
30:04
modules
30:05
to
30:05
agentic.
30:06
And
30:06
what
30:07
gets
30:07
me
30:07
excited
30:07
the
30:08
most,
30:08
because
30:08
I'm
30:08
in
30:08
the
30:09
supply
30:09
chain
30:09
execution
30:10
side.
30:11
This
30:11
whole
30:12
gen
30:12
AI
30:12
started
30:12
as
30:13
a
30:13
natural
30:13
language
30:14
kind
30:14
of
30:14
processing,
30:15
LLMs
30:16
models,
30:17
et
30:17
cetera.
30:17
So
30:17
it
30:17
was
30:17
really
30:18
good,
30:18
and
30:18
I
30:18
would
30:19
always
30:19
say
30:19
it
30:19
was
30:19
really
30:20
good
30:20
for
30:20
planning
30:20
systems
30:21
because
30:21
planners
30:21
interact
30:22
in
30:23
that
30:23
way
30:23
from
30:24
execution
30:25
the
30:25
less
30:25
human
30:26
intervention
30:26
there
30:27
is,
30:27
the
30:27
better
30:28
your
30:28
system
30:28
works.
30:29
So
30:29
historically,
30:30
these
30:30
LLMs
30:31
and
30:31
Genai
30:31
was
30:32
not
30:32
built
30:32
for
30:33
supply
30:33
chain
30:34
execution.
30:34
So
30:35
I
30:35
think
30:35
the
30:35
most
30:35
innovation
30:36
will
30:36
come
30:36
from
30:36
that
30:37
space.
30:38
And
30:38
now
30:38
with
30:38
the
30:38
new
30:38
technology
30:39
around
30:40
agentic,
30:41
around
30:41
this
30:41
kind
30:42
of
30:42
autonomous
30:42
agents
30:43
being
30:43
able
30:44
to
30:44
orchestrate
30:45
in
30:45
the
30:45
real
30:46
time.
30:46
Right.
30:46
Not
30:47
spinning
30:47
now,
30:48
you
30:48
know,
30:48
chatgpt
30:49
and
30:49
you're
30:49
asking
30:49
a
30:49
question,
30:50
right?
30:50
If
30:51
I'm
30:51
scanning
30:51
shipments,
30:52
I'm
30:52
scanning
30:52
them,
30:52
you
30:53
know,
30:53
within
30:53
milliseconds.
30:54
If
30:54
I'm
30:54
processing
30:55
orders,
30:55
I'm
30:55
processing
30:55
it
30:56
within
30:56
the
30:56
right
30:57
single
30:57
digit
30:58
milliseconds.
30:58
And
30:59
so
30:59
that
31:00
kind
31:00
of
31:01
ability
31:02
to
31:02
meet
31:02
the
31:02
business
31:02
needs
31:03
with
31:03
this
31:03
new
31:04
tack,
31:04
it's
31:04
probably
31:05
what's
31:05
going
31:05
to
31:05
evolve
31:05
over
31:06
time
31:06
in
31:06
a
31:06
very
31:07
exciting
31:08
and
31:08
new
31:08
ways.
31:08
Since
31:09
you're
31:09
saying
31:09
protect
31:10
the
31:10
brain.
31:10
Thank
31:10
you,
31:11
Eugene.
31:11
That
31:11
was
31:11
great.
31:12
Exactly,
31:12
Eugene.
31:15
Headline
31:16
number
31:16
four.
31:16
Aldi
31:17
is
31:17
running
31:17
digital
31:18
work
31:18
experience
31:18
courses
31:19
for
31:19
teens.
31:20
According
31:20
to
31:20
Internet
31:21
Retailing,
31:21
Aldi
31:22
has
31:22
launched
31:22
a
31:22
free
31:22
virtual
31:23
work
31:23
experience
31:24
program
31:25
for
31:25
anyone
31:25
over
31:25
the
31:26
age
31:26
of
31:26
13
31:26
to
31:26
help
31:27
them
31:27
discover
31:27
retail
31:28
careers.
31:28
The
31:28
online
31:29
course,
31:29
developed
31:29
with
31:30
Spring
31:30
Podcast,
31:31
is
31:31
designed
31:32
to
31:32
offer
31:32
insights
31:32
into
31:32
various
31:33
retail
31:33
roles,
31:34
from
31:34
warehouse
31:34
and
31:35
store
31:35
operations
31:35
to
31:36
office
31:36
positions.
31:37
Participants
31:38
will
31:38
engage
31:38
with
31:38
videos
31:39
and
31:39
guidance
31:39
from
31:39
Aldi
31:40
employees,
31:40
as
31:40
well
31:40
as
31:41
interactive
31:41
quizzes
31:41
and
31:42
activities.
31:43
Upon
31:43
finishing
31:44
the
31:44
program,
31:44
they
31:44
will
31:45
receive
31:45
a
31:45
certificate
31:46
to
31:46
strengthen
31:46
their
31:47
CVs.
31:48
You
31:48
can
31:48
tell
31:48
where
31:48
this
31:49
headline
31:49
originated
31:50
or
31:50
resumes
31:51
for
31:52
future
31:52
applications.
31:53
Since
31:54
launching,
31:54
Aldi
31:55
says
31:55
that
31:55
it
31:55
has
31:55
already
31:56
attracted
31:56
more
31:56
than
31:57
2,000
31:57
signups
31:58
in
31:58
hopes
31:58
to
31:58
inspire
31:59
even
31:59
more
31:59
young
31:59
people
32:00
to
32:01
explore
32:01
careers
32:01
in
32:02
retail.
32:02
Ann,
32:03
are
32:03
you
32:03
buying
32:03
or
32:04
selling
32:04
all
32:05
these
32:05
new
32:05
virtual
32:06
work
32:06
experience
32:06
course
32:07
for
32:07
teens?
32:08
I'm
32:08
buying
32:09
the
32:09
idea.
32:09
I
32:09
think
32:09
it's
32:10
great.
32:10
I
32:10
knew
32:11
you
32:11
would.
32:11
I
32:11
think
32:12
they're
32:12
going
32:12
to
32:12
have
32:13
to
32:13
figure
32:13
out
32:13
how
32:14
they
32:14
get
32:14
traffic.
32:15
Like
32:15
that's
32:15
my,
32:16
that's
32:16
my
32:17
biggest
32:17
concern
32:18
here
32:18
is
32:18
are
32:19
they
32:19
going
32:19
to
32:19
see
32:19
the
32:19
payoff
32:20
for
32:20
the
32:20
investment?
32:21
I
32:21
went
32:21
into
32:21
the
32:21
tool
32:22
yesterday
32:23
and
32:23
I
32:24
recommend
32:24
checking
32:25
this
32:25
out.
32:25
I
32:25
mean,
32:25
it's
32:25
really
32:26
impressive.
32:26
Like
32:26
I
32:27
went
32:27
through
32:27
a
32:28
couple
32:28
of
32:28
the
32:28
sessions.
32:29
They
32:29
help
32:29
you
32:29
set
32:30
up
32:30
a
32:30
LinkedIn
32:30
page.
32:31
They
32:31
do
32:31
like
32:32
interview
32:32
prep
32:33
and
32:33
practice.
32:33
Like
32:34
it's
32:34
a
32:34
great
32:34
thing.
32:35
I'm
32:35
making
32:35
my
32:36
14
32:36
year
32:36
old
32:36
sign
32:37
up
32:37
for
32:37
this
32:37
because
32:37
I
32:37
think
32:37
it's
32:38
a
32:38
great
32:38
tool.
32:39
Now,
32:40
will
32:40
this,
32:41
will
32:41
this
32:42
result
32:42
in
32:43
Aldi
32:43
getting
32:44
an
32:44
influx
32:44
of
32:45
new
32:46
talent?
32:46
I
32:47
don't
32:47
know.
32:47
I
32:48
think
32:48
that's
32:48
still
32:48
to
32:49
be
32:49
determined.
32:50
But
32:50
I
32:50
do
32:50
think,
32:50
you
32:51
know,
32:51
having
32:51
a
32:51
son
32:52
who's
32:52
going
32:52
through
32:52
this
32:52
process
32:53
right
32:53
now
32:53
of
32:53
trying
32:53
to
32:54
get
32:54
his
32:54
first
32:54
job
32:54
like
32:55
this
32:55
is
32:55
a
32:56
way
32:56
to
32:56
start
32:57
to
32:57
get
32:57
them
32:57
engaged
32:58
and
32:58
involved
32:58
with
32:58
your
32:59
brand
32:59
early
32:59
on
33:00
and
33:01
leave
33:01
a
33:01
good
33:01
taste
33:01
in
33:02
their
33:02
mouth.
33:02
I
33:02
think
33:02
no
33:03
matter
33:03
where
33:03
they
33:03
end
33:03
up
33:03
going.
33:04
Like
33:04
he
33:04
could
33:04
put
33:04
this
33:04
on
33:05
a
33:05
resume
33:05
for
33:05
a
33:05
local
33:06
grocery
33:06
retailer
33:07
or
33:07
something
33:07
when
33:07
he's
33:07
going
33:07
in.
33:08
And
33:08
there's
33:08
really
33:08
nowhere
33:09
else
33:09
to
33:09
do
33:10
that
33:10
when
33:10
you're
33:10
early
33:10
on
33:11
in
33:11
your
33:12
job
33:12
search.
33:13
And
33:13
I
33:13
think
33:13
the
33:13
other
33:14
component
33:14
of
33:14
this
33:14
that
33:15
we're
33:15
hearing
33:15
loud
33:16
and
33:16
clear
33:16
here
33:16
at
33:17
Shop
33:17
Talk
33:17
Europe
33:18
is
33:18
the
33:18
investment
33:19
in
33:20
the
33:20
people
33:20
that
33:20
are
33:21
working
33:21
in
33:21
your
33:21
stores,
33:22
getting
33:22
training
33:23
as
33:23
early
33:23
as
33:24
possible,
33:24
continuing
33:25
to
33:25
train
33:26
people
33:26
as
33:27
much
33:27
as
33:27
possible
33:27
to
33:28
do
33:28
a
33:28
multitude
33:29
of
33:29
skills,
33:29
not
33:29
just
33:30
training
33:30
them
33:30
on
33:30
task
33:31
specific
33:32
jobs,
33:32
but
33:33
really
33:33
preparing
33:34
them
33:34
for
33:34
a
33:34
career
33:35
in,
33:36
in
33:36
retail.
33:36
Because
33:37
I
33:37
think
33:37
that
33:37
that's
33:37
a
33:38
hard
33:38
thing
33:38
for
33:38
a
33:38
lot
33:39
of
33:39
retailers
33:39
to
33:40
find
33:40
is,
33:40
is
33:40
good
33:41
service
33:41
right
33:41
now.
33:43
So
33:43
I
33:43
think
33:43
that
33:43
this,
33:44
this
33:44
is
33:44
Aldi
33:45
making
33:45
a
33:45
strong
33:46
investment
33:46
here.
33:47
Whether
33:47
or
33:47
not
33:47
it
33:47
pays
33:48
off
33:48
still,
33:49
still
33:49
to
33:49
be
33:50
determined.
33:50
But
33:51
I'm
33:51
curious
33:51
if
33:52
you
33:52
are
33:52
buying
33:53
or
33:53
selling
33:53
this,
33:54
Chris,
33:55
you
33:55
can
33:56
probably.
33:56
Tell
33:56
what
33:56
I'm
33:56
thinking
33:56
based
33:57
on
33:57
how
33:57
I
33:57
responded
33:58
to
33:58
your
33:58
initial
33:58
take.
34:00
Well,
34:00
so
34:00
as
34:01
an
34:01
actual
34:01
recruitment
34:02
tool,
34:02
I'm
34:02
selling
34:02
this,
34:04
but
34:04
as
34:04
a
34:04
feel
34:04
good
34:05
branding
34:05
story,
34:05
which
34:06
I
34:06
think
34:06
you
34:06
just,
34:06
you
34:07
just
34:07
pretty
34:07
much
34:08
outlined
34:08
the
34:08
case
34:08
for
34:09
that.
34:09
I'm
34:10
buying
34:10
that.
34:10
Like,
34:10
I
34:11
think
34:11
it's
34:11
a,
34:11
it's
34:11
a
34:12
great
34:12
branding
34:12
story
34:12
for
34:12
Aldi,
34:14
but
34:15
the
34:15
reason
34:15
I'm
34:15
selling
34:16
it
34:16
as
34:16
a
34:16
recruitment,
34:17
yeah,
34:17
I
34:18
just,
34:18
I
34:18
just
34:18
don't
34:18
think
34:19
it's
34:19
grounded
34:19
in
34:19
the
34:19
reality
34:20
of
34:20
how
34:20
this
34:20
actually
34:21
works.
34:22
And
34:22
the
34:22
reason
34:22
I
34:23
say
34:23
that
34:23
is
34:23
I
34:24
spoke
34:24
to
34:25
Natalia
34:25
Wallenberg,
34:26
the
34:26
chief
34:27
human
34:27
resources
34:27
officer
34:28
at
34:28
AJO
34:29
Delez,
34:30
on
34:30
stage
34:30
here
34:31
at
34:31
this
34:31
conference
34:31
on
34:32
Monday
34:32
at
34:32
Shop
34:32
Talk
34:32
Europe.
34:33
And
34:34
she
34:34
said,
34:34
she
34:35
talked
34:35
about
34:35
very
34:36
extensively
34:36
how
34:37
they've
34:37
built
34:37
the
34:38
process
34:38
by
34:39
which
34:39
they
34:39
can
34:40
reject
34:41
or
34:41
accept
34:42
an
34:42
application
34:43
to
34:43
work
34:43
in
34:43
their
34:43
grocery
34:44
stores
34:44
in
34:44
eight
34:44
minutes.
34:45
So
34:45
that
34:46
tells
34:46
you
34:46
the
34:46
amount
34:46
of
34:47
traffic
34:47
that's
34:48
coming
34:48
through
34:48
and
34:48
how
34:49
quickly
34:49
they
34:49
need
34:49
to
34:50
short
34:50
through
34:50
it
34:50
and
34:50
how
34:51
often
34:51
they're
34:51
having
34:51
to
34:51
replace
34:52
the
34:52
labor
34:52
in
34:52
the
34:53
grocery
34:53
industry.
34:54
Right.
34:54
So
34:55
you
34:55
have
34:55
to
34:55
move
34:55
really
34:56
fast,
34:56
fast
34:57
to,
34:57
to
34:57
actually
34:58
get
34:58
the
34:58
benefit
34:58
out
34:59
of
34:59
this,
34:59
which
34:59
is
34:59
kind
35:00
of
35:00
antithetical
35:00
to
35:01
like
35:01
sitting
35:02
down,
35:02
taking
35:02
a
35:03
training
35:03
course,
35:03
all
35:03
that
35:04
kind
35:04
of
35:04
stuff.
35:04
And
35:05
you
35:05
know,
35:05
how
35:05
much
35:05
evaluation
35:06
is
35:06
really
35:06
going
35:07
into
35:07
it,
35:07
you
35:07
know,
35:07
at
35:08
this,
35:08
at
35:08
the
35:08
grocery
35:09
store
35:09
entry
35:10
level.
35:11
So
35:11
I
35:11
think
35:11
programs
35:12
like
35:12
this
35:12
sound
35:13
good,
35:13
but
35:14
they
35:14
don't
35:14
really
35:15
move
35:15
the
35:15
needle
35:16
to
35:16
me
35:16
and
35:16
actually
35:17
getting
35:17
people
35:18
into
35:18
the
35:19
door
35:19
and
35:19
through
35:19
the
35:19
vetting
35:20
process,
35:20
which
35:20
is
35:21
really
35:21
what
35:21
you
35:21
need,
35:22
you
35:22
know,
35:23
at
35:23
the
35:23
end
35:23
of
35:23
the
35:23
day.
35:23
So
35:23
I
35:24
don't,
35:24
I
35:24
don't
35:24
know.
35:24
I'm,
35:24
I'm,
35:25
I'm,
35:25
I'm
35:25
skeptical
35:26
of
35:26
this
35:26
one.
35:26
Do
35:26
you,
35:26
could
35:27
you
35:27
see
35:27
a
35:27
world
35:27
where,
35:28
could
35:28
you
35:29
see
35:29
a
35:29
world
35:29
where,
35:30
you
35:31
know,
35:31
like
35:31
before
35:32
the
35:32
first
35:32
interview,
35:33
like
35:33
yes,
35:33
you
35:33
have
35:33
the
35:34
eight
35:34
minute
35:34
process
35:34
of
35:35
acceptance
35:36
for
35:36
an
35:36
interview
35:36
or
35:37
rejection.
35:38
Could
35:38
you
35:38
see
35:38
a
35:38
world
35:39
where
35:39
they're
35:39
using
35:40
something
35:40
like
35:40
this
35:41
pre
35:41
in
35:42
person
35:42
interview
35:43
like
35:43
you
35:43
made
35:43
it
35:43
into
35:44
the
35:44
next
35:44
round.
35:44
This
35:45
is
35:45
like
35:45
a
35:45
qualifier
35:46
or
35:46
some
35:46
component
35:47
of.
35:47
This
35:47
is
35:47
a
35:47
qualifier
35:48
for,
35:48
for
35:49
making
35:49
it
35:49
to
35:49
an
35:49
in
35:49
person
35:50
interview
35:51
or
35:51
no.
35:51
You
35:51
don't
35:51
think
35:51
it's
35:52
worth
35:52
it?
35:52
You
35:52
can
35:52
tell
35:53
right
35:53
away?
35:54
Yeah,
35:54
I
35:56
don't
35:56
know.
35:57
Having
35:57
worked
35:57
in
35:57
the
35:57
stores,
35:58
I
35:58
just
35:58
find
35:58
it
35:59
hard
35:59
to
35:59
believe
36:00
that
36:00
the
36:00
average
36:00
person
36:01
applying
36:01
for
36:01
an
36:01
entry
36:02
level
36:02
job
36:02
is
36:02
going
36:03
to
36:03
take
36:03
the
36:03
time
36:03
to
36:04
do
36:04
that.
36:04
Number
36:05
one,
36:05
you
36:06
could
36:06
mandate
36:06
it,
36:07
I
36:07
guess
36:07
as
36:07
part
36:07
of
36:08
your
36:08
application
36:08
process,
36:09
which
36:09
would
36:09
be
36:09
good.
36:10
But
36:10
I
36:10
worry
36:10
then
36:11
that
36:11
you're
36:11
shutting
36:11
down
36:11
the
36:11
funnel
36:12
too
36:12
much
36:12
as
36:13
well
36:13
versus
36:14
just
36:14
getting
36:14
them
36:14
in
36:14
and
36:15
doing
36:15
the
36:15
on
36:15
the
36:15
job
36:16
training
36:16
based
36:16
on
36:16
the
36:17
typical
36:17
criteria
36:18
you
36:18
screen
36:18
for.
36:20
So
36:21
yeah,
36:21
that,
36:21
that's
36:21
what's
36:21
going
36:21
through
36:22
my
36:22
head
36:22
right
36:22
now.
36:22
To
36:22
answer
36:23
your
36:23
question,
36:23
Anne,
36:23
I,
36:24
I.
36:24
Guess
36:24
I'm
36:24
just
36:25
curious.
36:25
Like
36:26
yes,
36:27
you,
36:27
I
36:27
mean,
36:27
yes,
36:27
they
36:28
can,
36:28
they've
36:28
got
36:28
the
36:28
process
36:29
down
36:29
to
36:29
eight
36:30
minutes
36:30
at
36:30
Ahold.
36:31
But
36:31
are
36:32
they.
36:32
Would
36:32
it,
36:32
would
36:33
it
36:33
be
36:33
a
36:33
more
36:33
worthwhile
36:34
investment
36:34
to
36:34
spend
36:35
more
36:35
time
36:35
in
36:36
some
36:36
of
36:36
those
36:36
entry
36:37
level
36:37
jobs
36:38
to
36:38
invest
36:38
more
36:39
so
36:39
that
36:39
there's
36:39
less
36:40
turnover
36:40
so
36:41
that
36:41
you're,
36:41
you're
36:41
only
36:42
doing
36:42
this
36:42
one,
36:42
you
36:43
know.
36:43
Yeah.
36:44
And
36:44
all.
36:44
And
36:45
I
36:45
use
36:45
the
36:45
Ahold
36:45
example
36:45
just
36:46
to
36:46
talk,
36:46
talk
36:46
just
36:46
to
36:47
illustrate
36:47
the
36:47
speed
36:48
at
36:48
which,
36:48
you
36:48
know,
36:48
things
36:49
are
36:49
happening.
36:50
But
36:50
you
36:50
know.
36:51
Yes,
36:51
100
36:51
Ah,
36:52
hold.
36:52
Spent
36:52
a
36:52
lot
36:53
of
36:53
time
36:53
on
36:53
stage
36:53
talking
36:54
about
36:54
the
36:54
additional
36:55
on
36:55
the
36:55
job
36:56
training
36:56
they're
36:56
trying
36:57
to
36:57
give
36:57
people
36:57
too
36:58
and
36:58
the
36:58
tools
36:58
and
36:58
resources
36:59
that
36:59
they
36:59
want
36:59
to
37:00
give
37:00
them
37:00
to
37:00
help
37:00
them
37:00
do
37:01
the
37:01
job
37:01
so
37:01
that
37:02
they're
37:02
getting
37:02
people
37:02
in
37:03
quickly
37:03
because
37:03
it's,
37:04
it's
37:04
about,
37:04
it's
37:05
always,
37:05
it's
37:05
about
37:05
hiring,
37:06
training
37:06
and
37:06
retention,
37:07
those
37:07
three
37:07
things.
37:07
And
37:08
so
37:08
you
37:08
have
37:08
to
37:08
have
37:08
all
37:09
of
37:09
that.
37:09
And
37:10
this
37:10
one,
37:11
this
37:11
one
37:12
kind
37:12
of
37:12
falls
37:13
in
37:13
the
37:13
netherworld
37:13
of
37:13
that
37:14
when
37:14
you
37:14
think
37:14
about
37:14
the
37:14
actual
37:15
employee
37:15
because
37:15
it's
37:15
more
37:16
about
37:16
giving
37:17
education
37:17
and
37:18
certification
37:18
to
37:19
someone
37:19
that
37:19
could
37:19
eventually
37:20
work
37:20
for
37:20
you
37:21
and
37:22
it
37:22
even
37:22
leans
37:22
more
37:22
towards
37:23
like
37:23
the
37:23
office
37:23
side
37:24
of
37:24
it,
37:24
like
37:24
a
37:24
career
37:25
in
37:25
retail.
37:26
So
37:26
like
37:27
that's
37:27
where
37:27
it's
37:27
just.
37:28
This
37:28
one
37:28
feels
37:29
a
37:29
little
37:29
dissonant.
37:29
To
37:30
me
37:30
in
37:30
terms
37:30
of
37:30
how
37:30
it
37:30
fits
37:30
into
37:31
the
37:31
whole
37:31
pie.
37:31
But,
37:32
but
37:32
I
37:32
could
37:32
be
37:32
wrong.
37:33
I
37:33
think
37:33
Net
37:33
net
37:33
though,
37:34
it's
37:34
still
37:34
a
37:34
great
37:34
branding
37:35
story.
37:35
Yeah,
37:36
I
37:36
agree.
37:37
Well,
37:37
we'll
37:37
have
37:38
to
37:38
see.
37:38
I'll
37:38
make
37:38
my
37:39
14
37:39
year
37:39
old
37:39
go
37:40
through
37:40
this
37:40
process
37:40
in
37:41
full
37:41
and
37:42
then
37:42
I'll
37:42
report
37:42
back.
37:44
All
37:44
right,
37:44
let's
37:44
go
37:44
to
37:44
the
37:44
last
37:45
headline.
37:45
Chris
37:45
David's
37:46
Bridal
37:46
has
37:47
unveiled
37:47
a
37:47
new
37:48
store
37:48
concept.
37:49
It
37:49
is
37:49
calling
37:50
Diamonds
37:50
and
37:51
Pearls
37:51
one
37:51
of
37:52
maybe
37:52
the
37:52
greatest
37:52
Prince
37:53
songs
37:53
ever.
37:53
And
37:54
hopefully
37:54
they
37:55
are
37:55
giving
37:55
him
37:55
his
37:56
just
37:56
dues
37:56
for
37:57
taking
37:57
that
37:58
name.
37:59
According
37:59
to
37:59
Retail
38:00
Dive,
38:00
the
38:00
store
38:00
features
38:01
a
38:01
curated
38:01
selection
38:02
of
38:02
bridal
38:02
fashion
38:03
and
38:03
accessories,
38:04
personal
38:04
styling,
38:05
Shopify
38:05
point
38:06
of
38:06
sale,
38:06
integration
38:06
for
38:07
in
38:07
store
38:07
and
38:07
online
38:07
shoppers,
38:08
champagne
38:09
service,
38:09
alterations
38:10
and
38:11
luxury
38:11
trunk
38:12
shows.
38:12
The
38:13
store
38:13
also
38:13
carries
38:14
exclusives
38:14
not
38:15
available
38:15
at
38:15
other
38:15
David's
38:16
Bridal
38:16
locations.
38:17
Beyond
38:18
launching
38:18
a
38:18
new
38:18
store
38:19
concept,
38:19
the
38:19
retailer
38:20
has
38:20
also
38:20
expanded
38:21
its
38:21
product
38:21
assortment.
38:22
David's
38:22
Bridal
38:23
recently
38:23
teamed
38:24
up
38:24
with
38:24
Perry
38:24
Ellis
38:25
and
38:25
Cubavera
38:26
to
38:26
debut
38:27
its
38:27
first
38:27
menswear
38:28
collection.
38:29
The
38:29
retailer
38:29
released
38:30
suits
38:30
in
38:31
April
38:31
and
38:31
is
38:31
rolling
38:31
out
38:32
Cuba
38:32
Vera
38:32
items
38:33
over
38:33
the
38:33
summer.
38:34
Chris,
38:35
do
38:36
you
38:36
think
38:36
the
38:36
David's
38:37
Bridal
38:38
Store
38:38
new
38:38
store
38:39
concept,
38:39
Diamonds
38:40
and
38:40
Pearls
38:40
will
38:40
catch
38:41
on?
38:42
Oh
38:42
man,
38:43
I
38:43
feel
38:44
like,
38:44
I
38:44
feel
38:44
like
38:44
I'm,
38:44
I
38:45
feel
38:45
like
38:45
I'm
38:45
a
38:45
downer
38:45
on
38:45
this
38:46
podcast.
38:46
I
38:46
don't
38:46
feel
38:46
like
38:46
there's
38:47
anything
38:47
I've.
38:47
Well,
38:47
I,
38:47
I
38:48
guess
38:48
I
38:48
started
38:48
out.
38:48
Really?
38:49
You
38:49
started
38:49
out
38:49
with
38:49
Walmart?
38:50
Yeah,
38:50
I
38:50
lauded
38:51
Walmart.
38:51
Yeah.
38:51
Which
38:52
is
38:52
typical.
38:52
So,
38:53
yeah,
38:53
but
38:53
I,
38:53
I'm
38:54
skeptical
38:54
of
38:54
this
38:54
one
38:54
too.
38:55
And
38:55
I
38:55
think,
38:55
you
38:55
know,
38:56
I
38:56
mean,
38:57
for
38:57
a
38:57
number
38:57
of
38:57
reasons,
38:57
like,
38:57
and
38:58
endless
38:58
aisle
38:58
as
38:59
a
38:59
differentiator,
39:00
especially
39:00
in
39:00
a
39:01
physical
39:01
store
39:01
concept,
39:02
doesn't
39:02
mean
39:03
that
39:03
much
39:03
to
39:03
me
39:03
because,
39:04
you
39:04
know,
39:04
who
39:04
already
39:04
has
39:05
an
39:05
endless
39:05
aisle
39:05
in
39:06
the
39:06
online
39:07
sphere,
39:07
like,
39:08
okay,
39:08
fine,
39:09
I
39:09
can
39:09
go
39:09
into
39:09
a
39:09
store
39:10
and
39:10
I
39:10
can
39:10
look
39:10
things
39:10
up
39:11
online.
39:11
Like
39:11
that
39:12
just
39:12
doesn't
39:12
resonate
39:13
with
39:13
me.
39:13
And
39:13
we've
39:13
talked
39:14
over
39:14
and
39:14
over
39:14
again
39:14
in
39:15
the
39:15
eight
39:15
year
39:15
history
39:15
of
39:15
our
39:15
show
39:16
about
39:16
how
39:16
that's
39:16
kind
39:17
of
39:17
Fool's
39:17
gold.
39:18
So
39:18
that's
39:18
number
39:18
one.
39:19
The
39:19
second
39:19
point
39:19
I
39:20
make
39:20
is
39:21
promoting
39:21
the
39:21
Shopify
39:22
integration.
39:23
Who
39:23
cares?
39:24
Like
39:25
that
39:25
sounds
39:26
like
39:26
something
39:26
to
39:26
me
39:27
that,
39:27
you
39:27
know,
39:27
you
39:28
throw
39:28
it,
39:28
you
39:28
throw
39:29
in
39:29
to
39:29
sound
39:29
techie.
39:30
Right.
39:30
But
39:30
it's
39:31
really
39:31
a
39:31
tell
39:31
that
39:31
you
39:32
aren't
39:32
that
39:32
techie
39:33
in
39:33
my
39:33
opinion.
39:33
Like,
39:34
and
39:34
Shopify
39:34
has
39:35
its
39:35
limitations
39:35
as
39:36
a
39:36
POS
39:37
platform
39:37
from
39:37
my
39:37
understanding
39:38
too.
39:38
So.
39:40
So
39:40
no,
39:40
I
39:41
think
39:41
for
39:41
me
39:41
this
39:41
is
39:42
going
39:42
to
39:42
be
39:42
a
39:42
tough
39:42
get.
39:43
You
39:44
know,
39:44
had
39:44
they,
39:45
had
39:45
they
39:45
actually
39:46
brought
39:46
the
39:46
menswear
39:46
concept
39:47
into
39:47
a
39:47
combined
39:48
concept.
39:48
I
39:48
think
39:49
that's
39:49
a
39:49
better
39:49
way
39:49
to
39:50
go
39:50
because
39:50
I
39:51
would
39:51
be
39:51
interested
39:51
in
39:51
that.
39:52
Like,
39:52
yeah,
39:52
incremental
39:53
hook
39:53
there.
39:54
Like
39:54
dudes,
39:54
when
39:54
they
39:54
have
39:54
to
39:54
get
39:54
their
39:55
tuxes
39:55
for
39:55
the
39:55
wedding,
39:55
they
39:56
don't
39:56
care
39:56
where
39:56
they
39:56
go.
39:57
So
39:57
why
39:57
are
39:57
you
39:58
letting
39:58
that
39:58
business
39:58
go
39:58
somewhere
39:59
else?
39:59
Bring
39:59
it
39:59
together,
40:00
make
40:00
the
40:00
unit
40:01
more
40:01
productive.
40:02
It's
40:02
kind
40:02
of
40:02
the
40:02
old
40:03
like
40:03
consulting
40:04
case
40:04
in
40:04
business
40:04
school
40:05
of
40:05
like,
40:05
you
40:05
know,
40:06
how
40:06
do
40:06
you
40:06
get
40:06
the
40:06
fast
40:07
food
40:07
restaurant
40:07
to
40:07
do
40:08
breakfast,
40:08
lunch
40:08
and
40:09
dinner
40:09
more
40:09
continuously?
40:10
How
40:10
do
40:10
you
40:10
use
40:10
the
40:10
unused
40:11
times
40:11
of
40:12
the
40:12
day
40:12
to
40:12
be
40:12
more
40:12
productive?
40:13
So
40:13
like
40:13
that
40:14
I
40:14
think
40:14
could
40:14
work.
40:15
But,
40:15
but
40:15
as,
40:15
as
40:16
a,
40:16
as
40:16
a
40:17
plan
40:17
to
40:17
like
40:18
stave
40:18
off
40:18
what's
40:19
already
40:19
happening
40:19
endemically
40:20
to
40:20
David's
40:21
Bridal.
40:21
I
40:21
just
40:22
think
40:22
this
40:22
is
40:22
another
40:22
concept
40:23
that's
40:23
probably
40:24
not
40:24
going
40:24
to
40:24
work
40:24
in
40:24
the
40:25
long
40:25
run.
40:25
Really?
40:26
I.
40:26
Well,
40:27
one,
40:27
you
40:27
don't
40:27
want
40:28
the
40:28
guys
40:28
in
40:29
the
40:29
same
40:29
bridal
40:30
shop.
40:30
Like
40:31
that's
40:31
not
40:31
a
40:31
good
40:31
idea.
40:32
You're
40:32
not
40:32
supposed
40:32
to
40:32
see
40:33
the
40:33
bride
40:33
before.
40:34
But
40:34
I
40:35
don't
40:35
think
40:35
that
40:35
there's
40:36
anything
40:36
stopping
40:37
you.
40:37
I
40:37
do
40:37
think
40:37
that
40:38
you're
40:38
on
40:38
the
40:38
right
40:38
track
40:39
of
40:39
this
40:39
idea
40:40
could
40:40
live
40:40
on
40:41
its
40:41
own
40:41
as
40:42
a
40:42
male
40:42
concept
40:43
for
40:43
me.
40:44
I
40:44
think
40:44
this
40:44
is
40:45
a
40:45
brilliant
40:45
idea.
40:45
Chris.
40:46
I
40:46
actually
40:46
love
40:47
the
40:47
idea
40:47
of
40:48
bringing
40:48
service.
40:49
You
40:49
think
40:49
about
40:50
the
40:50
things
40:50
that
40:50
they're
40:50
talking
40:50
about
40:51
here.
40:51
Champagne,
40:52
these
40:52
little
40:53
touches,
40:53
they're,
40:53
they're
40:54
doing
40:54
trunk
40:54
shows.
40:55
They're
40:55
really
40:56
focusing
40:57
here
40:57
on
40:57
service
40:58
and
40:58
creating
40:59
a
40:59
luxury
40:59
experience
41:00
that
41:00
you
41:01
have
41:01
not
41:01
gotten
41:02
before
41:02
at
41:03
a
41:03
David's
41:03
Bridal.
41:04
You're
41:04
now
41:04
giving
41:05
this
41:05
high
41:05
touch,
41:06
high
41:06
service
41:07
experience
41:08
at
41:08
a
41:08
lower
41:09
price
41:09
point
41:09
product.
41:10
And
41:10
I
41:10
love
41:11
this.
41:11
I
41:11
think
41:11
it's
41:11
something
41:12
that
41:12
we
41:12
all
41:12
need
41:13
to
41:13
be
41:13
paying
41:13
more
41:14
close
41:14
attention
41:14
to.
41:15
Again,
41:15
something
41:15
that
41:15
we're
41:16
hearing
41:16
a
41:16
lot
41:16
about
41:17
at
41:18
Shop
41:18
Talk
41:18
Europe
41:18
is
41:19
this
41:19
emphasis
41:20
on
41:20
service
41:21
that
41:21
isn't
41:21
just
41:22
at
41:22
the
41:22
luxury
41:23
level
41:23
that
41:23
you
41:24
like.
41:24
If
41:24
we
41:24
started
41:25
seeing
41:25
more
41:25
retailers
41:26
like
41:26
this,
41:27
like
41:27
a
41:27
David's
41:27
Bridal,
41:28
really
41:28
lean
41:29
in
41:29
on
41:29
experience.
41:30
It's,
41:30
it's
41:30
the
41:31
one
41:31
thing
41:31
that
41:31
I
41:31
think
41:32
can
41:32
differentiate
41:33
them
41:33
right
41:33
now
41:33
because
41:34
no
41:34
one
41:34
else
41:34
is
41:35
doing
41:35
this.
41:36
It's
41:36
like
41:36
you
41:36
go
41:37
into
41:37
a
41:37
Macy's
41:37
Bridal,
41:38
you
41:38
go
41:38
into
41:38
another,
41:39
any
41:39
other
41:39
category.
41:40
Like
41:40
you
41:40
just,
41:40
you
41:41
don't
41:41
get
41:41
the
41:41
level
41:41
of
41:42
service
41:42
anymore.
41:42
It's
41:43
all
41:43
about
41:43
transaction
41:44
and
41:44
having
41:45
the
41:45
least
41:45
amount
41:45
of
41:45
people
41:46
on
41:46
the
41:46
floor.
41:46
And
41:46
I
41:47
think
41:47
this
41:47
is
41:47
one
41:48
of
41:48
these
41:48
experiences
41:49
where
41:49
if
41:49
I
41:49
was
41:49
at
41:49
David's
41:50
Bridal
41:50
right
41:50
Now,
41:50
I
41:50
would
41:51
100%
41:51
be
41:51
testing
41:52
a
41:52
concept
41:52
like
41:52
this.
41:53
And
41:53
for
41:53
the
41:53
men
41:54
too,
41:54
like
41:54
Making
41:55
this
41:55
an
41:55
experience
41:55
where
41:56
you
41:56
all
41:56
go
41:56
pick
41:56
out
41:56
your
41:56
tuxes,
41:57
there's
41:57
a
41:58
whiskey
41:58
bar,
41:58
there's
41:59
other
41:59
things
41:59
like
41:59
that's
42:00
what
42:00
you
42:00
get
42:00
at
42:00
the
42:00
high
42:01
end
42:01
experience.
42:02
And
42:02
I
42:02
think
42:02
that
42:03
if
42:03
they
42:03
can
42:04
pull
42:04
this
42:04
off
42:05
and
42:05
really
42:05
invest
42:06
in
42:06
service
42:06
and
42:06
this
42:07
high
42:07
touch,
42:07
I
42:08
think
42:08
that
42:08
they
42:08
could
42:09
be
42:09
doing
42:10
a
42:10
banger
42:11
business
42:11
right
42:12
now
42:12
and
42:13
really
42:13
start
42:13
to
42:14
stand
42:14
apart
42:14
from
42:14
their
42:14
competitors.
42:15
Because
42:15
who
42:15
doesn't
42:16
want
42:16
great
42:16
service
42:17
and
42:17
an
42:18
affordably
42:18
priced
42:19
product?
42:19
I
42:19
think
42:19
we're
42:19
going
42:20
to
42:20
start
42:20
to
42:20
see
42:20
people
42:21
coming
42:21
down
42:21
from
42:21
those
42:22
luxury
42:22
bridal
42:23
experiences
42:23
just
42:23
because
42:24
you
42:24
have
42:24
a
42:24
more
42:24
cost
42:24
conscious
42:25
consumer.
42:25
But
42:26
yeah,
42:27
so
42:27
I
42:27
think
42:27
of
42:27
two
42:28
things
42:28
in
42:28
response
42:28
to
42:28
that.
42:29
So
42:29
number
42:29
one,
42:29
you
42:30
know,
42:30
the
42:30
thing
42:30
about
42:30
the
42:31
men,
42:31
like
42:31
I
42:31
think,
42:32
you
42:32
know,
42:32
you
42:32
can,
42:33
you
42:33
can
42:33
solve
42:33
that
42:33
architecture,
42:34
you
42:34
can
42:34
solve
42:34
that
42:35
through
42:35
scheduling
42:35
and
42:36
oftentimes
42:36
too
42:36
like
42:37
the
42:37
men
42:37
shop
42:37
at
42:37
a
42:38
different
42:38
time
42:38
than
42:38
the
42:38
women
42:38
do
42:39
for
42:39
the
42:39
dresses.
42:40
So
42:40
I
42:40
don't
42:40
think
42:40
the
42:40
fear
42:40
of
42:41
seeing
42:41
the
42:42
bride
42:42
in
42:42
her
42:42
wedding
42:42
gown
42:42
is
42:43
really
42:43
that,
42:43
that
42:44
of
42:44
an,
42:44
that
42:44
much
42:44
of
42:44
an
42:45
issue.
42:45
But
42:46
the
42:46
second
42:46
thing,
42:46
like,
42:46
yeah,
42:46
I
42:47
agree
42:47
everybody
42:47
wants
42:47
better
42:48
service,
42:48
but
42:49
the
42:49
trick
42:49
with
42:49
providing
42:50
better
42:50
services,
42:51
you
42:51
need
42:51
to
42:51
pay
42:51
for
42:52
it.
42:52
And
42:53
so
42:53
that's
42:53
what's
42:53
unclear
42:54
to
42:54
me
42:54
in
42:54
terms
42:55
of,
42:55
you
42:55
know,
42:56
how
42:56
are
42:56
they
42:56
getting
42:56
the
42:57
margins
42:57
from
42:58
this
42:58
concept
42:59
to
42:59
pay
42:59
for
43:00
it.
43:00
You
43:00
can
43:00
just,
43:01
you
43:01
can't
43:01
just
43:01
wave
43:02
your
43:02
wand
43:02
and
43:02
give
43:02
better
43:03
service.
43:03
Yeah,
43:05
so
43:05
that
43:05
to
43:05
me
43:05
is,
43:06
is
43:06
the
43:06
element
43:07
that
43:07
was
43:07
missing
43:07
here.
43:08
It
43:08
sounds
43:08
like
43:08
they're
43:09
trying
43:09
to
43:09
put
43:09
some
43:09
higher
43:09
end
43:10
products
43:10
in,
43:10
but
43:10
yet
43:11
they're
43:11
going
43:11
to
43:11
have
43:11
a
43:12
smaller
43:12
array
43:12
of
43:13
products.
43:13
So,
43:14
so,
43:14
so
43:14
maybe,
43:15
but
43:15
it's
43:16
hard
43:16
to
43:16
become
43:16
something
43:17
that
43:17
you're
43:17
not.
43:18
And,
43:18
and
43:19
companies
43:20
have
43:20
failed
43:20
on
43:20
this
43:21
attempt
43:21
many,
43:21
many
43:22
times
43:22
over
43:22
the
43:22
year
43:22
because
43:23
they
43:23
forget
43:23
that,
43:24
you
43:24
know,
43:24
margins,
43:26
the
43:26
level
43:26
of
43:27
margin
43:27
that
43:27
you
43:27
have
43:28
is
43:28
correlated
43:28
to
43:29
the
43:29
amount
43:29
of
43:29
service
43:29
you
43:30
can
43:30
provide.
43:31
And
43:32
that's
43:32
what
43:32
makes
43:32
this
43:33
such
43:33
a
43:33
difficult
43:34
get
43:34
when
43:35
you
43:35
try
43:35
to
43:35
move
43:35
up
43:35
market
43:36
in
43:36
service.
43:37
And
43:37
I
43:37
just
43:37
don't
43:37
see
43:38
that
43:38
from
43:38
this
43:38
concept.
43:39
Yeah,
43:39
I
43:39
think
43:40
that's
43:40
the
43:40
big,
43:41
that's
43:41
the
43:42
big
43:42
issue
43:42
though
43:42
that
43:43
these
43:43
retailers
43:43
are
43:43
going
43:43
to
43:44
have
43:44
to
43:44
contend
43:44
with
43:44
right
43:45
now.
43:45
I
43:45
mean,
43:45
I
43:45
think
43:45
that's
43:46
where
43:46
things
43:46
like
43:46
AI
43:47
come
43:47
into
43:47
play.
43:48
Like
43:48
where
43:48
are
43:49
you
43:49
able
43:49
to
43:49
save
43:50
money,
43:50
use
43:51
leveraging
43:51
AI
43:52
in
43:52
your
43:52
businesses
43:52
so
43:53
that
43:53
you
43:53
can
43:54
find
43:54
some
43:54
of
43:55
that
43:55
additional
43:56
revenue
43:57
to
43:57
put
43:57
towards
43:58
service.
43:58
I
43:58
just,
43:58
I
43:59
think
43:59
it's
43:59
going
43:59
to
43:59
be
43:59
too,
44:00
too
44:00
much
44:00
of
44:01
a
44:01
determining
44:02
factor
44:02
in
44:02
the
44:03
success
44:03
of
44:03
a
44:03
business
44:04
overall
44:05
if
44:05
they're
44:06
not
44:06
willing
44:07
to
44:07
invest
44:07
here
44:07
because
44:08
this
44:08
is
44:09
too
44:09
high.
44:09
Touch
44:09
of
44:09
an
44:10
experience.
44:10
Shopping
44:10
for
44:10
a
44:11
wedding
44:11
gown
44:11
is
44:11
too
44:12
high
44:12
touch
44:12
of
44:13
an
44:13
experience
44:13
to,
44:14
to
44:14
let
44:14
that
44:15
service
44:15
element
44:15
decline.
44:16
So.
44:16
Oh,
44:17
okay,
44:17
let
44:17
me
44:17
just
44:17
press
44:17
you
44:18
on
44:18
that.
44:18
Yeah.
44:18
Because
44:19
like,
44:19
if
44:19
that's
44:20
the
44:20
case,
44:21
should
44:21
your
44:22
new
44:22
store
44:22
concept
44:23
be
44:23
dependent
44:24
upon
44:24
that?
44:25
I
44:25
think
44:26
that's
44:26
a
44:26
tough
44:28
service
44:29
be
44:29
dependent
44:30
on
44:30
you
44:30
leveraging
44:31
new
44:31
techniques
44:32
in
44:32
AI
44:32
to
44:33
make
44:33
it
44:33
work
44:33
financially.
44:34
I
44:34
think
44:34
that's
44:35
a
44:35
tough
44:35
ask.
44:35
No,
44:36
I
44:36
took
44:36
a
44:36
company
44:37
that's
44:37
calling
44:37
out
44:37
Shopify
44:38
as
44:38
a
44:38
key
44:39
technological
44:39
ingredient
44:40
to
44:40
this
44:40
store
44:40
concept.
44:41
I'm,
44:41
I'm
44:42
saying
44:42
more
44:42
from
44:43
other
44:43
areas
44:43
of
44:43
the
44:43
store.
44:44
I'm
44:44
not
44:44
saying
44:44
AI
44:45
in
44:45
the
44:45
store.
44:45
I
44:45
should
44:46
have
44:46
clarified.
44:46
I'm
44:46
saying
44:47
like,
44:47
overall,
44:48
where
44:48
can
44:48
you,
44:49
where
44:49
are
44:49
you
44:49
as
44:49
a
44:50
business
44:50
applying
44:50
AI
44:51
to
44:52
refine
44:53
and
44:53
find
44:54
more
44:54
efficiencies
44:55
in
44:55
your
44:55
business
44:55
operations
44:56
so
44:56
that
44:57
you
44:57
can
44:57
free
44:57
up
44:58
resources
44:59
to
44:59
pay
45:00
for
45:00
more
45:01
and
45:01
to
45:01
allocate
45:01
that
45:02
to
45:02
better
45:02
service
45:02
in
45:03
the
45:03
stores?
45:03
Because
45:03
that,
45:04
that's,
45:04
that
45:04
to
45:04
me,
45:05
you
45:05
know,
45:05
you're,
45:05
you're,
45:06
a
45:06
lot
45:06
of
45:06
companies
45:07
are
45:07
reducing
45:07
headcount
45:08
right
45:08
now
45:08
at
45:08
the
45:08
headquarters.
45:09
Like
45:09
that's
45:09
what
45:09
I'm
45:10
saying
45:10
is
45:10
if
45:10
you're
45:10
going
45:10
to
45:10
reduce
45:11
headcount
45:11
there,
45:12
can
45:12
you
45:12
start
45:12
to
45:13
put
45:13
this
45:13
back
45:13
into
45:13
service
45:14
in
45:14
the
45:14
stores
45:14
so
45:15
that
45:15
the,
45:15
the
45:15
companies
45:16
stay
45:16
alive
45:16
and
45:17
they
45:17
become
45:18
a
45:18
destination
45:19
for
45:19
shoppers
45:20
right
45:20
now.
45:21
Right.
45:21
Which
45:21
brings
45:22
me
45:22
back
45:22
to
45:22
the
45:22
point
45:22
of,
45:22
yeah,
45:22
if
45:23
you're
45:23
going
45:23
to
45:23
do
45:23
that,
45:23
do
45:23
that
45:23
for
45:24
your
45:24
fleet
45:24
of
45:24
stores
45:24
that
45:25
already
45:25
exist
45:25
because
45:25
you're
45:26
going
45:26
to
45:26
get
45:26
more
45:26
payback
45:27
there
45:27
than
45:27
doing
45:27
it,
45:27
than
45:28
trying
45:28
to
45:28
make
45:28
a
45:28
distracting
45:29
new
45:29
concept
45:30
to
45:30
work
45:30
when
45:31
you
45:31
don't
45:31
have
45:31
that
45:31
figured
45:31
out
45:32
for
45:32
your
45:32
chain
45:32
of
45:32
stores
45:32
already.
45:33
Like,
45:33
I
45:34
don't,
45:34
I,
45:34
I,
45:35
I'm
45:35
actually
45:35
getting
45:35
more
45:36
skeptical
45:36
of
45:36
this
45:36
as
45:37
we
45:37
talk
45:37
about
45:37
it,
45:37
but.
45:38
Well,
45:39
yes,
45:39
more,
45:40
more
45:40
discussion
45:41
to
45:41
be
45:41
had
45:41
on
45:41
this
45:42
topic
45:42
for
45:42
sure.
45:42
But
45:43
for
45:43
now,
45:43
let's
45:43
go
45:44
to
45:44
the
45:44
lightning
45:45
round,
45:46
Chris.
45:46
Oreo
45:47
maker
45:47
Mondelez
45:48
is
45:48
suing
45:49
Aldi,
45:49
alleging
45:50
that
45:50
grocery
45:50
chain
45:51
copies
45:51
its
45:51
packaging
45:52
to
45:52
confuse
45:53
customers.
45:54
What
45:54
own
45:54
brand
45:54
product
45:55
do
45:55
you
45:55
think
45:55
is
45:55
better
45:56
than
45:56
or
45:56
as
45:57
good
45:57
as
45:57
the
45:58
original?
45:59
Oh,
46:00
man,
46:00
you
46:00
know,
46:00
I
46:00
don't,
46:00
I
46:01
don't,
46:01
for
46:01
some
46:01
reason
46:02
I,
46:02
I
46:02
don't,
46:02
I
46:03
don't
46:03
buy
46:03
that
46:03
many
46:03
own
46:04
brand
46:04
products.
46:04
I
46:04
think
46:05
because
46:05
our
46:05
grocery
46:05
stores
46:05
don't
46:06
have
46:06
a
46:06
big
46:06
own
46:06
brand
46:07
assortment
46:07
because
46:07
Minnesota
46:08
groceries
46:08
is
46:08
kind
46:08
of
46:08
unique
46:09
in
46:09
that
46:09
way.
46:09
But
46:11
you
46:11
know,
46:11
for
46:11
me,
46:12
I
46:12
guess
46:12
I'd
46:12
go
46:12
with
46:12
like
46:13
the
46:13
standard,
46:13
like
46:13
OTC
46:14
drugs
46:14
and
46:15
you
46:15
know,
46:15
Mucinex,
46:16
Benadryl,
46:18
like
46:18
Prilosec,
46:19
like
46:19
I'm
46:19
buying
46:19
all
46:19
the
46:19
generics
46:20
of
46:20
Those,
46:20
those
46:20
things
46:21
are
46:21
always
46:21
at
46:21
least
46:22
as
46:22
good,
46:22
or
46:22
at
46:22
least
46:22
my
46:23
body
46:23
tells
46:23
me
46:23
that
46:23
they
46:24
are.
46:24
That's
46:25
great.
46:25
I'm
46:26
glad.
46:26
I'm
46:26
glad
46:26
that
46:27
they
46:27
worked
46:27
for
46:27
you.
46:27
Yes.
46:28
Right.
46:28
Yeah,
46:29
yeah.
46:29
No,
46:29
Trader
46:30
Joe's.
46:30
You
46:30
don't
46:30
do
46:30
any
46:31
of
46:31
like
46:31
the
46:31
Trader
46:31
Joe's
46:32
dupes
46:32
or
46:32
anything.
46:33
I
46:33
guess
46:33
it's
46:33
more
46:33
of
46:33
a
46:34
beauty.
46:34
Thing
46:34
too,
46:36
is
46:36
just
46:36
like.
46:37
Yeah,
46:37
it's
46:37
just
46:37
kind
46:37
of
46:38
like
46:38
it's,
46:38
it's,
46:38
it's,
46:39
it's
46:39
label,
46:39
you
46:39
know,
46:40
I
46:40
don't
46:40
think
46:40
of
46:40
it
46:40
like
46:40
the
46:41
same
46:41
way
46:41
for
46:41
some
46:42
reason.
46:42
I
46:42
don't
46:42
know.
46:42
But.
46:42
Okay.
46:43
I
46:44
mean,
46:44
I
46:44
guess.
46:44
Yeah,
46:44
you
46:44
do
46:45
like
46:45
peanut
46:45
butter
46:45
and
46:45
stuff,
46:46
you
46:46
know,
46:46
but,
46:47
but
46:47
no,
46:47
yeah,
46:47
yeah,
46:48
no,
46:48
I,
46:48
I
46:49
think,
46:49
you
46:49
know,
46:49
I
46:49
like,
46:50
I
46:50
like
46:50
the
46:50
way
46:50
the
46:51
private
46:51
label
46:51
Mucinex,
46:52
you
46:52
know,
46:53
clears
46:53
my
46:53
lungs.
46:54
And
46:54
a
46:54
Kentucky
46:55
mom
46:55
found
46:56
herself
46:56
in
46:56
a
46:56
sticky
46:57
situation
46:57
when
46:57
her
46:57
8
46:57
year
46:58
old
46:58
son
46:58
ordered
46:59
70,000
47:00
dum
47:00
dum
47:01
lollipops.
47:02
Dum
47:02
dums
47:03
on
47:03
her
47:03
phone.
47:04
What
47:04
have
47:04
you
47:04
accidentally
47:05
purchased
47:05
is
47:05
almost
47:06
as
47:06
ridiculous
47:06
as
47:07
70,000
47:07
dum
47:08
dums.
47:09
The
47:10
first
47:10
thing
47:10
that
47:11
I
47:11
thought
47:11
of
47:12
was
47:12
one
47:12
summer
47:13
when
47:13
I
47:13
was
47:14
home
47:14
from
47:14
school.
47:14
My
47:15
mom
47:15
was
47:15
working
47:16
and
47:16
we
47:17
were
47:17
bored
47:18
and
47:18
there
47:19
was
47:19
a.
47:19
How
47:20
old,
47:20
how
47:20
old
47:20
were
47:20
you?
47:20
Probably
47:22
eight
47:22
or
47:22
nine.
47:23
I
47:23
mean,
47:24
it
47:24
was,
47:24
it
47:24
was
47:24
like
47:25
in
47:25
elementary
47:26
school
47:26
and
47:27
my
47:27
brother
47:27
and
47:27
I
47:27
were
47:27
bored.
47:28
So
47:29
there
47:29
was
47:29
an
47:29
ad
47:30
during
47:31
the
47:31
daytime
47:32
soap
47:32
operas
47:32
for,
47:33
for
47:33
the
47:33
Book
47:34
of
47:34
Mormon
47:35
and
47:35
they
47:35
said
47:36
they
47:36
would
47:36
send
47:36
you
47:36
a
47:37
free
47:37
book.
47:37
And
47:37
I
47:37
was
47:38
like,
47:38
yes,
47:39
I'll
47:39
take
47:39
a
47:39
free
47:39
book.
47:40
Like,
47:40
let's
47:40
check
47:40
it
47:41
out.
47:41
We're
47:41
bored.
47:42
And
47:42
sure
47:43
enough,
47:43
they
47:43
sent
47:44
us
47:44
the
47:44
Book
47:44
of
47:44
Mormon
47:45
and
47:45
we
47:45
had
47:46
visitors
47:46
from
47:46
the
47:47
LDS
47:47
Church
47:48
at
47:48
our
47:48
house
47:48
for
47:49
maybe
47:49
the
47:49
next
47:49
next
47:50
five
47:50
years,
47:50
calling,
47:51
stopping
47:52
by
47:52
the
47:52
house,
47:53
trying
47:53
to
47:53
talk
47:53
to
47:53
my
47:53
mom
47:54
and
47:54
get
47:54
her
47:54
on
47:55
board.
47:55
And
47:55
she
47:55
was
47:56
not
47:56
thrilled.
47:56
She
47:57
would
47:57
not
47:57
let
47:57
me
47:57
live
47:57
that
47:58
one
47:58
down.
47:58
So.
47:58
Didn't
47:59
cost
47:59
her
47:59
as
47:59
much
48:00
as
48:00
70,000
48:00
dum
48:01
dums.
48:01
Yeah.
48:01
No,
48:02
just
48:02
her
48:02
time
48:03
and
48:03
patience.
48:04
Yeah,
48:05
that
48:05
must
48:05
have
48:05
been
48:05
one
48:05
hell
48:06
of
48:06
a
48:06
bill,
48:06
the
48:06
70,000
48:07
dum
48:07
dums.
48:08
My
48:08
God.
48:09
Oh.
48:09
All
48:09
right,
48:10
Chris,
48:10
question
48:10
number
48:11
three.
48:11
The
48:11
creator
48:12
of
48:12
Succession
48:13
reportedly
48:14
skewers
48:15
tech
48:15
billionaires
48:16
in
48:16
his
48:16
latest
48:16
film,
48:17
Mountainhead.
48:18
Will
48:18
Mountain
48:18
head
48:19
be
48:19
must
48:19
see
48:20
TV
48:20
for
48:20
you?
48:21
Oh
48:22
my
48:22
God,
48:22
yes,
48:22
100%.
48:23
I'm
48:23
actually
48:23
dying
48:24
to
48:24
watch
48:24
this.
48:24
I've
48:24
been.
48:25
I
48:25
might
48:25
even
48:25
fire
48:26
it
48:26
up
48:26
tomorrow
48:26
if
48:26
I
48:26
can
48:27
get
48:27
it
48:27
here
48:27
in
48:27
Spain.
48:28
But
48:28
yeah,
48:28
I
48:28
can
48:28
think
48:29
of
48:29
no
48:29
one
48:29
better
48:29
who
48:30
needs
48:30
skewering
48:31
or
48:31
deserves
48:31
it
48:31
more
48:32
than
48:32
tech
48:32
billionaires.
48:33
And
48:33
that's.
48:34
That's
48:34
my
48:34
take
48:34
on
48:34
that.
48:35
What
48:35
is
48:35
it?
48:35
On
48:35
what's.
48:36
What's.
48:36
Like,
48:37
where
48:37
do
48:37
you
48:37
find
48:37
it?
48:38
I
48:38
don't
48:38
know.
48:38
I
48:39
gotta
48:39
look
48:39
that
48:39
up.
48:39
Fans,
48:40
let
48:40
us
48:40
know
48:40
if
48:41
you
48:41
know
48:41
where
48:41
it
48:41
is
48:42
or
48:42
have
48:42
watched
48:42
it
48:42
and
48:42
give
48:42
it.
48:43
Let
48:43
us
48:43
know
48:43
your
48:43
review
48:44
too.
48:44
So.
48:45
All
48:45
right,
48:45
last
48:45
one.
48:45
Sydney
48:46
Sweeney.
48:46
This
48:46
one's
48:47
great.
48:47
Sydney
48:48
Sweeney
48:48
is
48:48
selling
48:49
soap
48:49
that
48:49
contains
48:50
her
48:50
own
48:50
bathwater.
48:51
Whose
48:52
bath
48:52
water
48:52
would
48:53
you
48:53
most
48:53
want
48:53
infused
48:54
into
48:54
your
48:54
soap?
48:55
Sign
48:55
me
48:55
up
48:55
for
48:56
this.
48:56
All
48:56
right.
48:56
And
48:57
what
48:57
bathwater
48:58
would
48:58
you
48:58
most
48:58
want?
48:59
No
48:59
one's.
49:00
No
49:00
one's.
49:01
No
49:01
one's.
49:01
Come
49:01
on.
49:02
You
49:02
honestly
49:03
want
49:03
somebody's
49:03
bath
49:04
water?
49:04
Like,
49:04
I
49:04
have
49:04
my
49:05
own
49:05
bath
49:05
water.
49:05
Why
49:06
do
49:06
I
49:06
need
49:06
Sydney
49:07
Sweeney's
49:07
bath
49:07
water?
49:08
This
49:08
is
49:08
like,
49:09
only
49:09
fans
49:09
gone
49:10
to
49:10
another
49:10
level
49:10
that
49:11
I
49:11
am
49:11
not
49:11
comfortable
49:12
with.
49:12
Like.
49:12
Like,
49:12
only
49:13
fans
49:13
got
49:14
to
49:14
another
49:14
level.
49:15
Like,
49:15
that
49:16
is.
49:16
That
49:16
is
49:16
like
49:17
the.
49:17
I
49:17
mean,
49:18
I
49:18
think
49:19
that's
49:19
the
49:19
origination
49:20
of
49:20
this
49:20
concept.
49:21
Like,
49:21
it
49:21
wasn't
49:22
until
49:22
a
49:23
platform
49:23
like
49:23
only
49:23
fans,
49:24
where
49:24
you
49:24
start
49:24
selling
49:25
bath
49:25
water
49:26
to,
49:26
like.
49:27
No,
49:28
no,
49:28
no.
49:28
I
49:29
cannot
49:29
say
49:29
no
49:29
enough.
49:30
Well,
49:30
you
49:30
must
49:30
use
49:30
bath
49:31
water.
49:31
You
49:31
must
49:31
use
49:31
water
49:32
in
49:32
the
49:32
production
49:32
of
49:32
soap.
49:33
So,
49:33
like,
49:33
what's
49:33
the
49:33
big
49:34
deal
49:34
if
49:34
it's
49:34
somebody's
49:35
bath
49:35
water?
49:35
Like,
49:36
you
49:36
know,
49:36
it's
49:36
got
49:36
to
49:37
be.
49:37
Well,
49:37
it's
49:37
got
49:37
to
49:37
be
49:37
cleaned,
49:38
you
49:38
know?
49:39
You
49:40
know,
49:40
Are
49:40
you
49:40
sure?
49:44
I
49:44
think
49:45
I.
49:45
It's
49:46
got
49:46
to
49:46
be.
49:46
I
49:47
don't
49:47
know.
49:47
It's
49:47
got
49:47
to
49:47
pass
49:48
fda.
49:48
I
49:48
don't
49:48
know,
49:49
but.
49:49
Well,
49:49
I
49:49
guess
49:50
I
49:50
don't
49:50
know.
49:50
It's
49:50
that.
49:50
I
49:50
don't
49:51
know.
49:51
Yeah,
49:51
maybe
49:51
not.
49:52
Who
49:52
knows?
49:53
Are
49:53
you
49:53
gonna
49:54
buy
49:54
Sydney
49:54
Sweeney's?
49:55
So.
49:55
No,
49:55
I'm
49:56
not
49:56
gonna
49:56
buy
49:56
it.
49:56
Are
49:56
you
49:57
kidding
49:57
me?
49:57
God,
49:57
no.
49:58
Good.
49:59
So
49:59
just
50:00
shooting
50:00
shopper.
50:00
I'm
50:00
not
50:00
gonna
50:01
fall
50:01
for
50:01
this
50:01
marketing
50:02
gimmick.
50:02
Although,
50:03
you
50:03
know.
50:03
Yeah,
50:04
you
50:04
know,
50:04
but,
50:04
I
50:05
mean,
50:05
love.
50:05
Sydney
50:05
Sweeney,
50:06
but
50:06
I
50:06
don't
50:06
want
50:06
her.
50:07
She's
50:07
still
50:07
the
50:08
human,
50:08
and
50:08
I
50:09
don't
50:09
want
50:09
her
50:09
dirty
50:09
bath
50:10
water.
50:10
Everything
50:11
she
50:11
does
50:11
turns
50:11
to
50:11
gold
50:12
in
50:12
my
50:12
mind,
50:12
but
50:13
I'm
50:13
not
50:13
buying
50:13
her,
50:13
so
50:14
no
50:14
way.
50:14
All
50:15
right.
50:15
Happy
50:15
birthday
50:16
today
50:16
to
50:16
Keith
50:16
David,
50:17
Angelina
50:17
Jolie,
50:18
and
50:18
to
50:18
my
50:19
favorite
50:19
Hardy
50:19
Boy,
50:20
Parker
50:21
Stevenson.
50:22
And
50:22
remember,
50:22
if
50:22
you
50:23
can
50:23
only
50:23
read
50:23
or
50:23
listen
50:23
to
50:24
one
50:24
retail
50:24
blog
50:24
in
50:24
the
50:24
business,
50:25
make
50:25
it
50:25
Omnitok,
50:26
the
50:26
only
50:26
retail
50:26
media
50:26
outlet
50:27
run
50:27
by
50:27
two
50:27
former
50:27
executives
50:28
from
50:28
a
50:28
current
50:28
top
50:28
10
50:29
US
50:29
retail
50:29
retailer.
50:30
Our
50:30
Fast
50:30
5
50:31
podcast
50:31
is
50:31
the
50:31
quickest,
50:32
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50:32
rundown
50:32
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50:33
all
50:33
the
50:33
week's
50:33
top
50:33
news.
50:33
And
50:34
our
50:34
daily
50:34
newsletter,
50:34
the
50:35
Retail
50:35
Daily
50:35
Minute,
50:35
tells
50:36
you
50:36
all
50:36
you
50:36
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50:36
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50:36
know
50:36
each
50:37
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50:37
to
50:37
stay
50:37
on
50:38
top
50:38
of
50:38
your
50:38
game
50:38
as
50:38
a
50:38
retail
50:39
executive
50:39
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50:39
also
50:40
regularly
50:40
feature
50:40
special
50:41
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50:41
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50:41
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50:41
exclusive
50:42
to
50:42
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50:42
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50:43
that
50:43
Ann
50:43
and
50:43
I
50:43
take
50:43
a
50:44
lot
50:44
of
50:44
pride
50:44
in
50:44
doing
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just
50:44
for
50:45
you.
50:45
Thanks
50:45
as
50:45
always
50:45
for
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listening
50:46
in.
50:46
Please
50:46
remember
50:46
to
50:46
like
50:47
and
50:47
leave
50:47
us
50:47
a
50:47
review
50:47
wherever
50:48
you
50:48
happen
50:48
to
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listen
50:49
to
50:49
your
50:49
podcast
50:50
or
50:50
on
50:50
YouTube.
50:51
You
50:51
can
50:51
follow
50:51
us
50:51
today
50:52
by
50:52
simply
50:52
going
50:52
to
50:53
YouTube.com
50:54
omnitalk
50:55
retail.
50:56
Last
50:56
time
50:56
I
50:56
checked,
50:56
Ann,
50:57
subscriber
50:57
count
50:57
is
50:57
up
50:57
over
50:58
160,000
50:59
subscribers.
51:00
So
51:01
until
51:01
next
51:01
week
51:02
and
51:02
on
51:02
behalf
51:03
of
51:03
all
51:03
of
51:03
us
51:03
at
51:03
Omnitalk
51:04
Retail,
51:05
as
51:05
always,
51:05
be
51:06
careful
51:06
out
51:06
there.