Latest / Omni Talk Retail / Starbucks Returns To Office, Shopify Blocks Bots & Kraft Heinz Seeks Couples Therapy | Fast Five

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Starbucks Returns To Office, Shopify Blocks Bots & Kraft Heinz Seeks Couples Therapy | Fast Five · Omni Talk Retail

0:00
The
0:00
Amitak
0:01
Fast5
0:01
is
0:02
brought
0:02
to
0:02
you
0:02
by
0:02
the
0:02
A
0:02
and
0:03
M
0:03
Consumer
0:03
and
0:03
Retail
0:04
Group.
0:04
The
0:04
A
0:05
and
0:05
M
0:05
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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consulting
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firm
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that
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tackles
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complex
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advances
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its
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clients,
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people
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communities
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for
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their
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maximum
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potential.
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CRG
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brings
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to
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help
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retailers
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and
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consumer
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products
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companies
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be
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on
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the
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right
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of
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disruption
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the
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dropship
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retail
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media
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succeeding
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with
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you
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can
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unlock
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partners
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and
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more
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profits
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without
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the
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heavy
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lifting.
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holding
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you
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to
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M
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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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the
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banners
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with
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today's
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Albertsons,
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@
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they
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unite
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warehousing,
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and
1:04
order
1:04
management
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into
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a
1:05
seamless,
1:05
adaptable
1:06
network.
1:07
Infios
1:07
helps
1:08
you
1:08
stay
1:08
ahead
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from
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promise
1:10
to
1:10
delivery
1:10
and
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every
1:11
step
1:11
in
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between.
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To
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learn
1:13
more,
1:13
visit
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infios.com
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and
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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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be
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guesswork.
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Clear
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Demand's
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powered
1:20
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data
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and
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optimization
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solutions
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help
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retailers
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stay
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competitive
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while
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protecting
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pricing
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strategies,
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Demand
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makes
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it
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happen.
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Learn
1:30
more@cleardemand.com
1:32
omnitalk
1:33
and
1:33
finally,
1:34
Ocampo
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Capital.
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Ocampo
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Capital
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is
1:37
a
1:37
venture
1:37
capital
1:37
firm
1:38
founded
1:38
by
1:38
retail
1:39
executives
1:39
with
1:39
the
1:40
aim
1:40
of
1:40
helping
1:40
early
1:41
stage
1:41
consumer
1:41
businesses
1:42
succeed
1:42
through
1:43
investment
1:43
and
1:43
operational
1:44
support.
1:45
Learn
1:45
more@ocampo
1:46
capital.com
1:47
hello,
1:48
you
1:48
are
1:48
listening
1:49
to
1:49
Omnitalk's
1:50
Retail
1:50
Fast
1:50
Five
1:51
ranked
1:51
in
1:51
the
1:51
top
1:51
10%
1:52
of
1:52
all
1:52
podcasts
1:53
globally
1:53
and
1:53
currently
1:54
the
1:54
only
1:54
retail
1:55
podcast
1:55
ranked
1:55
in
1:55
the
1:56
top
1:56
100
1:56
of
1:56
all
1:57
business
1:57
podcasts
1:57
on
1:57
Apple
1:58
Podcast
1:59
the
1:59
Retail
1:59
Fast
1:59
five
2:00
is
2:00
the
2:00
podcast
2:00
that
2:00
we
2:01
hope
2:01
makes
2:01
you
2:01
feel
2:01
a
2:01
little
2:02
smarter,
2:02
but
2:02
most
2:03
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
2:06
great
2:07
podcasts
2:07
you
2:07
can
2:08
find
2:08
from
2:08
the
2:08
Amitak
2:09
Retail
2:09
Podcast
2:10
Network
2:10
alongside
2:11
our
2:11
Retail
2:11
Daily
2:12
minute
2:12
read
2:13
each
2:13
day
2:13
by
2:13
the
2:14
one
2:14
and
2:14
only
2:14
Chris
2:15
Walton,
2:15
which
2:15
brings
2:16
you
2:16
a
2:16
curated
2:16
selection
2:17
of
2:17
the
2:17
most
2:18
important
2:18
retail
2:19
headlines
2:19
every
2:19
morning
2:20
and
2:20
our
2:20
Retail
2:21
Technology
2:21
Spotlight
2:21
series
2:22
which
2:22
goes
2:22
deep
2:22
each
2:23
week
2:23
on
2:23
the
2:23
latest
2:24
retail
2:24
technology
2:24
trends.
2:25
It's
2:26
July
2:26
16,
2:27
2025.
2:28
I'm
2:28
one
2:28
of
2:28
your
2:28
hosts,
2:29
Sam
2:29
Mazing.
2:30
And
2:30
I
2:30
guess
2:31
Now.
2:31
And
2:31
I'm
2:31
the
2:31
one
2:31
and
2:32
only
2:32
Chris.
2:32
Walton,
2:32
you
2:33
are,
2:33
you
2:33
are.
2:33
And
2:34
we
2:34
are
2:34
here
2:34
once
2:35
again
2:35
to
2:35
discuss
2:35
all
2:36
the
2:36
top
2:36
headlines
2:37
from
2:37
the
2:37
past
2:37
week
2:38
making
2:38
waves
2:39
in
2:39
the
2:39
world
2:39
of
2:39
Omni
2:40
Channel
2:40
retailing.
2:40
And
2:41
Chris,
2:41
joining
2:42
us
2:42
today
2:42
as
2:42
they
2:43
do
2:43
once
2:43
a
2:44
month,
2:44
every
2:45
month,
2:45
we
2:45
have
2:46
managing
2:46
directors
2:47
from
2:48
the
2:48
A
2:48
and
2:48
M
2:48
consumer
2:49
and
2:49
retail
2:49
group,
2:50
Chad
2:50
Lusk
2:50
and
2:51
David
2:51
Brown.
2:52
Welcome
2:53
Chad.
2:53
David,
2:54
we're
2:54
so
2:54
excited
2:55
to
2:55
have
2:55
you.
2:56
You're
2:56
typically
2:56
our
2:56
end
2:57
of
2:57
the
2:57
year
2:57
guest
2:58
so
2:58
I
2:58
love
2:58
that.
2:58
This
2:58
is
2:59
like
2:59
our,
2:59
our
2:59
mid
3:00
year
3:00
preview,
3:01
the
3:01
July
3:01
preview
3:02
of
3:02
what
3:03
might
3:03
happen
3:04
on
3:04
the
3:05
end
3:05
of
3:05
the
3:05
year
3:06
podcast.
3:07
Chad
3:08
the
3:08
Lusker.
3:09
Chad
3:09
Lusk,
3:10
how
3:10
are
3:10
you
3:10
doing
3:10
today?
3:11
Are
3:11
you
3:11
ready
3:11
for
3:11
this
3:11
show?
3:12
I'm
3:12
doing
3:13
great
3:13
guys.
3:13
It's
3:14
good
3:14
to
3:14
be
3:14
back.
3:15
Yeah,
3:15
this
3:15
is
3:15
a
3:15
little
3:15
meta.
3:16
I
3:16
mean
3:16
last
3:16
time
3:17
I
3:17
was
3:17
on.
3:18
Was
3:19
the
3:19
end
3:19
of
3:19
year
3:19
award
3:20
show.
3:21
The
3:21
Omnis
3:22
as
3:23
now
3:23
dub.
3:24
Thank
3:24
you
3:24
very
3:24
much.
3:25
But
3:25
I
3:25
was
3:25
actually
3:26
sitting
3:26
in
3:27
for
3:27
David,
3:27
not
3:28
alongside
3:28
David.
3:29
That's
3:29
true.
3:30
Using
3:30
his
3:31
mailed
3:31
in
3:31
envelopes
3:32
to
3:32
unleash
3:33
the
3:33
winners.
3:33
So
3:35
that's
3:35
right
3:35
about
3:36
three
3:36
years
3:36
since
3:37
David
3:37
and
3:37
I
3:37
did
3:38
this
3:38
together.
3:38
So
3:40
you
3:40
know
3:40
we
3:40
lit
3:40
that
3:41
show
3:41
up.
3:41
We'll,
3:41
we'll
3:41
do
3:42
it
3:42
again
3:42
here
3:42
today.
3:43
Yeah,
3:44
absolutely.
3:44
I
3:45
think
3:45
of
3:45
you
3:45
every
3:45
time
3:46
I
3:46
pick
3:46
up
3:46
an
3:46
envelope,
3:47
which
3:47
is
3:47
rare
3:48
Chad,
3:48
but
3:48
every
3:48
time
3:49
those
3:49
white
3:49
envelopes
3:50
I
3:50
pull
3:50
one
3:51
out,
3:51
I
3:51
think
3:51
about
3:51
it.
3:53
Chad,
3:53
before
3:54
we
3:54
go
3:54
to
3:54
David's
3:55
introduction,
3:55
quick
3:56
background
3:56
on
3:56
you
3:56
for
3:57
those
3:57
of
3:57
our
3:57
listeners
3:58
who
3:58
might
3:58
be
3:58
joining
3:58
us
3:58
here
3:59
for
3:59
the
3:59
first
3:59
time
3:59
if
3:59
you
4:00
don't
4:00
mind.
4:00
Yeah,
4:01
absolutely.
4:02
Partner
4:03
Managing
4:03
director
4:03
out
4:04
of
4:04
Chicago
4:05
background
4:06
pre
4:07
consulting
4:07
here
4:08
as
4:08
a
4:09
multi
4:09
time
4:09
Chief
4:10
Marketing
4:10
Officer,
4:11
Chief
4:11
Strategy
4:12
Officer
4:12
across
4:13
both
4:13
CPG
4:14
and
4:14
retail
4:15
today.
4:16
Nowadays
4:16
I
4:17
spend
4:17
most
4:17
of
4:17
my
4:17
time
4:18
on
4:18
broad
4:19
scale
4:19
transformation
4:20
with
4:20
a
4:20
real
4:21
focus
4:21
on
4:22
growth
4:22
and
4:23
commercial
4:23
excellence.
4:25
Wonderful.
4:26
We
4:26
have
4:26
some
4:26
stories
4:27
for
4:27
you
4:27
today
4:27
Chad
4:28
that
4:28
we're
4:28
quite
4:29
excited
4:29
to
4:30
discuss.
4:31
David
4:31
Brown,
4:32
another
4:32
Omnitalk
4:33
veteran.
4:34
David,
4:35
why
4:35
don't
4:35
you
4:35
give
4:36
our
4:36
listeners
4:36
a
4:36
quick
4:37
background
4:37
on
4:37
you
4:38
your
4:38
role
4:39
out
4:39
there
4:39
at
4:39
am.
4:41
Sure.
4:41
Happy
4:42
to
4:42
Ann.
4:42
Great
4:42
to
4:43
be
4:43
here.
4:44
I
4:44
lead
4:44
the
4:44
consumer
4:45
retail
4:46
group
4:46
along
4:46
with
4:47
a
4:47
couple
4:47
others
4:49
lifetime
4:49
professional
4:50
services
4:51
started
4:51
in
4:51
banking
4:52
and
4:52
now
4:52
25
4:52
plus
4:53
years
4:53
and
4:54
consulting
4:55
with
4:56
the
4:56
red
4:56
thread
4:57
of
4:58
being
4:58
retail
4:59
kind
5:00
of
5:00
optimization
5:01
programs
5:02
whether
5:02
that
5:02
be
5:02
kind
5:03
of
5:03
turnaround,
5:03
growth,
5:04
etc.
5:05
Really
5:05
working
5:06
across
5:06
the
5:06
whole
5:06
value
5:06
chain.
5:07
So
5:07
super
5:07
excited
5:08
to
5:08
be
5:08
here.
5:09
Very
5:09
sorry
5:09
I
5:10
missed
5:10
the
5:11
year
5:11
end
5:11
show
5:13
but
5:13
this
5:13
will
5:14
be
5:14
great
5:14
prep
5:14
for,
5:16
for
5:16
this
5:16
year.
5:17
It
5:17
was
5:17
like
5:17
you
5:18
were
5:18
here
5:18
in
5:18
spirit
5:18
David,
5:19
for
5:19
sure.
5:19
Like
5:19
we
5:20
did
5:20
it.
5:20
We,
5:20
we,
5:20
we
5:21
did
5:21
skip
5:21
a
5:21
beat
5:22
with
5:22
you.
5:22
I
5:22
mean
5:22
you're
5:22
historically
5:23
on
5:23
the
5:23
year
5:24
end
5:24
show
5:24
every
5:24
year.
5:24
And
5:24
it
5:25
felt
5:25
like
5:25
you
5:25
were
5:25
still
5:25
there,
5:25
Chad
5:26
job
5:26
representing
5:27
your,
5:27
your
5:27
point
5:28
of
5:28
view.
5:28
And
5:28
I've
5:28
never
5:28
heard
5:28
the
5:29
term
5:29
red
5:29
thread
5:30
before,
5:30
so
5:30
I
5:31
might
5:31
have
5:31
to,
5:31
might
5:32
have
5:32
to
5:32
borrow
5:32
that
5:32
if
5:33
you're
5:33
okay
5:33
with
5:33
it,
5:33
of
5:33
course.
5:34
Well,
5:34
I
5:34
will
5:34
attribute
5:34
it
5:35
to
5:35
you
5:35
as
5:35
well.
5:36
All
5:36
right,
5:36
Ed,
5:37
should
5:38
we
5:38
get
5:38
started
5:38
with
5:38
this
5:38
week's
5:39
show?
5:39
Let's
5:39
do
5:39
it.
5:39
Let's
5:40
do
5:40
it.
5:40
All
5:40
right.
5:41
In
5:41
this
5:41
week's
5:41
Fast5,
5:42
we've
5:42
got
5:43
news
5:43
on
5:43
return
5:43
to
5:44
office
5:44
mandates
5:45
from
5:45
both
5:45
Starbucks
5:46
and
5:46
Target
5:47
this
5:47
week.
5:48
Yesterday's
5:48
inflation
5:49
report,
5:49
Supermarkets
5:50
reportedly
5:51
losing
5:51
ground
5:51
with
5:52
younger
5:52
shoppers
5:53
shopify
5:54
setting
5:54
boundaries
5:54
for
5:55
AI
5:55
agents
5:55
on
5:56
its
5:56
merchant
5:56
sites.
5:57
And
5:57
AWS's
5:58
Danielle
5:59
Stropa
6:00
stops
6:00
by
6:00
to
6:01
announce
6:01
this
6:01
month's
6:02
retail
6:02
tech
6:03
startup
6:03
of
6:03
the
6:04
month
6:04
for
6:04
the
6:04
month
6:05
of
6:05
July.
6:06
But
6:06
we
6:06
begin
6:06
today
6:07
with
6:07
what
6:07
may
6:08
be
6:08
the
6:08
worst
6:09
catch
6:09
up
6:09
secret.
6:10
Chad,
6:10
I'm
6:10
so
6:10
glad
6:11
you're
6:11
on
6:11
the
6:11
show
6:11
this
6:11
week
6:11
because
6:12
I
6:12
know
6:12
you're
6:12
going
6:12
to
6:12
get
6:12
that
6:12
reference.
6:13
The
6:13
worst
6:14
ketchup
6:14
secret
6:14
in
6:15
history.
6:15
And
6:16
yes,
6:17
we
6:17
promised
6:18
a
6:18
headline
6:18
for
6:18
Chad.
6:19
Here
6:19
it
6:19
is,
6:19
headline
6:20
number
6:20
one.
6:20
Kraft
6:21
Heinz
6:21
is
6:21
preparing
6:22
to
6:22
break
6:22
itself
6:22
up
6:23
a
6:23
decade
6:24
after
6:24
an
6:24
infamous
6:25
merger
6:25
of
6:25
the
6:26
two
6:26
biggest
6:26
names
6:27
in
6:27
packaged
6:27
foods
6:27
that
6:28
was
6:28
orchestrated
6:28
by
6:29
Warren
6:29
Buffett
6:30
and
6:30
Brazilian
6:30
private
6:31
equity
6:31
firm
6:31
3G
6:32
Capital
6:32
Partners.
6:33
According
6:33
to
6:33
the
6:33
Wall
6:34
Street
6:34
Journal,
6:34
Kraft
6:34
Heinz
6:35
is
6:35
planning
6:35
to
6:35
spin
6:35
off
6:36
a
6:36
large
6:36
chunk
6:36
of
6:36
its
6:36
grocery
6:37
business,
6:37
including
6:38
many
6:38
craft
6:39
products,
6:39
into
6:39
a
6:39
new
6:40
entity
6:40
that
6:40
could
6:40
be
6:41
valued
6:41
as
6:41
much
6:42
as
6:42
$20
6:43
billion
6:44
on
6:44
its
6:44
own,
6:44
according
6:45
to
6:45
people
6:45
familiar
6:45
with
6:46
the
6:46
matter.
6:46
That
6:47
would
6:47
leave
6:47
a
6:47
company
6:47
housing
6:48
goods
6:48
such
6:48
as
6:49
sauces
6:49
and
6:49
spreads
6:50
like
6:50
Heinz
6:50
namesake
6:51
ketchup
6:51
and
6:52
Dijon
6:52
mustard
6:53
brand
6:53
Gray
6:54
Poupon.
6:54
The
6:55
company
6:55
has
6:55
given
6:55
priority
6:56
to
6:56
its
6:56
faster
6:57
going
6:57
offerings
6:57
like
6:57
hot
6:58
sauces,
6:58
dressings
6:59
and
6:59
condiments,
6:59
which
7:00
are
7:00
more
7:00
in
7:00
line
7:00
with
7:00
consumer
7:01
preferences
7:02
than
7:02
processed
7:03
lunch
7:03
meats
7:03
and
7:04
cheeses.
7:04
It
7:05
hopes
7:05
the
7:05
two
7:05
separate
7:06
units
7:06
could
7:06
be
7:07
in
7:07
total
7:07
more
7:08
than
7:08
KRAFT
7:08
Heinz,
7:09
roughly
7:09
$31
7:10
billion
7:11
market
7:11
value
7:11
currently.
7:12
Chad,
7:13
what
7:13
is
7:13
your
7:13
assessment
7:14
of
7:14
the
7:14
Kraft
7:15
Heinz
7:15
breakup
7:16
and
7:16
what
7:16
is
7:16
the
7:16
potential
7:17
value
7:17
creation
7:18
given
7:18
as
7:18
the
7:19
rationale?
7:21
So
7:21
first
7:21
of
7:21
all,
7:21
it
7:21
was
7:22
a
7:22
pretty
7:22
big
7:22
week
7:22
for
7:23
food
7:23
M
7:24
and
7:24
A
7:24
overall,
7:25
I
7:25
believe
7:26
this
7:26
was
7:27
just
7:27
a
7:27
day
7:28
after
7:28
Ferrero
7:29
announced
7:29
the
7:29
deal
7:30
to
7:30
buy
7:30
Kellogg
7:31
cereal
7:32
division.
7:32
Right,
7:35
Listen,
7:35
in
7:35
this
7:35
case,
7:36
the,
7:36
the
7:36
massive
7:37
devaluation
7:38
that's
7:39
occurred
7:39
since
7:39
the
7:39
Kraft
7:40
Heinz
7:40
merger
7:40
is,
7:41
is
7:41
stuff
7:41
of
7:42
legend,
7:42
right?
7:43
So
7:43
am
7:44
I
7:44
surprised
7:44
to
7:45
see
7:45
this
7:45
like,
7:46
especially
7:46
in
7:46
this
7:47
current
7:47
era
7:47
of
7:49
pretty
7:49
massive
7:49
portfolio
7:50
shaping
7:50
and
7:51
reshaping
7:51
across
7:52
food
7:52
and
7:52
Bev
7:52
cpg
7:53
No,
7:53
not
7:54
at
7:54
all.
7:54
Your
7:55
question
7:55
is,
7:55
will
7:55
it
7:56
work?
7:56
Right,
7:56
Right.
7:58
You
7:58
know,
7:58
listen,
7:59
the
7:59
theory
7:59
of
8:00
M
8:00
and
8:00
A
8:01
is
8:01
painfully
8:02
simple.
8:03
When
8:03
you
8:03
break
8:03
it
8:04
down,
8:04
even
8:04
though
8:04
it's
8:05
kind
8:05
of
8:05
painful
8:05
to
8:05
make
8:06
work,
8:06
you
8:06
need
8:06
to
8:06
make
8:07
the
8:07
move
8:07
that
8:07
adds
8:08
value.
8:09
And
8:09
so
8:09
the
8:09
numbers
8:10
that
8:10
are
8:10
being
8:10
stated
8:11
out
8:11
in
8:11
the
8:11
article
8:11
are,
8:11
wow,
8:12
we
8:12
break
8:12
it
8:12
up,
8:12
it's
8:13
worth
8:13
more
8:13
than
8:14
it
8:14
is
8:14
together.
8:14
How
8:15
does
8:15
that
8:15
work?
8:15
Right.
8:16
So
8:17
you
8:17
know
8:17
it's
8:17
the
8:18
inverse
8:18
of
8:18
an
8:19
acquisition
8:19
deal,
8:19
right.
8:20
If
8:20
you're
8:20
acquiring,
8:20
you're
8:21
betting
8:21
on
8:22
being
8:23
able
8:23
to
8:23
disproportionately
8:24
grow
8:25
something
8:25
more
8:26
or
8:26
faster
8:26
than
8:26
it
8:27
otherwise
8:27
could
8:28
or
8:28
grow
8:29
the
8:29
same
8:29
at
8:29
a
8:29
higher
8:30
profit
8:30
margin.
8:30
Otherwise
8:31
you're
8:31
paying
8:31
for
8:32
it
8:32
in
8:32
the
8:32
purchase
8:32
price.
8:33
That's
8:34
what
8:34
Ferrero
8:34
is
8:35
banking
8:35
on
8:35
by
8:35
taking
8:36
those
8:36
slower
8:37
moving
8:37
cereal
8:37
brands
8:38
from
8:38
kellogg.
8:39
That's
8:39
what
8:39
J.M.
8:39
smucker
8:40
bet
8:40
on
8:41
with
8:41
Hostess,
8:42
you
8:42
know,
8:42
countless
8:42
examples.
8:43
If
8:44
you're
8:44
divesting
8:44
and
8:45
breaking
8:45
things
8:45
apart,
8:46
you're
8:46
getting
8:47
rid
8:47
of
8:47
the
8:47
boat
8:48
anchors
8:48
that
8:48
others
8:49
could
8:49
do
8:49
better
8:50
than
8:50
you,
8:51
right?
8:51
In
8:51
this
8:52
market,
8:53
growth
8:53
is
8:53
hard.
8:54
Folks
8:54
have
8:55
negative
8:55
comps.
8:56
So
8:57
you're
8:57
seeing
8:57
this
8:57
a
8:57
lot.
8:58
It's
8:58
shrink
8:58
to
8:58
grow,
8:59
Right.
9:00
Could
9:00
someone
9:00
else
9:00
do
9:01
better
9:01
with
9:02
Oscar
9:03
Meyer
9:03
and
9:03
Lunchables
9:04
and
9:04
Mac
9:05
and
9:05
Cheese?
9:05
When,
9:06
when
9:06
these
9:06
brands
9:06
aren't
9:07
succeeding
9:07
at
9:07
Kraft
9:08
Heinz,
9:09
you
9:09
know
9:09
what?
9:09
Probably,
9:10
right?
9:11
The
9:11
large
9:11
conglomerate
9:12
CPGs,
9:14
you
9:14
know,
9:14
they
9:14
take
9:15
off
9:15
their
9:15
pants
9:15
one
9:16
leg
9:16
at
9:16
a
9:16
time
9:16
like
9:17
the
9:17
rest
9:17
of
9:17
us.
9:17
They
9:17
have
9:18
to
9:18
allocate
9:18
resources
9:19
like
9:19
anyone
9:19
else.
9:20
So,
9:20
you
9:21
know,
9:21
these
9:21
brands,
9:21
they
9:21
fall
9:22
out
9:22
of
9:22
favor,
9:23
kind
9:23
of
9:23
a
9:24
death
9:24
spiral
9:24
internally.
9:26
So
9:26
someone
9:26
who
9:27
can
9:27
take
9:27
them,
9:28
make
9:28
them
9:28
higher
9:28
priority,
9:29
take
9:30
the
9:30
brand
9:30
equity,
9:31
invest
9:32
in
9:32
marketing,
9:32
invest
9:33
in
9:33
innovation.
9:34
It's
9:34
been
9:34
shown
9:34
numerous
9:35
times
9:35
that
9:35
it
9:35
works
9:36
and
9:36
that's
9:36
what
9:36
they're
9:37
banking
9:37
on
9:37
here.
9:38
Which
9:39
does
9:39
make
9:40
sense
9:40
if
9:40
there's
9:40
a
9:41
willing
9:41
party,
9:41
which
9:42
is
9:42
always
9:42
the
9:42
other
9:43
side
9:43
of
9:43
it.
9:43
But
9:44
you
9:44
know,
9:44
the,
9:45
the
9:45
breakup,
9:46
I
9:46
mean,
9:46
it's
9:46
just
9:46
a
9:47
couple
9:47
years
9:47
ago
9:47
in
9:48
terms
9:48
of
9:48
what
9:48
Kellogg
9:49
did,
9:49
you
9:49
know,
9:49
into
9:49
Kellanova
9:50
and
9:50
Kellogg,
9:51
and
9:51
now
9:51
that's
9:51
selling
9:51
off
9:52
to
9:52
Ferrero,
9:52
who's
9:53
going
9:53
to
9:53
try
9:53
to
9:53
put
9:54
it
9:54
on
9:54
speed.
9:56
You
9:56
know,
9:56
it's,
9:56
it's,
9:57
it's,
9:58
it's
9:58
a
9:58
ten
9:58
year
9:58
journey
9:59
here.
9:59
That,
9:59
that
10:00
reached
10:00
kind
10:00
of
10:00
an
10:00
inevitable
10:01
conclusion
10:02
and
10:02
we'll
10:02
see
10:02
where
10:02
it
10:02
goes
10:02
from
10:03
here.
10:04
Yeah.
10:04
Chad,
10:04
how
10:05
much
10:05
do
10:05
you
10:05
think
10:05
like
10:06
regulation
10:06
is
10:07
going
10:07
to
10:07
impact?
10:07
You
10:08
know,
10:08
in
10:08
the
10:08
past
10:08
you
10:09
had
10:09
these
10:09
mergers
10:09
and
10:10
acquisitions
10:10
or
10:11
divestitures
10:12
happening.
10:12
Do
10:13
you
10:13
think
10:13
that
10:13
there's
10:14
less
10:14
opportunity
10:15
now
10:15
because
10:16
of
10:16
the
10:16
requirements
10:17
to
10:17
change
10:18
ingredients
10:19
or
10:19
remove
10:20
artificial
10:20
flavorings
10:21
and
10:21
that
10:21
kind
10:21
of
10:21
stuff?
10:22
In
10:22
this
10:22
kind
10:22
of
10:23
category
10:23
that
10:23
will
10:23
impact
10:24
that.
10:25
I
10:25
don't
10:26
know
10:26
that
10:26
it
10:26
has
10:26
an
10:27
impact
10:27
specifically
10:28
on
10:28
a,
10:28
on
10:29
a
10:29
deal
10:29
like
10:29
this.
10:29
I
10:30
mean,
10:30
listen,
10:30
your
10:31
food
10:31
industry
10:31
is
10:32
on
10:32
watch
10:32
right
10:32
now
10:33
when
10:33
it
10:34
comes
10:34
to
10:34
that,
10:34
right?
10:35
And
10:36
you
10:36
know,
10:36
that's
10:36
just
10:37
becoming,
10:38
you
10:38
know,
10:38
at
10:39
this
10:39
point
10:39
some
10:39
degree
10:40
of
10:40
table
10:40
stakes
10:40
of
10:40
how
10:41
the
10:41
industry
10:41
needs
10:41
to,
10:42
to
10:42
react
10:42
going
10:42
forward.
10:43
I'm
10:43
not
10:43
sure
10:44
that
10:44
individual,
10:46
especially
10:46
brands
10:47
in
10:47
this
10:48
kind
10:48
of
10:48
catalog
10:49
that,
10:50
that
10:50
ultimately
10:51
is
10:51
going
10:51
to
10:51
be
10:52
a
10:52
deterrent
10:53
or
10:53
an
10:53
accelerator
10:54
on
10:54
M
10:54
and
10:54
A
10:54
activity.
10:56
And
10:56
David
10:56
Brown,
10:57
where
10:57
do
10:57
you
10:58
see
10:58
the
10:58
opportunity
10:59
here
10:59
from
10:59
this?
10:59
You
11:00
know,
11:00
as
11:00
somebody
11:00
who's
11:01
worked
11:01
in
11:02
professional
11:02
services
11:02
for
11:03
a
11:03
long
11:03
time,
11:03
if,
11:03
if
11:04
Kraft
11:04
Heinz
11:04
is
11:04
coming,
11:05
they're,
11:06
they're
11:06
the
11:06
separate
11:07
companies
11:07
now.
11:07
What
11:08
are
11:08
some
11:08
of
11:08
the
11:08
key
11:08
things
11:09
that
11:09
you
11:09
think
11:09
could
11:10
be,
11:10
or
11:10
actions
11:11
that
11:11
could
11:11
be
11:11
taken
11:12
right
11:12
now
11:12
to
11:13
help
11:13
the
11:13
success
11:14
of
11:14
the
11:14
future?
11:16
I
11:16
agree
11:16
with
11:16
a
11:16
lot
11:16
of
11:17
what
11:17
Chad
11:18
said
11:18
and
11:18
I
11:18
think
11:18
there's
11:19
a
11:19
couple
11:19
other
11:19
angles.
11:21
One,
11:21
I
11:21
think
11:21
what
11:22
we're
11:22
seeing
11:22
now
11:22
is
11:22
the
11:22
dismantling
11:23
or
11:24
the,
11:24
the
11:25
proof
11:25
point
11:25
that
11:25
a
11:26
lot
11:26
of
11:26
the
11:27
3G
11:28
work
11:28
just
11:29
really
11:29
didn't
11:29
work.
11:30
Right.
11:31
That
11:31
you
11:31
know,
11:31
all
11:32
of
11:33
these
11:33
billions
11:34
of
11:34
dollars
11:34
of
11:35
cost
11:35
synergies
11:36
that
11:36
were
11:36
supposed
11:37
to
11:37
happen
11:38
really
11:38
haven't
11:39
worked
11:39
because
11:40
of
11:40
either
11:40
the
11:40
complexity
11:41
of
11:41
the
11:41
organizations
11:42
or
11:43
as
11:43
Chad
11:43
said,
11:43
the
11:44
resource
11:44
allocation,
11:46
etcetera,
11:46
etcetera.
11:48
So
11:48
I
11:48
think
11:48
the
11:49
opportunities
11:49
as
11:50
you
11:50
split
11:50
these
11:50
apart
11:51
is
11:51
really
11:51
going
11:51
to
11:51
be
11:52
to
11:52
be
11:53
laser
11:53
focused
11:54
on
11:54
what
11:54
matters
11:56
for
11:56
the
11:56
consumer,
11:57
right?
11:57
So
11:58
you
11:58
pick
11:58
a
11:58
strategy
11:59
and
11:59
then
11:59
you
12:00
ruthlessly
12:01
execute
12:02
against
12:02
it.
12:02
It's
12:03
really
12:03
hard
12:03
to
12:04
pick,
12:05
you
12:05
know,
12:06
six
12:06
different
12:06
strategies
12:07
within
12:07
an
12:07
organization
12:09
and
12:09
execute
12:10
it
12:10
against
12:10
it
12:10
effectively
12:12
because
12:12
it
12:12
just
12:13
doesn't
12:13
work.
12:13
Right.
12:14
So
12:14
I
12:14
think
12:15
that's
12:15
what
12:15
we're
12:15
seeing
12:15
more
12:16
than
12:16
anything
12:16
here.
12:16
And
12:17
as
12:17
you
12:17
kind
12:17
of
12:18
divest
12:19
and
12:19
be
12:19
able
12:19
to
12:19
get
12:20
more
12:20
focused,
12:21
I
12:21
think
12:21
the
12:21
other
12:21
interesting
12:22
thing
12:22
that
12:23
I
12:23
haven't
12:23
seen
12:24
in
12:24
any
12:24
of
12:24
the
12:24
press
12:24
on
12:25
any
12:25
of
12:25
these
12:25
deals
12:26
yet
12:28
is
12:28
as
12:28
they
12:29
go
12:29
to
12:30
either
12:31
get
12:31
sold
12:31
to
12:31
foreign
12:32
entities
12:33
or
12:33
foreign
12:34
entities
12:34
are,
12:35
are
12:35
looking
12:35
at
12:35
them,
12:36
the
12:36
regulations
12:37
do
12:38
matter,
12:38
right?
12:38
You
12:39
know,
12:39
there's
12:39
a
12:40
lot
12:40
more
12:40
ingredients
12:41
that
12:42
are
12:42
limited
12:42
outside
12:43
of
12:43
the
12:43
U.S.
12:44
than
12:44
inside
12:44
the
12:44
U.S.
12:45
that's
12:45
a
12:45
whole
12:45
different
12:46
debate
12:47
that,
12:48
that
12:48
we
12:48
could
12:49
have.
12:50
But
12:50
also
12:50
the,
12:51
you
12:51
know,
12:51
the
12:51
ongoing
12:52
tariff
12:52
situation
12:54
and
12:54
like
12:54
if
12:55
you
12:55
start
12:55
moving,
12:56
you
12:56
know,
12:56
kind
12:56
of
12:56
manufacturing
12:57
plants
12:58
or
12:58
you
12:59
know,
12:59
now
12:59
you're
12:59
re
13:00
importing
13:01
cereal
13:01
or
13:02
Mac
13:02
and
13:02
cheese
13:02
or,
13:03
or
13:03
whatever
13:03
it
13:04
is,
13:05
you,
13:06
you
13:06
could
13:06
be
13:06
talking
13:06
about
13:07
drastically
13:07
different
13:07
price
13:08
points,
13:08
right?
13:09
So
13:11
how
13:11
that
13:11
plays
13:11
out
13:11
on
13:12
the
13:12
valuations,
13:13
right?
13:13
And,
13:13
and
13:14
Kraft
13:14
Heinz
13:14
has
13:14
had
13:15
this
13:15
innovation
13:15
center
13:16
focused
13:16
on
13:17
product
13:17
design
13:18
and
13:18
development
13:18
for
13:19
75
13:19
years
13:20
or
13:20
something
13:20
now,
13:21
too,
13:21
but
13:21
likely
13:22
focused
13:22
on
13:22
the
13:23
US
13:23
Market
13:24
and
13:24
what
13:24
they're
13:24
doing
13:25
here,
13:25
not
13:25
what
13:25
those
13:26
regulations
13:26
are
13:27
probably
13:27
going
13:27
to
13:27
be
13:28
when
13:28
you're
13:28
looking
13:28
at
13:28
overseas
13:29
buyers.
13:30
Chris
13:31
Walton,
13:32
round
13:32
us
13:33
out
13:33
here.
13:33
What
13:33
else
13:34
would
13:34
you
13:34
add
13:34
to
13:35
what
13:35
David
13:35
and
13:36
Chad
13:36
had
13:36
to
13:36
say?
13:37
Yeah,
13:38
I
13:38
don't,
13:38
I
13:38
don't,
13:38
I
13:38
don't
13:39
think
13:39
I'd
13:39
add
13:39
much,
13:39
but
13:39
I
13:39
do
13:39
have
13:40
an
13:40
analogy
13:40
that
13:40
I
13:40
use
13:41
to
13:41
think
13:41
about
13:41
these
13:41
things.
13:41
You
13:42
know,
13:42
I
13:42
think
13:42
of
13:42
it
13:42
like,
13:42
you
13:43
know,
13:43
whenever
13:43
it
13:43
was
13:43
what
13:44
they
13:44
say
13:44
was
13:44
15
13:45
years
13:45
ago
13:45
that
13:45
this,
13:46
this
13:46
merger
13:46
happened.
13:48
You
13:48
know,
13:48
to
13:48
me,
13:48
it's
13:48
just
13:49
like,
13:49
you
13:49
know,
13:49
it's
13:49
like
13:49
a
13:49
marriage
13:50
and
13:50
the
13:50
marriage
13:51
didn't
13:51
work
13:51
out
13:51
and
13:52
they
13:53
need
13:53
to
13:53
separate
13:54
and
13:54
they,
13:54
they're
13:55
not
13:55
as
13:55
sexy,
13:55
they're
13:56
not
13:56
as
13:56
good
13:56
looking,
13:57
they're
13:57
not
13:57
as
13:57
happy
13:58
as
13:58
they
13:58
were
13:58
when
13:58
they
13:59
were
13:59
apart
14:00
from
14:00
each
14:00
other.
14:00
And
14:00
so
14:01
now
14:01
they've
14:01
got
14:01
to
14:01
separate
14:02
and
14:02
potentially
14:03
get
14:03
back
14:03
into
14:03
the
14:03
gym
14:04
and
14:04
start
14:04
working
14:05
out
14:05
and
14:05
finding
14:06
the
14:06
happiness
14:06
in
14:06
life.
14:06
And
14:07
potentially
14:07
there's
14:08
another
14:08
acquirer
14:08
down
14:09
the
14:09
road.
14:09
And
14:09
maybe
14:09
to
14:10
David's
14:10
point,
14:10
that
14:10
Acquirer
14:11
is
14:11
an
14:11
international
14:11
company
14:12
that
14:12
is
14:13
farther
14:13
ahead
14:13
on
14:13
understanding
14:14
the
14:14
different
14:15
puts
14:15
and
14:15
takes
14:16
with,
14:16
you
14:16
know,
14:16
refining
14:17
product
14:17
formulations
14:18
and
14:18
all
14:18
that.
14:19
So
14:19
that,
14:19
that's
14:19
how
14:19
I
14:20
look
14:20
at
14:20
this.
14:20
It's
14:20
just,
14:21
you
14:21
know,
14:21
the
14:21
natural
14:22
progression
14:22
that,
14:23
that
14:23
happens
14:24
for
14:24
a
14:24
lot
14:25
of
14:25
folks
14:25
in
14:25
many
14:25
aspects
14:26
of
14:26
life.
14:27
Except
14:28
for
14:28
you,
14:28
Chris,
14:29
who's
14:29
gotten
14:29
sexier
14:30
over
14:30
time.
14:31
Oh,
14:31
thank
14:32
you,
14:32
Chad.
14:32
Thank
14:32
you
14:33
everywhere
14:34
on
14:34
this
14:34
podcast,
14:35
Chad.
14:35
Thank
14:35
you.
14:36
Thank
14:36
you.
14:37
All
14:38
right,
14:38
well,
14:38
let's
14:39
move
14:39
on
14:39
on
14:39
that
14:40
note,
14:40
because
14:40
I've
14:40
got
14:40
riding
14:41
high
14:41
already
14:41
for
14:42
this
14:42
to
14:42
start
14:43
today
14:43
off.
14:43
All
14:43
right,
14:43
headline
14:44
number
14:44
two,
14:45
both
14:45
Starbucks
14:46
and
14:46
Target
14:46
issued
14:47
return
14:47
to
14:47
office
14:48
orders
14:48
this
14:48
week,
14:49
according
14:49
to
14:50
local
14:50
Minneapolis
14:51
NBC
14:51
affiliate
14:52
Carol
14:52
Evan
14:52
Shout
14:53
out
14:53
to
14:53
Carol
14:53
Levin.
14:54
Target's
14:54
Chief
14:55
Commercial
14:55
Officer
14:56
Rick
14:56
Gomez
14:56
said
14:57
that
14:57
starting
14:57
September
14:58
2,
14:58
he's
14:59
asking
14:59
all
14:59
team
14:59
members
15:00
to
15:00
work
15:00
in
15:00
person
15:01
at
15:01
least
15:01
three
15:01
times
15:02
a
15:02
week,
15:02
adding
15:03
that
15:03
there
15:03
will
15:03
be
15:03
flexibility,
15:04
including
15:05
allowing
15:05
employees
15:06
to
15:06
decide
15:06
which
15:07
three
15:07
days
15:08
to
15:08
work
15:08
in
15:08
person.
15:09
Sounds
15:09
a
15:09
little
15:09
half
15:10
pregnant
15:10
to
15:10
me.
15:10
Target
15:11
reportedly
15:11
doesn't
15:12
mandate
15:12
its
15:12
employees
15:13
to
15:13
work
15:13
remotely
15:14
or
15:14
in
15:14
person.
15:14
Rather,
15:15
individual
15:15
leaders
15:15
make
15:16
the
15:16
decision
15:17
based
15:17
on
15:17
what's
15:18
best
15:18
for
15:18
their
15:18
teams.
15:19
Starbucks,
15:20
in
15:20
contrast,
15:20
said
15:21
employees
15:21
will
15:21
have
15:22
to
15:22
work
15:22
in
15:22
the
15:22
office
15:22
a
15:23
minimum
15:23
of
15:23
four
15:24
days
15:24
a
15:24
week,
15:25
Monday,
15:25
Tuesday,
15:26
Wednesday
15:26
and
15:26
Thursday,
15:27
starting
15:28
in
15:28
October.
15:29
The
15:29
new
15:29
requirement,
15:30
which
15:30
is
15:30
up
15:31
from
15:31
a
15:31
previous
15:32
one
15:32
of
15:32
three
15:32
days,
15:33
applies
15:34
to
15:34
workers
15:34
in
15:34
Starbucks,
15:35
Seattle
15:35
and
15:35
Toronto
15:36
support
15:36
centers.
15:37
As
15:37
well
15:37
as
15:37
North
15:38
American
15:38
regional
15:39
offices
15:40
for
15:40
workers
15:40
who
15:41
decide
15:41
to
15:41
opt
15:42
out
15:42
and
15:42
leave
15:43
the
15:43
company.
15:43
Instead
15:43
of
15:44
meet
15:44
the
15:44
new
15:44
four
15:44
day
15:45
requirement,
15:46
Starbucks
15:46
is
15:46
offering
15:46
a,
15:47
quote,
15:47
one
15:47
time
15:48
voluntary
15:48
exit
15:49
program
15:49
with
15:49
a
15:49
cash
15:50
payment,
15:50
end
15:50
quote.
15:51
David,
15:52
lots
15:53
of
15:53
companies
15:53
are
15:53
instituting
15:54
backed
15:54
office
15:54
policies
15:55
this
15:55
week.
15:55
Some
15:56
mandating
15:56
four
15:56
days
15:57
like
15:57
Starbucks,
15:57
others
15:57
like
15:58
Target,
15:58
keeping
15:58
it
15:58
loose
15:59
as
15:59
far
15:59
as
15:59
when
16:00
people
16:00
need
16:00
to
16:00
be
16:00
in
16:01
the
16:01
office
16:01
for
16:01
their
16:02
three
16:02
expected
16:03
days.
16:04
Is
16:04
there
16:04
a
16:04
best
16:05
practice
16:05
across
16:06
the
16:06
industry
16:06
at
16:06
this
16:07
point
16:07
or
16:07
how
16:07
should
16:07
retail
16:08
executives
16:08
think
16:09
about
16:09
this
16:09
challenge?
16:11
Yeah,
16:11
this
16:11
is
16:12
a
16:12
super
16:12
interesting
16:12
one,
16:13
Chris,
16:14
to
16:14
me.
16:14
Like,
16:14
I
16:15
don't
16:15
know
16:15
if
16:15
there's
16:15
a
16:15
best
16:16
practice.
16:16
I
16:16
will
16:17
say
16:17
this,
16:17
that
16:18
the
16:19
majority
16:20
of
16:20
my
16:20
clients,
16:21
and
16:21
I
16:21
think
16:21
our
16:21
clients
16:22
are
16:23
moving
16:23
back
16:23
towards
16:24
this.
16:24
Right.
16:24
And
16:25
you
16:25
know,
16:25
being
16:26
in
16:26
the
16:26
office
16:26
more,
16:27
I
16:28
don't
16:28
think
16:28
it's
16:28
going
16:29
back
16:29
to
16:30
five
16:30
days
16:30
a
16:31
week
16:32
anytime
16:32
soon.
16:33
I
16:33
do
16:33
think
16:33
there's
16:34
been
16:34
some
16:34
lessons
16:34
learned
16:36
about
16:36
that.
16:37
You
16:37
can
16:37
have
16:37
some
16:38
remote
16:38
workforce
16:39
and
16:39
there's
16:41
a
16:41
work
16:41
life
16:42
balance
16:42
that
16:43
just
16:44
naturally
16:44
comes
16:44
with
16:45
not
16:45
being
16:45
in
16:45
the
16:45
office
16:46
five
16:46
days
16:47
a
16:47
week.
16:47
But
16:48
on
16:48
the
16:48
flip
16:48
side
16:48
of
16:49
that,
16:49
I
16:50
will
16:50
tell
16:50
you
16:50
that
16:50
the
16:51
clients
16:51
that
16:51
I
16:51
see
16:51
that
16:52
are
16:52
in
16:52
the
16:52
office
16:52
more,
16:53
collaborating
16:54
more,
16:55
just
16:56
being
16:56
in
16:56
the
16:57
same
16:57
room
16:57
to
16:58
make
16:58
big
16:58
decisions
17:00
are
17:00
more
17:00
productive,
17:02
they're
17:02
more
17:03
efficient,
17:03
and
17:05
I
17:05
actually
17:05
think
17:05
they
17:06
make
17:06
better
17:06
decisions
17:07
because
17:08
there's
17:08
just
17:08
something
17:09
about
17:09
the
17:09
human
17:09
element
17:10
that
17:10
is
17:10
missing
17:10
on
17:12
when
17:12
you're,
17:13
you
17:13
know,
17:13
three,
17:13
four,
17:14
five
17:14
days
17:14
a
17:14
week
17:15
on,
17:15
on
17:16
zoom
17:16
calls,
17:16
you
17:16
don't
17:16
build
17:17
relationships
17:17
as
17:18
well.
17:19
You
17:19
really
17:19
can't
17:20
have
17:21
as
17:21
active
17:21
a
17:22
debate
17:22
where
17:22
you're,
17:23
you
17:23
know,
17:23
getting
17:24
super
17:24
demonstrative
17:25
or
17:26
whatever
17:26
in
17:26
the
17:26
room,
17:27
you
17:27
know,
17:27
being
17:27
very
17:28
Italian
17:28
and
17:28
talking
17:29
with
17:29
your
17:29
hands.
17:30
But
17:30
I
17:30
never
17:31
thought
17:31
about
17:31
that.
17:31
Yeah,
17:32
yeah.
17:32
So
17:33
I'm
17:33
surprised
17:33
it's
17:34
taken
17:34
this
17:34
long,
17:35
quite
17:35
frankly.
17:36
Kind
17:36
of
17:37
COVID
17:39
But
17:39
I
17:39
do
17:39
think
17:41
if
17:41
I
17:41
was
17:42
to
17:42
think
17:42
about
17:42
kind
17:43
of
17:43
a
17:43
best
17:43
practice
17:43
and
17:44
if
17:44
it
17:45
was
17:45
my
17:45
company,
17:46
I
17:47
would
17:47
probably
17:47
have
17:47
three,
17:48
four
17:48
days
17:48
a
17:48
week
17:49
with
17:50
some
17:50
flexibility
17:51
because
17:51
I
17:52
think
17:52
there
17:52
is
17:52
huge
17:52
value
17:53
to
17:53
being
17:54
in
17:54
person
17:55
now.
17:56
Do
17:57
I
17:57
hate
17:57
traveling
17:58
as
17:58
much
17:58
now
17:59
again
18:00
as
18:00
I
18:00
do
18:02
and
18:02
being
18:02
away
18:02
from
18:03
the
18:03
family?
18:03
Probably,
18:04
sure.
18:05
But
18:05
I
18:05
do
18:05
think
18:06
for
18:06
the
18:06
companies
18:07
there's
18:07
value.
18:08
Yeah.
18:08
There's
18:09
puts
18:09
and
18:09
takes
18:09
with
18:09
every
18:10
job
18:10
really.
18:10
At
18:10
the
18:10
end
18:10
of
18:10
the
18:11
day.
18:11
David,
18:11
let
18:11
me
18:11
ask
18:11
you,
18:12
because
18:12
we
18:13
put
18:13
both
18:13
of
18:13
these
18:13
headlines
18:14
in
18:14
on
18:15
purpose,
18:15
the
18:15
Starbucks
18:16
and
18:16
the
18:16
target
18:16
dichotomy
18:17
in
18:17
terms
18:17
of
18:18
how
18:18
they're
18:18
handling
18:18
it.
18:19
Do
18:19
you
18:19
think,
18:20
I'm
18:20
curious,
18:21
do
18:21
you
18:22
approve
18:22
of
18:22
one
18:22
approach
18:22
over
18:23
the
18:23
other?
18:23
Say
18:23
Starbucks
18:24
saying
18:24
you
18:24
have
18:24
to
18:24
be
18:25
in
18:25
these
18:25
four
18:25
days.
18:26
Whereas
18:26
Target
18:26
saying
18:27
it's
18:27
up
18:28
to
18:28
the
18:28
individual
18:28
manager's
18:29
discretion
18:29
which
18:29
three
18:30
days
18:30
of
18:30
the
18:30
week
18:30
they
18:30
want
18:31
to
18:31
be
18:31
in.
18:33
How
18:33
do
18:33
you
18:33
think
18:33
about
18:33
that?
18:34
Is
18:34
there
18:35
a
18:36
right
18:36
or
18:36
a
18:36
wrong.
18:36
Way
18:36
to
18:36
do
18:36
that?
18:37
Yeah,
18:37
no,
18:37
I
18:38
do
18:38
think
18:38
there
18:38
is
18:38
a
18:38
right
18:38
way.
18:39
I
18:39
do
18:39
think
18:39
if
18:39
you're
18:40
gonna,
18:40
you
18:40
know,
18:40
pick
18:41
some
18:41
minimum
18:41
number
18:42
of
18:42
days,
18:43
you
18:43
have
18:43
to
18:43
define
18:44
those
18:44
days.
18:44
Otherwise
18:45
the
18:45
standardized
18:46
three
18:47
days.
18:47
Right.
18:47
You
18:47
know,
18:48
that
18:48
leaves
18:48
40%
18:48
of
18:49
the
18:49
time.
18:49
And
18:50
if
18:50
you
18:50
do
18:50
the
18:50
math,
18:51
and
18:51
I'm
18:51
not
18:51
gonna
18:51
do
18:51
the
18:52
math
18:52
right
18:52
now,
18:52
but
18:53
you,
18:54
you
18:54
could
18:54
end
18:54
up
18:55
with
18:55
one
18:55
day
18:55
a
18:55
week
18:56
overlap.
18:57
Right.
18:57
And
18:57
you
18:57
know,
18:58
what,
18:58
what
18:59
have
18:59
you
18:59
really
18:59
accomplished
19:00
there
19:00
then?
19:00
Right.
19:01
You
19:01
know,
19:01
set
19:01
the
19:01
operating
19:02
rhythms
19:02
of
19:02
the
19:03
company
19:03
and,
19:03
you
19:03
know,
19:04
set
19:04
a
19:04
series
19:04
of
19:04
meetings
19:05
where
19:05
people
19:05
can
19:05
be
19:06
together.
19:07
And
19:07
I'm
19:07
not
19:07
a
19:07
huge
19:07
advocate
19:08
of
19:08
meeting
19:08
just
19:08
for
19:09
meeting
19:09
sake,
19:09
but
19:10
like,
19:11
but
19:11
if
19:11
you're
19:11
going
19:11
to
19:12
have
19:12
the
19:12
benefit
19:12
of
19:12
people
19:12
being
19:13
in
19:13
the
19:13
office,
19:13
you
19:14
actually
19:14
have
19:14
to
19:14
have
19:14
them
19:14
in
19:14
the
19:14
office
19:15
together.
19:17
So
19:17
I
19:17
would
19:17
mandate,
19:18
you
19:18
know,
19:18
whether
19:18
it's
19:19
Tuesday
19:19
to
19:19
Thursday
19:19
or
19:20
whatever,
19:20
but,
19:21
but
19:22
I,
19:22
I
19:22
would
19:22
go
19:22
to
19:22
the
19:23
mandate
19:23
route.
19:24
Yeah.
19:24
Otherwise
19:24
you're
19:25
on,
19:25
on.
19:25
You're
19:25
in
19:26
the
19:26
office
19:26
on
19:26
Zoom
19:26
with
19:27
many
19:27
people
19:27
still.
19:28
And
19:28
I
19:28
saw
19:28
you
19:28
shaking
19:29
your
19:29
head.
19:30
Do
19:30
you
19:30
agree
19:30
with
19:31
that?
19:31
Yeah,
19:31
I
19:31
mean,
19:32
I
19:32
think
19:32
it's
19:32
just,
19:33
it
19:33
seems
19:33
like
19:33
it's
19:33
actually
19:34
more
19:34
work
19:34
when
19:35
you
19:35
don't
19:35
specify
19:36
what
19:36
the
19:36
days
19:36
are
19:37
like
19:37
on
19:37
top
19:37
of
19:38
just
19:38
what
19:38
David
19:39
was
19:39
saying.
19:39
Trying
19:39
to
19:39
make
19:39
sure
19:39
that
19:40
you're
19:40
getting
19:40
Zoom
19:40
calls
19:41
coordinated
19:42
when
19:42
people
19:42
are
19:43
not
19:43
in
19:43
the
19:43
office.
19:44
Like
19:44
now
19:44
you
19:44
have
19:45
to
19:45
have
19:45
that
19:45
extra
19:46
layer
19:46
for
19:46
each
19:47
one
19:47
of
19:47
those
19:47
managers
19:48
to
19:48
figure
19:48
out.
19:50
And
19:50
I
19:50
just
19:50
think,
19:50
like,
19:51
that
19:51
it
19:51
also
19:52
seems
19:52
a
19:52
little
19:53
disruptive
19:54
to
19:54
the
19:54
whole
19:55
organization
19:55
too.
19:56
Like,
19:56
I
19:56
think
19:57
the
19:57
Starbucks
19:57
approach
19:57
makes
19:58
much
19:58
more
19:58
sense.
19:59
Like,
19:59
you're
19:59
not
20:00
just
20:00
working
20:00
at
20:01
a
20:01
Target,
20:01
you're
20:01
not
20:02
just
20:02
working
20:02
with
20:02
your
20:03
team.
20:03
Like
20:04
you're
20:04
working
20:04
with
20:04
teams
20:05
throughout
20:05
the
20:05
organization,
20:06
hopefully.
20:07
And
20:07
so
20:08
I
20:08
think
20:08
standardizing
20:09
it
20:09
makes
20:09
a
20:09
lot
20:09
more
20:10
sense.
20:10
Yeah,
20:10
I
20:11
100%,
20:11
I,
20:11
I
20:12
100%
20:12
agree
20:12
with
20:12
you
20:12
and
20:13
I
20:13
think,
20:13
I
20:13
think
20:13
you
20:13
said
20:13
it
20:14
very
20:14
well.
20:14
Chad.
20:14
Chad,
20:15
what's
20:15
your
20:15
take?
20:15
Do
20:16
you
20:16
have
20:16
any
20:16
other
20:16
light
20:16
you'd
20:17
share
20:17
on
20:17
this,
20:17
given
20:17
your
20:18
personal
20:18
experience
20:18
in
20:19
working
20:19
with
20:19
retailers
20:20
across
20:20
the
20:20
industry?
20:21
Yeah,
20:21
I
20:22
mean,
20:22
I'd
20:22
agree
20:22
with
20:22
everything
20:22
David
20:23
said
20:23
in
20:23
terms
20:23
of
20:24
the
20:24
merits
20:24
and
20:24
values
20:25
and
20:25
what
20:25
we've
20:26
observed
20:26
and
20:26
experience
20:27
of,
20:27
of
20:27
in
20:28
person
20:28
work.
20:28
Right.
20:29
You
20:29
know,
20:30
easier
20:31
to
20:31
maintain
20:31
relationships
20:32
remotely,
20:33
harder
20:33
to
20:33
build
20:34
new
20:34
ones,
20:35
decisions
20:35
get
20:35
made
20:36
faster.
20:37
And
20:38
quite
20:38
frankly,
20:38
psychologically.
20:39
Right.
20:39
People
20:40
have
20:40
feelings
20:41
of
20:41
Higher
20:41
collaboration
20:42
that
20:42
is
20:43
less
20:43
transactional
20:43
when
20:44
they're
20:44
in
20:44
person.
20:45
We're
20:45
generally
20:46
social
20:46
creatures,
20:47
so
20:47
I
20:47
would
20:47
also
20:47
imagine
20:48
in
20:48
person
20:48
leads
20:49
to
20:49
higher
20:49
engagement,
20:50
more
20:50
connection
20:51
and
20:51
loyalty
20:52
to
20:52
the
20:52
job
20:52
and
20:53
company.
20:53
Higher
20:53
satisfaction.
20:55
Don't
20:55
have
20:55
the
20:55
data,
20:55
but,
20:56
you
20:56
know,
20:56
as
20:56
you
20:56
guys
20:57
are
20:57
debating
20:58
Starbucks
20:58
versus
20:59
Target's
20:59
model
20:59
and
21:00
which
21:00
is
21:00
better
21:00
and
21:01
you
21:01
know,
21:01
kind
21:01
of
21:01
the
21:02
practicality
21:03
of
21:03
logistics
21:04
aside,
21:05
you
21:05
know,
21:05
I,
21:05
I
21:06
think
21:06
what
21:06
I'd
21:06
add
21:06
is
21:06
like
21:07
corporate
21:07
cultures
21:07
are
21:08
different
21:08
and
21:09
policies
21:09
need
21:10
to
21:10
align
21:10
with
21:11
the
21:11
values
21:12
and
21:12
cultural
21:13
norms
21:13
of
21:13
that
21:14
company.
21:14
Right.
21:15
They
21:15
have
21:15
to
21:15
balance
21:16
the
21:16
productivity
21:17
with
21:17
recruitment
21:18
and
21:18
retention.
21:20
It
21:20
can't
21:20
be
21:21
viewed
21:21
in
21:21
a
21:21
vacuum.
21:21
Right.
21:22
So
21:22
how
21:22
employees
21:23
are
21:23
treated
21:24
and
21:24
respected
21:25
and
21:25
valued
21:26
in
21:26
other
21:27
ways
21:27
than
21:27
just
21:27
office
21:28
policy.
21:29
Right.
21:29
So,
21:30
you
21:30
know,
21:30
maybe
21:30
an
21:31
illusion
21:31
of
21:32
flexibility
21:33
when
21:33
corporate
21:33
culture
21:34
is
21:34
way
21:34
more
21:35
restrictive.
21:35
Right.
21:36
Can
21:36
just
21:36
be
21:36
lip
21:37
service.
21:37
Or
21:38
if
21:38
you
21:38
do
21:38
have
21:39
a
21:39
more
21:39
restricted
21:40
mandatory
21:40
policy,
21:41
but
21:41
employees
21:42
do
21:42
feel
21:43
valued
21:43
and
21:43
respected,
21:44
it
21:44
can
21:44
work
21:45
and
21:45
make
21:45
sense.
21:46
So
21:46
I
21:46
would
21:46
just,
21:47
you
21:47
know,
21:47
continue
21:47
to
21:48
advise
21:49
companies
21:49
to
21:50
make
21:50
sure
21:50
that
21:50
the
21:50
policies
21:51
that
21:51
they're
21:51
doing
21:52
aligns
21:53
with
21:53
their
21:53
overall
21:53
culture
21:54
and
21:54
values.
21:55
Yeah.
21:56
The
21:56
point
21:56
I'd
21:56
add
21:56
on
21:57
top
21:57
of
21:57
that,
21:57
and
21:57
I'm
21:57
not,
21:58
I've
21:58
been
21:58
thinking
21:58
about
21:58
this
21:58
a
21:58
lot.
21:59
I'm
21:59
not
21:59
sure
21:59
exactly
21:59
how
22:00
to
22:00
articulate.
22:00
So
22:00
you
22:00
guys
22:01
will
22:01
need
22:01
to
22:01
give
22:01
me
22:01
some
22:01
space
22:01
here
22:02
and
22:02
maybe
22:02
even
22:02
help
22:02
me
22:03
out
22:03
to
22:03
articulate
22:03
it.
22:04
I
22:05
think
22:05
in
22:05
a
22:05
D.
22:05
In
22:05
addition
22:06
to
22:06
the
22:06
culture,
22:06
there's
22:07
also
22:07
the
22:07
work
22:07
that
22:08
is
22:08
required
22:08
from
22:09
the
22:09
company
22:09
itself
22:10
inside
22:10
of
22:10
that
22:10
culture.
22:11
And
22:11
so,
22:11
you
22:12
know,
22:12
I
22:12
look
22:12
at
22:12
Target
22:13
and
22:13
the
22:13
commercial
22:13
team,
22:14
that's
22:14
basically
22:14
the
22:15
merchant
22:15
and
22:15
the
22:15
inventory
22:16
planning
22:16
teams,
22:16
the
22:16
planning
22:17
and
22:17
allocation
22:17
teams.
22:18
And
22:18
you
22:19
know,
22:19
I,
22:19
as
22:19
I
22:19
was
22:20
stepping
22:20
back
22:20
from
22:20
this
22:20
story
22:21
both
22:21
for
22:21
Starbucks
22:21
and
22:21
Target,
22:22
I
22:22
was
22:22
like,
22:22
okay,
22:22
yeah,
22:22
if
22:22
your
22:23
job
22:23
is
22:23
to
22:23
put
22:24
products
22:24
in
22:25
front
22:25
of
22:26
customers
22:26
in
22:27
physical
22:27
spaces,
22:28
it
22:28
probably
22:28
is
22:29
important
22:29
for
22:29
you
22:29
to
22:30
work
22:30
together
22:31
to
22:31
get
22:31
into
22:32
the
22:32
stores
22:32
together
22:32
to
22:33
understand
22:33
that,
22:33
to
22:34
be
22:34
in
22:34
charge
22:34
of
22:34
that,
22:35
to
22:35
make
22:36
it
22:36
work
22:36
the
22:36
best
22:36
way.
22:37
Because
22:37
my
22:37
guess,
22:38
and
22:38
from
22:38
what
22:38
I'm
22:38
hearing
22:38
from
22:39
a
22:39
lot
22:39
of
22:39
people,
22:39
and
22:39
I've
22:40
been
22:40
hearing
22:40
this
22:40
for
22:40
the
22:40
past
22:41
two
22:41
or
22:41
three
22:41
years,
22:41
the
22:42
remote
22:42
work
22:43
has
22:43
been
22:43
a
22:43
big
22:44
reason
22:44
why
22:44
we're
22:44
seeing
22:45
all
22:45
these
22:45
pictures
22:45
of
22:46
Targets
22:46
out
22:46
of
22:47
stock
22:47
shelves
22:48
throughout
22:48
social
22:48
media
22:49
constantly.
22:50
And
22:50
that's
22:50
because
22:50
I
22:51
think
22:51
these
22:51
teams
22:51
are
22:51
not
22:52
together
22:52
working
22:53
through
22:53
the
22:53
issues
22:53
and
22:54
not,
22:54
you
22:54
know,
22:54
going
22:55
down
22:55
to
22:55
the
22:55
store
22:56
right
22:56
next
22:56
door
22:56
and
22:57
being
22:57
like,
22:57
look,
22:57
what
22:57
are
22:57
we
22:58
doing
22:58
about
22:58
this?
22:58
You
22:59
can't
22:59
get
22:59
together
22:59
to
23:00
solve
23:00
that
23:00
problem
23:01
in
23:01
a
23:01
way
23:01
that's,
23:02
that's
23:02
easy
23:03
and
23:03
efficient.
23:04
So
23:04
I,
23:04
that's
23:05
the.
23:05
Sorry
23:06
for
23:06
not
23:06
articulating
23:07
that
23:07
as
23:07
well
23:07
as
23:07
I
23:08
normally
23:08
would
23:08
try
23:08
to
23:08
do,
23:09
but
23:09
I
23:09
think
23:09
there's
23:09
something
23:10
to
23:10
that
23:10
in
23:10
terms
23:10
of
23:10
the
23:11
work
23:11
that
23:11
has
23:11
to
23:11
be
23:12
done
23:12
as
23:12
well.
23:13
Chris,
23:13
you
23:13
bring
23:13
up
23:14
a
23:14
really
23:14
good
23:14
point,
23:14
too.
23:14
It's
23:15
like,
23:15
how
23:15
is
23:15
this
23:15
being
23:16
measured,
23:16
too?
23:16
Like,
23:17
I,
23:17
I
23:17
don't
23:17
know.
23:18
Like,
23:18
are
23:18
we,
23:18
or
23:19
is
23:19
it
23:19
just
23:19
simply,
23:20
like,
23:20
productivity
23:21
that's
23:21
being
23:21
measured
23:22
once
23:22
people
23:22
are
23:22
coming
23:23
back
23:23
to
23:23
work?
23:23
But,
23:23
like,
23:24
are
23:24
there
23:25
teams
23:25
at
23:25
these,
23:26
at
23:26
these
23:27
eight,
23:27
these
23:27
companies
23:28
who
23:28
are
23:28
really
23:28
investigating,
23:29
like,
23:29
what
23:30
positives
23:30
are
23:30
we
23:31
seeing
23:31
from
23:31
this?
23:31
Like,
23:32
how
23:32
do
23:32
we
23:32
measure
23:33
the
23:33
success
23:33
of
23:34
our
23:34
organizations
23:35
after
23:35
being
23:35
able
23:35
to
23:36
do
23:36
that?
23:36
Is
23:36
it
23:36
just
23:37
full
23:37
shelves
23:37
or,
23:38
you
23:38
know,
23:38
what
23:38
else
23:38
are
23:39
they
23:39
tracking
23:39
to
23:40
make
23:40
sure
23:40
that
23:40
they.
23:40
This
23:40
is
23:40
the
23:41
right
23:41
move,
23:41
too?
23:42
Well,
23:42
that's,
23:42
that's
23:42
a
23:42
pretty
23:43
easy
23:43
measurable
23:44
metric.
23:45
You
23:45
know,
23:45
like,
23:46
do
23:46
we
23:46
see
23:46
in
23:46
stock
23:47
improvement
23:47
once
23:48
we
23:48
force
23:48
the
23:48
teams
23:49
back
23:49
in
23:49
the
23:49
office?
23:49
I
23:49
mean,
23:50
that's,
23:50
that's
23:50
one.
23:51
Can
23:51
you
23:51
correlate
23:51
it
23:51
directly?
23:52
No.
23:52
Is
23:52
it
23:53
required?
23:53
Not
23:53
necessarily,
23:54
but
23:55
it
23:55
probably
23:55
doesn't
23:56
hurt.
23:56
Right.
23:57
All
23:57
right,
23:57
let's
23:58
move
23:58
on
23:58
to
23:58
headline
23:58
number
23:59
three.
23:59
Tariff
24:00
driven
24:00
inflation
24:01
may
24:01
now
24:01
be
24:02
starting
24:02
to
24:02
emerge.
24:03
According
24:03
to
24:04
the
24:04
Associated
24:04
Press,
24:05
inflation
24:05
rose
24:05
last
24:06
month
24:06
to
24:06
its
24:06
highest
24:07
level
24:07
since
24:07
February
24:07
as
24:08
President
24:08
Donald
24:08
Trump's
24:09
sweeping
24:09
tariffs
24:10
push
24:10
up
24:10
the
24:10
cost
24:11
of
24:11
a
24:11
range
24:11
of
24:11
goods,
24:12
including
24:12
furniture,
24:12
clothing,
24:13
and
24:13
large
24:13
appliances.
24:14
Consumer
24:15
prices
24:15
rose
24:15
2.7%
24:16
in
24:17
June
24:17
from
24:17
a
24:17
year
24:18
earlier,
24:18
the
24:18
Labor
24:19
Department
24:19
said
24:20
on
24:20
Tuesday,
24:21
up
24:21
from
24:22
an
24:22
annual
24:22
increase
24:23
of
24:23
2.4%
24:24
in
24:24
May.
24:24
On
24:25
a
24:25
monthly
24:25
basis,
24:25
prices
24:26
climbed
24:26
0.3%
24:27
from
24:28
May
24:28
to
24:28
June
24:28
after
24:28
rising
24:29
just
24:29
0.1%
24:30
the
24:30
previous
24:31
month.
24:31
Excluding
24:32
the
24:32
volatile
24:33
food
24:33
and
24:33
energy
24:34
categories,
24:34
core
24:35
inflation
24:35
raised
24:36
2.9%
24:37
in
24:37
June
24:37
from
24:37
a
24:37
year
24:37
earlier,
24:38
up
24:38
from
24:38
2.98%
24:39
in
24:40
May.
24:40
On
24:40
a
24:41
monthly
24:41
basis,
24:41
it
24:41
picked
24:42
up
24:42
0.2%
24:43
from
24:43
May
24:43
to
24:44
June.
24:44
David,
24:45
I
24:45
hope
24:45
you
24:45
were
24:45
keeping
24:46
track
24:46
of
24:46
all
24:46
those
24:47
percentages
24:47
as
24:48
I
24:48
was
24:48
reading
24:48
them.
24:49
What
24:50
impact
24:51
do
24:51
you
24:51
predict
24:52
tariffs
24:52
will
24:53
have
24:53
on
24:53
retail
24:54
for
24:54
this
24:54
upcoming
24:55
holiday
24:55
season?
24:57
Yeah,
24:57
so
24:58
it's
24:58
a
24:58
great
24:58
question.
24:58
And,
24:59
and
25:00
I
25:01
think
25:01
the
25:01
short
25:01
answer
25:02
is,
25:02
don't
25:02
know
25:03
yet.
25:04
We're
25:05
getting
25:05
dangerously
25:06
close.
25:06
But
25:06
let's
25:06
be
25:07
honest,
25:07
without
25:07
getting
25:07
into
25:07
the
25:07
whole
25:08
political
25:08
discussion,
25:10
President
25:11
Trump's
25:11
playing
25:11
a
25:12
giant
25:12
game
25:12
of
25:12
chicken
25:13
with
25:13
the
25:13
rest
25:13
of
25:13
the
25:14
world.
25:14
Right.
25:15
In
25:15
terms
25:16
of
25:16
who's
25:17
going
25:17
to
25:17
blink
25:17
first,
25:19
because
25:19
I
25:19
think
25:20
nobody
25:20
believes
25:22
that,
25:23
you
25:23
know,
25:23
high
25:24
tariffs
25:24
across
25:25
the
25:25
world
25:25
are
25:26
a
25:26
good
25:26
thing.
25:27
Right.
25:27
And
25:29
if
25:29
there
25:29
isn't
25:30
resolution,
25:31
I
25:31
think
25:31
it's
25:31
going
25:31
to
25:31
have
25:32
an
25:32
enormous
25:32
impact
25:33
on
25:34
the
25:35
holiday
25:35
season,
25:37
you
25:37
know,
25:37
across
25:38
all
25:38
categories,
25:39
whether
25:39
it's
25:39
luxury
25:40
goods,
25:40
toys,
25:42
apparel,
25:44
it
25:44
really
25:44
doesn't
25:45
matter.
25:46
Everything
25:47
is
25:47
going
25:48
to
25:48
be
25:48
affected.
25:49
And
25:51
you
25:51
know,
25:51
there's
25:51
a,
25:51
it's
25:52
just
25:52
a
25:52
share
25:52
of
25:52
wallet
25:53
issue.
25:53
Right.
25:54
People
25:55
have
25:55
so
25:55
much
25:55
money
25:55
to
25:56
spend
25:56
on
25:57
holiday
25:58
gifts
25:58
and
25:59
family
25:59
excursions
26:00
and,
26:00
and
26:00
everything
26:01
along
26:01
those
26:01
lines.
26:02
And,
26:03
and
26:03
I
26:03
think
26:03
you're
26:03
going
26:03
to
26:04
see
26:04
a
26:04
rebalancing
26:05
of
26:05
how
26:06
those
26:06
dollars
26:06
get
26:07
spent
26:08
to
26:09
more
26:09
experiential
26:10
things
26:10
as
26:11
opposed
26:11
to
26:11
less
26:12
material
26:12
things
26:13
if
26:14
they
26:14
still
26:14
end
26:14
up
26:15
being
26:15
kind
26:16
of
26:16
20,
26:16
30,
26:17
40%
26:17
more
26:18
expensive.
26:20
But
26:21
nobody
26:22
could
26:23
tell
26:23
you
26:23
right
26:23
now
26:23
with
26:23
any
26:24
certainty
26:25
what
26:25
the
26:25
tariffs
26:26
are
26:26
going
26:26
to
26:26
be
26:27
when
26:27
we
26:27
get
26:27
into
26:27
the
26:27
heart
26:28
of
26:28
the
26:28
holiday
26:28
season.
26:30
And
26:30
anybody
26:31
that
26:31
says
26:31
they
26:31
can
26:32
is,
26:32
is,
26:33
you
26:33
know,
26:33
either
26:33
lying
26:34
or
26:34
hopeless,
26:35
hopelessly
26:36
optimistic.
26:37
Right.
26:37
Or,
26:38
you
26:38
know,
26:38
and
26:38
who
26:39
knows
26:39
what
26:39
products
26:39
will
26:40
be
26:40
on
26:40
shelves.
26:40
Chris,
26:40
you
26:40
were
26:41
just
26:41
talking
26:41
about
26:41
this
26:41
in
26:41
the
26:42
last
26:42
headline,
26:42
like
26:42
we're
26:43
already
26:43
seeing
26:43
out
26:44
of
26:44
stocks
26:44
at
26:45
Target
26:45
and
26:45
other
26:46
places.
26:46
What
26:47
do
26:47
you
26:47
think
26:48
as
26:48
a
26:48
former
26:48
merchant
26:49
in
26:49
particular,
26:50
like,
26:50
what
26:50
do
26:50
you
26:50
think
26:50
we're
26:51
going
26:51
to
26:51
see
26:51
once
26:51
we
26:52
head
26:52
into
26:52
the
26:52
holiday
26:52
season
26:53
as
26:53
a
26:53
result
26:53
of
26:54
this?
26:54
Yeah,
26:55
I
26:55
agree
26:55
with
26:55
David.
26:56
Like,
26:56
we
26:56
don't
26:56
know
26:56
what
26:56
tariffs
26:57
will
26:57
be
26:57
in
26:57
place
26:58
during
26:58
the
26:58
holiday
26:58
season,
26:59
but
26:59
I
26:59
do
26:59
think
26:59
there
26:59
are
27:00
some,
27:00
you
27:01
know,
27:01
things
27:01
that
27:01
we
27:01
can
27:01
potentially
27:02
bet
27:02
on.
27:02
And
27:03
everyone
27:03
knows
27:03
I'm
27:03
on
27:03
this
27:03
show,
27:04
knows
27:04
I'm
27:04
a
27:04
betting
27:04
man
27:04
if
27:05
you
27:05
look
27:05
at
27:05
my
27:05
Kentucky
27:06
Derby
27:06
track
27:06
record.
27:07
But,
27:07
you
27:08
know,
27:08
I
27:08
think
27:08
if
27:08
I
27:08
was
27:08
betting
27:09
and
27:09
looking
27:09
at
27:09
what's
27:09
going
27:10
to
27:10
happen,
27:10
I
27:10
think
27:10
there's,
27:10
there's
27:11
two
27:11
things
27:11
I'm,
27:12
I'm
27:12
pretty
27:12
confident
27:13
about.
27:13
I
27:13
think,
27:13
one,
27:14
I
27:14
think
27:14
this
27:15
will
27:15
be
27:15
the
27:15
least
27:15
well
27:16
stocked
27:17
shelves
27:17
are
27:18
across
27:18
all
27:19
of
27:19
retail
27:19
that
27:19
we've
27:20
seen
27:20
for
27:20
a
27:20
long
27:20
time.
27:21
And
27:21
so,
27:21
and
27:22
so
27:22
that
27:22
then
27:22
therefore
27:23
means
27:24
the
27:25
proclivity
27:25
we've
27:26
seen
27:26
for
27:26
consumer
27:27
spending
27:27
to
27:27
get
27:27
pushed
27:28
up
27:28
into
27:28
October
27:29
by
27:29
way
27:29
of
27:30
Prime
27:30
Day,
27:30
which
27:30
kicks
27:31
it
27:31
off,
27:31
is
27:31
going
27:32
to
27:32
happen
27:32
even
27:32
more
27:33
this
27:33
year
27:33
because
27:33
people
27:34
are
27:34
going
27:34
to
27:34
need
27:34
to
27:34
get
27:35
in
27:35
there
27:35
and
27:35
get
27:35
what
27:36
they
27:36
can
27:36
when
27:36
they
27:37
can
27:37
get
27:37
it
27:38
for
27:38
those
27:38
gifts
27:38
and
27:39
for
27:39
the
27:39
holidays.
27:39
So
27:40
those
27:40
are
27:40
the
27:40
two
27:40
things
27:41
I
27:41
would
27:41
bet
27:41
on.
27:41
It's
27:42
not
27:42
going
27:42
to
27:42
be
27:42
great
27:43
stock
27:43
position
27:43
because
27:43
people
27:44
are
27:44
probably
27:44
waiting
27:44
to
27:45
decide
27:45
where
27:45
to
27:45
place
27:45
their
27:46
bets,
27:46
how
27:46
much
27:46
they're
27:46
going
27:46
to
27:47
place.
27:47
They
27:47
just
27:47
don't
27:47
know
27:48
yet.
27:48
At
27:48
least
27:48
that's
27:48
what
27:49
I'm
27:49
surmising.
27:49
But
27:49
you
27:50
guys,
27:50
A
27:50
and
27:50
M
27:51
group
27:51
can
27:51
probably
27:51
answer
27:51
that
27:52
better
27:52
than
27:52
I
27:52
can.
27:52
But
27:53
yeah,
27:53
I
27:53
think
27:53
you're
27:53
going
27:53
to
27:53
see
27:53
people
27:54
trying
27:54
to
27:54
Grab
27:54
things
27:54
as
27:55
quickly
27:55
as
27:55
they
27:55
can
27:55
on
27:56
deals
27:56
early
27:56
in
27:56
the
27:56
season
27:56
too.
27:57
Yeah,
27:58
and
27:58
I'm
27:58
curious
27:58
too,
27:59
you
27:59
know
27:59
Chad,
28:00
we'll
28:00
go
28:00
to
28:00
you
28:00
next.
28:01
But
28:01
I
28:01
also
28:02
wonder
28:02
like
28:02
the
28:02
mass
28:03
retailers
28:03
that
28:04
we're
28:04
talking
28:04
about,
28:04
the
28:04
Walmarts,
28:05
the
28:05
targets,
28:06
you
28:06
know,
28:06
the,
28:07
these
28:07
guys
28:07
are
28:08
prepared
28:09
more
28:09
or
28:09
have
28:10
the
28:10
ability
28:10
to
28:10
be
28:11
more
28:11
agile
28:11
when
28:12
it
28:12
comes
28:12
to
28:12
these
28:12
types
28:12
of
28:13
things.
28:13
I'm
28:13
wondering
28:14
what
28:14
the
28:14
small,
28:14
medium
28:15
sized
28:15
businesses
28:15
are
28:16
going
28:16
to
28:16
do
28:16
because
28:16
they
28:16
cannot
28:17
tolerate
28:18
the
28:18
flux,
28:19
the
28:19
constant
28:19
fluctuation.
28:21
And
28:21
I
28:21
think
28:22
that
28:22
also
28:23
impacts,
28:23
you
28:24
know,
28:24
when
28:24
it
28:24
comes
28:24
to
28:25
gift
28:25
giving
28:25
and
28:25
holiday
28:26
times
28:26
of
28:27
year.
28:27
You
28:27
know,
28:27
are
28:28
we
28:28
in
28:28
the
28:28
sea
28:28
of
28:29
sameness
28:29
where
28:29
it's
28:29
like
28:30
your
28:30
options
28:30
are
28:30
whatever
28:31
Target
28:31
and
28:31
Walmart
28:32
and
28:32
Amazon
28:32
still
28:33
have
28:33
left
28:33
in
28:33
stock
28:34
and
28:34
that's
28:34
what
28:34
you're
28:35
going
28:35
to
28:35
get?
28:35
There's
28:36
no,
28:36
there's,
28:36
you
28:36
know,
28:36
we
28:37
had
28:37
Chris
28:37
and
28:37
Sevilla
28:38
on
28:38
the
28:38
show
28:38
not
28:38
too
28:38
long
28:38
ago
28:39
talking
28:39
about
28:39
how
28:39
it's
28:40
the
28:40
sea
28:40
of
28:40
sameness.
28:41
We're
28:41
going
28:41
to
28:41
see,
28:41
you
28:42
know,
28:42
all,
28:42
all
28:43
beige
28:43
goods.
28:44
We're
28:44
not
28:44
going
28:44
to
28:44
see
28:44
the,
28:45
the
28:45
like
28:45
highlight
28:46
pop
28:46
of
28:46
color
28:46
in
28:47
apparel
28:47
or
28:47
accessories
28:48
that
28:49
used
28:49
to
28:49
be
28:49
that
28:49
intriguing
28:50
and
28:50
fun,
28:50
more
28:51
personal
28:51
kind
28:52
of
28:52
gift.
28:53
So
28:53
I,
28:53
I'm
28:53
curious
28:54
Chad,
28:54
like
28:54
what
28:55
do
28:55
you
28:55
think
28:56
shoppers
28:57
are
28:57
going
28:57
to
28:57
see?
28:58
Are
28:58
they
28:58
going
28:58
to
28:58
go
28:59
the
28:59
way
28:59
of
28:59
what
28:59
David's
29:00
saying
29:00
where
29:00
you
29:01
know,
29:01
they're
29:02
just
29:02
going
29:02
to
29:02
have
29:02
to
29:02
cross
29:03
their
29:03
fingers
29:03
and
29:03
hope
29:03
that
29:04
they
29:04
can
29:04
get
29:04
the
29:04
best
29:05
thing
29:05
possible
29:06
or
29:07
are
29:07
there
29:07
things
29:07
that
29:08
your
29:08
clients
29:09
or
29:09
that
29:09
other
29:09
retailers
29:10
and
29:10
brands
29:10
can
29:10
be
29:10
doing
29:11
now
29:11
to
29:11
kind
29:11
of
29:11
help
29:12
still
29:12
give
29:13
people
29:13
that
29:13
thing
29:14
to
29:14
shop
29:14
for
29:14
that
29:15
unique
29:15
gift?
29:16
Yeah,
29:18
really,
29:19
really
29:19
great
29:19
avenues
29:20
that,
29:20
that
29:21
you
29:21
guys
29:21
have
29:21
laid
29:22
out.
29:22
So
29:23
if
29:23
I
29:23
first
29:23
answer
29:24
from
29:24
kind
29:24
of
29:24
the
29:24
advisory
29:25
standpoint
29:26
and
29:26
then
29:26
maybe
29:26
the
29:26
prognostication
29:28
standpoint,
29:29
listen
29:29
with,
29:29
with
29:30
respect
29:30
to
29:30
tariffs
29:31
and,
29:32
and
29:32
actually
29:33
predating
29:33
that
29:34
to
29:34
the
29:34
last
29:34
round
29:35
of,
29:35
of
29:35
hyperinflation,
29:36
what,
29:36
what
29:37
we're
29:37
advising
29:37
our
29:38
clients
29:38
is
29:38
first
29:41
minimize
29:41
the
29:41
impact
29:42
as
29:42
much
29:42
as
29:42
possible.
29:42
Right.
29:43
Leave
29:43
no
29:44
stone
29:44
unturned.
29:45
When
29:45
it
29:45
comes
29:45
to
29:45
cost
29:46
reduction.
29:46
You
29:46
have
29:47
to
29:47
approach
29:47
it
29:47
there
29:48
first
29:49
before
29:49
even
29:50
testing
29:51
how
29:51
much
29:51
is
29:52
too
29:52
much
29:52
for
29:52
the
29:52
consumer
29:53
to
29:53
bear
29:53
in
29:53
pricing.
29:54
Like
29:54
a
29:54
hard
29:54
look
29:55
of
29:56
costs
29:56
across
29:57
the
29:57
board,
29:57
not
29:57
just
29:58
in
29:58
cogs
29:59
is,
29:59
is
29:59
mandatory
30:00
but
30:00
then
30:01
as
30:01
far
30:01
as
30:01
pricing
30:03
and
30:03
those
30:03
that
30:03
will
30:03
be
30:04
more
30:04
successful
30:04
in
30:05
that
30:05
then
30:05
have
30:05
the,
30:06
the
30:06
ability
30:06
to,
30:07
to
30:07
have
30:07
more
30:07
flexibility
30:08
to
30:08
your
30:08
point
30:08
and
30:09
you
30:09
know,
30:09
when
30:10
it
30:10
comes
30:10
to
30:10
pricing
30:10
like
30:11
especially
30:11
at
30:12
this
30:12
stage,
30:12
it
30:12
has
30:12
to
30:12
be
30:13
precise.
30:13
Right.
30:14
Looking
30:14
at
30:15
consumer
30:15
price
30:16
elasticities
30:16
buy
30:17
skew
30:18
being
30:18
selective
30:19
on
30:19
where
30:20
your
30:20
hikes
30:20
Versus
30:21
holds
30:21
are
30:23
blanket
30:23
moves
30:24
are
30:24
going
30:24
to
30:24
be
30:24
tough
30:25
to
30:25
do
30:25
again
30:25
more
30:26
broadly
30:26
or
30:27
people
30:27
are
30:27
going
30:27
to
30:27
find
30:27
themselves
30:28
out
30:28
of
30:28
the
30:28
market.
30:28
Right.
30:29
I
30:30
mean,
30:30
as
30:30
far
30:31
as
30:31
going
30:31
into
30:31
the
30:31
back
30:31
part
30:32
of
30:32
the
30:32
year
30:32
here,
30:32
I
30:33
mean,
30:33
I
30:33
agree.
30:33
Listen,
30:34
we
30:34
can't
30:35
predict
30:35
exactly
30:36
where
30:36
things
30:36
are
30:36
going
30:36
to
30:37
hit
30:37
and
30:37
how.
30:38
I
30:38
think
30:38
we
30:38
are
30:38
going
30:39
to
30:39
continue
30:39
to
30:39
see
30:39
upward
30:40
movement
30:40
in
30:41
kind
30:41
of
30:41
the
30:41
staples
30:41
and
30:42
essentials
30:42
categories.
30:43
So.
30:43
Okay,
30:44
grocery,
30:45
personal
30:45
care,
30:46
pet,
30:47
you
30:47
know,
30:47
and
30:48
private
30:48
labels,
30:49
not
30:49
exempt
30:49
from
30:49
these.
30:50
So
30:50
I
30:50
think
30:50
we'll,
30:51
we'll
30:51
likely
30:51
see
30:52
them
30:52
move
30:53
together.
30:53
And
30:54
where
30:54
you
30:55
may
30:55
see
30:55
more
30:55
holds,
30:56
especially
30:57
for
30:57
holiday
30:57
season,
30:58
here
30:58
is
30:58
in
30:59
your
30:59
more
31:00
traditional
31:01
gift
31:01
giving
31:02
discretionary
31:03
spend
31:03
areas
31:03
like
31:04
apparel
31:04
and
31:05
it'll
31:05
be
31:05
tough
31:06
but,
31:06
but
31:06
electronics,
31:07
right.
31:07
They're
31:07
too
31:08
important
31:08
for
31:08
the
31:08
season.
31:10
And
31:10
I
31:10
love
31:10
what
31:10
David
31:11
said.
31:11
We've
31:11
already
31:12
seen
31:12
shifting
31:13
last
31:13
year
31:13
toward
31:14
experiences
31:16
versus
31:16
goods
31:17
on
31:17
holiday
31:18
gift
31:18
giving.
31:20
But
31:20
I
31:20
also
31:20
agree,
31:21
I
31:21
mean
31:21
I,
31:21
I
31:22
think
31:22
it's
31:22
important
31:22
that
31:22
where
31:23
prices
31:23
do
31:24
rise,
31:24
I
31:25
expect
31:26
significantly
31:27
lower
31:27
inventory
31:28
positions
31:29
for
31:29
those
31:29
items
31:29
at
31:30
holiday.
31:30
Right.
31:30
I
31:30
think
31:31
retailers
31:31
will
31:31
be
31:31
more
31:32
content
31:33
to
31:33
sell
31:33
out,
31:35
you
31:35
know,
31:35
than
31:35
be
31:35
left
31:36
with
31:36
tremendously
31:37
expensive
31:37
inventory
31:38
piles.
31:38
And
31:39
so,
31:39
you
31:39
know,
31:39
it'll
31:40
be
31:40
those
31:40
that
31:40
can
31:41
manage
31:42
the
31:42
SKU
31:42
balance
31:43
with
31:43
how
31:43
they're
31:44
able
31:44
to
31:44
optimize
31:45
cost
31:46
and,
31:47
you
31:47
know,
31:48
pointed
31:49
pricing
31:50
actions
31:51
relative
31:52
to
31:52
inventory
31:52
for
31:53
the
31:53
season.
31:53
Man,
31:54
it's
31:54
a
31:54
tricky,
31:54
it's
31:55
a
31:55
tricky,
31:55
tricky
31:55
balance.
31:56
Yeah,
31:57
well
31:57
said.
31:57
I
31:58
don't,
31:59
I
31:59
don't
31:59
miss
31:59
being
32:00
in
32:00
those
32:00
rooms
32:00
making
32:01
those
32:01
decisions
32:01
one
32:01
bit
32:02
right
32:02
now,
32:02
especially
32:03
during,
32:03
with
32:03
this
32:03
climate.
32:04
All
32:04
right,
32:04
well,
32:04
let's
32:04
bring
32:05
Danele
32:05
onto
32:06
the
32:06
show
32:06
to
32:06
announce
32:07
July's
32:07
Retail
32:08
Tech
32:08
Startup
32:09
of
32:09
the
32:09
Month.
32:10
Foreign
32:12
let's
32:12
give
32:12
a
32:13
big
32:13
Omni
32:13
Talk
32:14
welcome
32:14
back
32:14
to
32:14
AWS's
32:15
Danele
32:16
Stropa.
32:17
Danielle
32:17
is
32:17
the
32:17
worldwide
32:18
technical
32:18
lead
32:18
for
32:19
AWS
32:19
Partners
32:20
in
32:20
Retail
32:20
at
32:20
Amazon
32:21
Web
32:21
Services,
32:22
where
32:22
he
32:22
drives
32:23
the
32:23
technical
32:23
strategy
32:24
for
32:24
AWS
32:25
Partners
32:25
in
32:25
Digital
32:26
Commerce,
32:26
Customer
32:27
Engagement
32:27
and
32:27
Generative
32:28
AI.
32:29
Danella,
32:30
it
32:30
is
32:30
hard
32:30
to
32:30
believe
32:30
that
32:31
it
32:31
has
32:31
already
32:31
been
32:31
one
32:32
month
32:32
since
32:32
we
32:32
handed
32:32
out
32:33
our
32:33
first
32:33
Retail
32:33
Startup
32:34
of
32:34
the
32:34
Month
32:34
award.
32:35
But
32:35
that
32:36
was
32:36
June.
32:37
Now
32:37
it's
32:37
July.
32:38
So
32:38
who
32:38
is
32:39
this
32:39
month's
32:39
Retail
32:40
Tech
32:40
Startup
32:41
of
32:41
the
32:41
Month?
32:42
This
32:42
month
32:43
peak
32:43
is
32:44
Braia
32:44
AI
32:45
and
32:45
I'm
32:46
really
32:46
excited
32:46
to
32:46
share
32:47
what
32:47
they're
32:48
doing
32:48
in
32:48
the
32:48
industry
32:49
and
32:49
how
32:49
they
32:50
are
32:50
revolutionizing
32:53
content
32:53
creation
32:54
for
32:54
brands.
32:55
So
32:55
Bria
32:56
B
32:56
R
32:56
I
32:57
AI.
32:59
Correct.
32:59
Yeah,
33:00
Bria
33:00
AI.
33:01
What
33:02
do
33:02
they
33:02
do?
33:03
Why
33:03
is
33:03
it
33:03
so
33:03
important
33:03
in
33:04
your
33:04
mind
33:04
and
33:04
what
33:05
kind
33:05
of
33:05
sets
33:05
them
33:05
apart
33:06
from
33:06
other
33:06
players
33:06
in
33:07
the
33:07
space?
33:09
So
33:09
Priya
33:10
is
33:10
a
33:11
visual
33:11
Generative
33:12
AI
33:12
platform.
33:14
However,
33:15
they
33:15
are
33:15
not
33:15
just
33:16
another
33:17
text
33:18
image
33:18
generator.
33:19
Right.
33:19
We've
33:20
seen
33:20
many
33:20
of
33:21
those.
33:22
They
33:23
built
33:23
what
33:23
they
33:24
called
33:25
build
33:25
their
33:26
first
33:26
platform
33:27
and
33:27
that
33:28
really
33:28
focuses
33:29
on
33:29
three
33:30
key
33:30
aspects,
33:31
three
33:31
key
33:31
things.
33:32
The
33:32
first
33:33
one
33:33
is
33:34
bringing
33:34
commercial
33:35
value
33:36
to
33:36
their
33:36
customer,
33:37
so
33:37
helping
33:38
businesses
33:39
creating
33:40
on
33:40
brand
33:41
content
33:41
that
33:42
actually
33:42
drives
33:43
results.
33:45
The
33:45
second
33:46
one
33:46
is
33:46
ease
33:47
of
33:47
integration.
33:48
So
33:48
their
33:48
technology
33:49
is
33:49
available
33:50
in
33:51
different
33:52
or
33:52
is
33:52
accessible
33:53
through
33:53
different
33:54
mechanisms
33:55
and
33:55
that
33:56
can
33:56
plug
33:56
right
33:56
into
33:58
existing
33:58
workflows.
33:59
So
33:59
ease
34:00
of
34:00
adoption
34:00
as
34:00
well.
34:02
The
34:02
last
34:03
one,
34:03
which
34:03
I
34:03
think
34:04
it's
34:04
huge
34:05
for
34:05
enterprises,
34:06
is
34:07
really
34:07
the
34:07
fact
34:07
that
34:09
the
34:09
content
34:10
that
34:11
Praia
34:11
creates
34:12
is
34:13
fully
34:13
compliant,
34:14
it's
34:14
safe
34:15
to
34:15
use.
34:16
Their
34:16
model
34:16
is
34:17
trained
34:17
on
34:18
properly
34:18
licensed
34:19
data
34:20
and
34:20
commercial
34:21
data.
34:22
So
34:22
that's
34:23
a
34:23
huge
34:23
aspect
34:24
for
34:25
enterprises.
34:27
One
34:28
thing
34:28
that
34:28
I
34:29
think
34:29
really
34:29
sets
34:30
Priya
34:31
apart
34:31
from
34:31
the
34:32
rest
34:32
is
34:33
the
34:33
ability
34:34
to
34:34
maintain
34:35
brand
34:36
integrity.
34:37
They
34:37
have
34:38
a
34:38
feature
34:38
called
34:39
tailored
34:40
generation
34:40
where
34:41
basically
34:41
customers
34:42
brands
34:43
can
34:44
take
34:44
Praia's
34:44
model,
34:45
they
34:45
can
34:47
fine
34:47
tune
34:47
it,
34:48
adapt
34:48
it
34:48
so
34:49
that
34:49
it
34:50
creates
34:51
content
34:52
specific
34:53
for
34:53
a
34:54
brand
34:54
for
34:55
a
34:55
product.
34:57
So
34:57
they're
34:57
not
34:57
just
34:58
say
34:59
messing
34:59
around
35:00
with
35:00
the
35:01
actual
35:01
products,
35:02
they
35:02
place
35:03
the
35:03
actual
35:03
products
35:04
in
35:04
different
35:04
contexts,
35:05
in
35:05
different
35:05
scenarios
35:06
with
35:07
proper
35:07
lightning
35:08
and
35:08
shadows
35:09
maintaining
35:10
the
35:10
proportions.
35:11
So
35:12
it's
35:12
really
35:12
like
35:13
having
35:13
a
35:13
professional
35:14
studio
35:15
at
35:15
your
35:15
fingertips,
35:16
just
35:17
more
35:17
scalable
35:17
and
35:18
faster.
35:20
Danielle,
35:21
for
35:21
an
35:21
example
35:22
with
35:22
this
35:22
might
35:22
be
35:23
product
35:23
images,
35:24
might
35:24
be
35:25
different
35:26
ads
35:26
that
35:26
you're
35:27
creating
35:27
for
35:27
retail.
35:28
Retail
35:28
media,
35:28
is
35:28
there
35:28
any
35:29
other
35:29
example
35:29
of
35:30
this
35:30
that
35:30
you
35:30
could
35:30
provide?
35:33
Yeah,
35:33
I
35:33
mean
35:33
oriented
35:34
media
35:35
is,
35:35
is
35:35
definitely
35:36
one
35:36
of
35:36
the,
35:37
one
35:37
of
35:37
the
35:37
use
35:37
cases,
35:39
social
35:39
media
35:40
campaigns
35:40
and
35:41
any
35:41
kind
35:41
of
35:42
communication
35:43
or
35:44
customer
35:44
engagement
35:45
that
35:46
brands
35:46
are
35:46
doing.
35:48
But
35:48
also
35:50
the,
35:50
the
35:51
products,
35:51
the
35:52
product
35:52
detail
35:52
pages.
35:53
Right.
35:53
So
35:54
that's
35:55
something
35:55
where
35:56
it's
35:56
often
35:56
the
35:57
case
35:57
where
35:57
you
35:57
see
35:58
products
35:58
in
35:59
a
35:59
lifestyle
36:00
scenario
36:01
so
36:01
it
36:01
can
36:01
really
36:02
relate
36:02
with
36:03
users
36:04
on
36:04
a
36:04
more
36:04
personal
36:05
level.
36:07
Danielle,
36:08
let's
36:08
get
36:08
you
36:08
out
36:08
of
36:08
here
36:08
on
36:08
this.
36:10
What
36:10
are
36:10
the
36:10
long
36:10
term
36:11
implications
36:11
of
36:12
AI
36:13
image
36:13
generation
36:14
when
36:15
you
36:15
think
36:15
about
36:15
it
36:15
broadly
36:15
across
36:16
the
36:16
industry,
36:16
for
36:17
the
36:17
retail
36:17
executives
36:18
that
36:18
are
36:18
listening,
36:19
what
36:19
do
36:20
they
36:20
need
36:20
to
36:20
know
36:20
in
36:20
terms
36:20
of
36:21
why
36:21
this
36:21
is
36:21
an
36:21
important
36:21
topic
36:22
and
36:22
how
36:22
things
36:22
are
36:22
going
36:23
to
36:23
change
36:23
in
36:23
this
36:23
direction?
36:24
Content
36:25
creation,
36:25
content
36:26
generation
36:27
is
36:28
time
36:28
consuming,
36:29
it's
36:29
expensive
36:30
when
36:30
you
36:30
need
36:31
to
36:31
do
36:31
it
36:31
at
36:31
scale
36:32
for
36:32
thousands
36:33
of
36:33
products
36:34
and
36:35
possibly
36:36
even
36:36
multiple
36:36
times
36:37
a
36:37
year
36:37
when
36:37
you
36:37
have
36:38
different
36:38
collections,
36:40
different
36:40
seasons.
36:42
Here
36:42
we
36:43
are
36:43
talking
36:43
about
36:44
reducing
36:45
dramatically
36:46
the
36:46
cost
36:46
of
36:47
creating
36:47
this
36:47
type
36:48
of
36:48
content,
36:49
achieving
36:51
faster
36:51
time
36:51
to
36:52
market
36:53
and
36:53
the
36:54
ability
36:54
to
36:54
create
36:55
personalized
36:56
content
36:57
at
36:57
scale,
36:58
all
36:59
while
36:59
maintaining
37:00
that
37:00
brand
37:01
consistency.
37:02
Imagine
37:03
being
37:03
able
37:03
to
37:03
create
37:04
thousands
37:05
of
37:05
product
37:06
images
37:06
for
37:07
an
37:07
e
37:07
commerce
37:08
store
37:08
in
37:09
minutes
37:09
instead
37:09
of
37:10
weeks,
37:11
or
37:11
being
37:11
able
37:12
to
37:12
run
37:13
localized
37:14
social
37:14
media
37:15
campaigns
37:17
across
37:17
different
37:17
markets
37:19
without
37:19
incurring
37:20
into
37:21
huge
37:21
production
37:22
cost.
37:24
So
37:24
I
37:24
think
37:25
what
37:25
Brea
37:25
is
37:25
doing
37:26
here
37:26
is
37:26
really
37:27
addressing
37:28
a
37:28
key
37:28
challenge
37:29
in
37:30
the
37:30
industry.
37:30
It's
37:31
not
37:31
just
37:31
a
37:31
cool
37:33
technology
37:33
that
37:34
they
37:34
have
37:34
built.
37:36
It's
37:36
a
37:36
practical
37:37
solution
37:37
that
37:38
can
37:38
easily
37:39
be
37:39
integrated
37:39
into
37:40
existing
37:41
system,
37:42
again
37:42
which
37:43
is
37:43
crucial
37:43
for
37:44
large
37:44
scale
37:45
adoption
37:46
and
37:47
the
37:47
focus
37:47
on
37:49
commercial
37:49
value.
37:50
Brand
37:51
integrity
37:52
is
37:52
something
37:52
that
37:53
is
37:53
key
37:53
for
37:54
enterprises
37:55
and
37:55
for
37:55
that
37:56
commercial
37:57
use.
37:57
So
37:57
I
37:57
think
37:58
Bria
37:58
is
37:59
really
37:59
one
38:00
of
38:01
those
38:01
startups
38:02
that
38:02
is
38:02
worth
38:03
keeping
38:03
an
38:03
eye
38:03
on
38:04
in
38:04
this
38:04
retail
38:05
tech
38:05
space.
38:07
Well,
38:07
you
38:07
heard
38:08
it
38:08
here
38:08
first
38:08
folks.
38:08
Bria
38:09
AI
38:09
put
38:10
it
38:10
on
38:10
your
38:10
radar
38:10
screen.
38:11
Thanks,
38:11
Danielle.
38:12
Thank
38:12
you.
38:16
Okay,
38:16
headline
38:17
number
38:17
four
38:17
Supermarkets
38:18
appear
38:18
to
38:18
be
38:18
losing
38:19
ground
38:19
with
38:19
younger
38:20
shoppers,
38:20
according
38:21
to
38:21
Grocery
38:21
Dive.
38:22
Traditional
38:23
supermarkets
38:23
are
38:23
falling
38:24
out
38:24
of
38:24
favor
38:24
with
38:25
younger
38:25
generations,
38:26
with
38:26
people
38:27
in
38:27
those
38:27
cohorts
38:28
increasingly
38:28
turning
38:29
to
38:29
discount
38:29
retailers
38:30
to
38:30
buy
38:30
groceries,
38:31
according
38:31
to
38:31
survey
38:32
data
38:32
published
38:33
Tuesday
38:33
by
38:33
the
38:33
feedback
38:34
group
38:35
Gen
38:35
Zers.
38:35
Millennials
38:36
and
38:36
Gen
38:36
Xers.
38:37
Yes,
38:37
shout
38:38
out
38:38
to
38:38
all
38:38
those
38:38
Gen
38:38
Xers
38:39
out
38:39
there
38:40
are
38:40
most
38:40
partial
38:40
to
38:40
Walmart,
38:41
with
38:41
more
38:41
than
38:42
a
38:42
fifth
38:42
of
38:43
people
38:43
in
38:43
each
38:43
of
38:44
those
38:44
groups
38:44
who
38:44
participated
38:45
participated
38:46
in
38:46
a
38:46
poll
38:47
the
38:47
research
38:48
firm
38:48
fielded
38:48
this
38:49
spring,
38:49
saying
38:49
they
38:49
most
38:50
recently
38:50
shopped
38:51
for
38:51
food
38:51
at
38:51
the
38:52
mass
38:52
retailer.
38:53
Those
38:53
generations
38:54
also
38:54
showed
38:54
a
38:54
preference
38:55
for
38:55
Aldi,
38:56
with
38:56
Gen
38:56
Z'
38:57
ers
38:57
especially
38:58
likely
38:58
to
38:58
have
38:58
made
38:58
their
38:59
latest
38:59
grocery
38:59
shopping
39:00
trip
39:00
at
39:01
that
39:01
chain.
39:02
22%
39:03
of
39:03
shoppers
39:03
in
39:03
that
39:04
group
39:04
shop
39:04
for
39:04
groceries,
39:05
most
39:05
recently
39:05
at
39:06
Aldi,
39:06
the
39:07
same
39:07
proportion
39:07
that
39:08
did
39:08
so
39:08
at
39:08
Walmart.
39:09
While
39:10
supermarkets
39:10
might
39:10
be
39:11
losing
39:11
ground
39:11
with
39:11
younger
39:12
shoppers,
39:12
they
39:12
remain
39:13
popular
39:13
with
39:14
older
39:14
consumers,
39:15
the
39:15
survey
39:16
found.
39:16
I
39:16
love
39:16
how
39:16
the
39:16
the
39:17
survey
39:17
said
39:17
older
39:18
consumers,
39:19
28%
39:20
of
39:20
baby
39:20
boomers
39:21
and
39:21
31%
39:22
of
39:22
people
39:23
in
39:23
the
39:23
silent
39:24
generation.
39:24
We
39:24
got
39:24
to
39:25
come
39:25
up
39:25
with
39:25
a
39:25
better
39:25
name
39:25
for
39:26
that
39:26
generation
39:26
than
39:26
the
39:27
silent
39:27
generation.
39:28
Well,
39:28
they
39:28
said
39:29
they
39:29
shop
39:29
for
39:29
groceries
39:30
most
39:30
recently
39:30
at
39:31
a
39:31
supermarket
39:31
ahead
39:32
of
39:32
other
39:32
formats.
39:33
Walmart
39:33
came
39:33
in
39:34
at
39:34
number
39:34
two
39:34
among
39:35
members
39:35
of
39:35
both
39:35
baby
39:36
boomers
39:36
and
39:36
the
39:37
silent
39:37
generation,
39:37
well
39:38
ahead
39:38
of
39:38
Aldi.
39:39
Chad,
39:40
what
39:40
advice
39:40
would
39:40
you
39:41
have
39:41
for
39:41
regional
39:41
grocers
39:42
as
39:42
they
39:42
appear
39:42
to
39:42
be
39:43
losing
39:43
share
39:43
with
39:43
the
39:44
younger
39:44
generations
39:45
but
39:45
still
39:45
attracting
39:46
boomers
39:46
and
39:47
the
39:47
silent
39:47
generation?
39:49
I'm
39:49
not
39:49
sure
39:49
first
39:50
of
39:50
all,
39:50
where
39:50
I
39:50
fall
39:51
into
39:51
all
39:51
of
39:51
this
39:51
I
39:53
generation.
39:53
Wait,
39:54
what,
39:54
what
39:54
are
39:54
we
39:55
calling
39:55
me
39:55
again?
39:55
I
39:56
don't
39:56
know.
39:59
You
39:59
know,
39:59
I,
39:59
I
39:59
love
40:00
when
40:01
predictive
40:03
data
40:03
starts
40:04
to
40:04
actually
40:04
play
40:05
out
40:05
in
40:05
the,
40:05
in
40:06
the
40:06
market.
40:06
And
40:06
what
40:07
I
40:07
mean
40:07
by
40:07
that
40:08
is
40:08
we,
40:08
we
40:08
can
40:09
go
40:09
back
40:09
Shameless
40:10
plug,
40:10
but
40:10
we
40:10
can
40:10
go
40:11
back
40:11
to
40:11
some
40:11
of
40:11
the
40:11
learnings
40:12
of
40:13
within
40:13
our
40:13
A
40:14
and
40:14
M
40:14
consumer
40:14
and
40:14
retail
40:15
group.
40:15
We
40:15
do
40:15
a
40:15
semi
40:16
annual
40:16
consumer
40:17
sentiment
40:17
survey
40:19
and
40:19
we
40:19
look
40:19
at
40:20
these
40:20
sort
40:20
of
40:20
buying
40:20
trends
40:21
and
40:21
look
40:21
at
40:22
all
40:22
kinds
40:23
of
40:23
different
40:24
spreads
40:24
and
40:24
segments
40:25
of
40:25
the
40:25
population,
40:26
household
40:26
income
40:27
and,
40:27
and
40:27
there's
40:27
a
40:28
lot
40:28
of
40:28
generational
40:28
preferences
40:29
that,
40:30
that
40:30
have
40:30
popped
40:31
when
40:31
it,
40:31
when
40:31
it
40:31
came
40:31
to
40:32
grocery
40:32
over
40:32
our
40:32
past
40:33
couple
40:33
of
40:33
surveys.
40:34
So
40:35
you
40:35
know,
40:35
on
40:35
the
40:35
whole,
40:36
younger
40:36
grocery
40:37
consumers
40:38
are
40:38
more
40:38
price
40:39
sensitive
40:40
and
40:40
they're
40:40
more
40:41
likely
40:41
to
40:41
look
40:41
and
40:42
try
40:42
out
40:42
different
40:43
products
40:43
and
40:43
assortments.
40:45
They
40:45
have
40:45
a
40:45
particularly
40:46
high
40:46
confidence
40:47
in
40:47
private
40:47
label.
40:48
They're
40:49
interested
40:49
in
40:49
quality
40:50
of
40:50
goods,
40:50
but
40:51
they're
40:51
the
40:51
ones
40:52
who
40:52
disproportionately
40:53
see
40:54
a
40:54
quality
40:55
boost
40:55
in
40:56
store
40:56
brands.
40:57
So
40:57
that
40:57
trade
40:58
off
40:58
for
40:58
the
40:58
better
40:58
price
40:59
isn't
40:59
as
40:59
significant
41:00
to
41:00
them
41:00
because
41:01
they
41:01
feel
41:01
like
41:01
they're
41:01
getting
41:02
quality.
41:03
And
41:03
about
41:04
half
41:04
say
41:04
they're
41:05
likely
41:05
or
41:06
very
41:06
likely
41:06
to
41:07
try
41:07
new
41:07
brands
41:08
that
41:08
they
41:08
see
41:09
especially
41:09
when
41:09
they
41:10
provide
41:10
better
41:10
for
41:10
you
41:11
health
41:11
benefits.
41:12
That's
41:12
the
41:13
playbook,
41:13
right?
41:14
And
41:14
like
41:14
these
41:15
are
41:15
the
41:15
areas
41:15
that
41:16
Walmart
41:16
and
41:16
Aldi
41:17
are
41:17
winning
41:17
at,
41:18
right?
41:18
Discount
41:19
prices,
41:19
high
41:20
private
41:20
label
41:20
penetration
41:21
with
41:21
good
41:22
quality
41:23
that
41:23
they
41:23
invest
41:23
in
41:25
healthy
41:25
assortment
41:26
options.
41:27
And
41:28
this
41:28
is
41:28
where
41:28
we
41:29
can
41:29
see
41:29
that,
41:29
you
41:29
know,
41:30
many
41:30
regional
41:30
grocers
41:31
are
41:31
falling
41:31
behind.
41:32
So
41:32
look
41:32
no
41:33
further
41:33
to
41:33
the
41:33
data
41:34
and
41:34
preference
41:34
and
41:35
purchase
41:35
drivers
41:36
of
41:36
these
41:36
generations
41:37
and
41:37
the
41:37
playbook
41:38
is
41:38
laid
41:39
out
41:39
in
41:39
front
41:39
of
41:39
you.
41:40
Yeah,
41:41
Chad,
41:41
I'll
41:41
give
41:41
you
41:42
another
41:42
plug
41:42
because
41:42
in
41:42
addition
41:43
to
41:43
your
41:43
consumer
41:43
sentiment
41:44
survey,
41:44
you
41:44
guys
41:44
also
41:44
released
41:45
a
41:45
report
41:45
on
41:46
space
41:46
planning
41:47
which
41:47
I
41:47
got
41:47
thinking
41:48
about
41:48
in
41:48
regards
41:49
to
41:49
this
41:49
conversation
41:50
too.
41:50
And
41:50
so,
41:51
you
41:51
know,
41:51
to
41:51
answer
41:51
the
41:51
question
41:52
from
41:52
that
41:52
perspective
41:53
in
41:53
terms
41:53
of
41:53
the
41:53
advice
41:54
that,
41:54
you
41:54
know,
41:54
I
41:54
personally
41:55
would
41:55
give
41:55
to
41:55
the
41:55
regional
41:56
grocers
41:56
would
41:56
be,
41:57
and
41:57
I
41:57
got
41:57
it
41:57
from,
41:58
you
41:58
know,
41:58
talking
41:58
to
41:58
your
41:58
team
41:59
about
41:59
that
41:59
report
41:59
is
42:00
you
42:00
gotta
42:01
map
42:01
out
42:01
your
42:01
current
42:01
strengths
42:02
and
42:02
weaknesses
42:05
as
42:05
a
42:05
grocer
42:06
and
42:06
you
42:06
gotta
42:06
do
42:06
it
42:07
by
42:07
category.
42:08
And
42:08
then
42:08
you
42:08
have
42:08
to
42:08
ask
42:08
yourself
42:09
the
42:09
hard
42:09
question
42:09
of
42:10
how
42:10
are
42:10
those
42:10
categories
42:11
gonna
42:11
be
42:11
trending
42:12
five
42:12
to
42:12
10
42:12
years
42:12
out
42:13
and
42:13
placing
42:13
bets
42:14
again
42:14
on
42:14
which
42:14
trends
42:15
you
42:15
think
42:15
are
42:15
gonna
42:16
be
42:16
most
42:16
impactful
42:17
against
42:17
your
42:17
overall
42:18
value
42:18
proposition.
42:18
You
42:18
know,
42:18
is
42:19
it
42:19
gonna
42:19
be
42:19
E
42:19
commerce,
42:19
Is
42:20
it
42:20
gonna
42:20
be
42:20
fresh
42:20
food,
42:20
Is
42:21
it
42:21
gonna
42:21
be
42:22
food
42:22
is
42:22
medicine
42:22
as
42:23
the
42:23
trend?
42:23
And
42:23
you
42:23
need
42:24
to
42:24
get
42:24
to
42:24
work.
42:24
You
42:25
need
42:25
to
42:25
get
42:25
to
42:25
work
42:25
designing
42:26
your
42:26
in
42:26
store
42:26
experience
42:27
and
42:27
your
42:28
digital
42:28
experience,
42:29
not
42:29
just
42:29
for
42:30
today
42:30
because
42:30
I
42:30
feel
42:30
like
42:30
a
42:30
lot
42:31
of
42:31
people
42:31
are
42:31
just
42:31
designing
42:32
both
42:32
those
42:32
experiences
42:33
for
42:33
today.
42:33
You
42:34
gotta
42:34
be
42:34
designing
42:35
it
42:35
five
42:35
to
42:35
10
42:35
years
42:36
out.
42:36
That's
42:36
what
42:36
I
42:37
think.
42:37
And
42:37
that's
42:37
why
42:37
Walmart's
42:38
killing
42:38
it
42:38
on
42:38
both
42:38
ends.
42:39
They're
42:39
killing
42:39
it
42:39
with
42:39
the
42:39
younger
42:40
shoppers
42:40
and
42:40
the
42:40
high
42:41
income
42:41
demo,
42:41
which
42:42
is
42:42
why
42:42
they're
42:42
so
42:43
strong
42:43
right
42:43
now.
42:43
But
42:43
I
42:44
don't
42:44
know,
42:44
David,
42:44
anything
42:45
you'd
42:45
add
42:45
here?
42:46
Yeah,
42:47
the
42:47
only
42:47
thing
42:47
I'd
42:48
add
42:48
is,
42:48
I
42:48
think
42:48
where
42:48
you
42:49
were
42:49
going,
42:49
Chris,
42:49
is
42:49
that
42:51
I
42:51
actually
42:51
think
42:51
that
42:52
they're
42:52
just
42:52
a
42:52
better
42:53
experience.
42:54
Right.
42:54
Like
42:54
if
42:55
I
42:55
would,
42:55
I
42:56
just
42:56
think
42:56
about
42:56
like
42:57
the,
42:57
gotta
42:57
amplify
42:58
that.
42:58
The
42:58
three
42:59
or
42:59
four
42:59
options
43:00
that
43:00
I
43:00
have
43:00
here
43:00
in
43:01
my
43:01
little
43:01
hometown
43:02
of
43:02
Truckee,
43:03
California.
43:04
You
43:04
know,
43:04
we
43:04
have
43:04
a
43:04
Raley's
43:05
One
43:05
Market,
43:05
which
43:06
was
43:06
the
43:06
first
43:06
Raley's
43:07
One
43:07
Market,
43:07
which
43:08
is
43:08
an
43:08
amazing
43:09
experience.
43:10
We
43:10
have
43:10
a
43:10
brand
43:10
new
43:11
grocery
43:11
outlet
43:11
which
43:12
is
43:13
a
43:13
way
43:14
better
43:14
experience
43:14
than
43:15
the
43:15
Safeway
43:15
that
43:15
is
43:16
right
43:16
across
43:16
the
43:17
street.
43:17
And
43:17
it's
43:17
better
43:18
prices,
43:19
et
43:20
cetera.
43:20
So
43:20
you
43:20
know,
43:21
why
43:21
wouldn't
43:21
I
43:22
go
43:22
shopping
43:23
someplace
43:23
that
43:23
has
43:23
a
43:23
better
43:23
experience
43:24
and
43:24
lower
43:24
prices?
43:25
I
43:25
mean
43:25
it's,
43:26
it,
43:27
it,
43:28
as
43:28
Chad
43:28
said,
43:28
it's
43:29
simple
43:29
data
43:30
and
43:30
the
43:30
data's
43:31
playing
43:31
out.
43:32
Yeah.
43:32
And
43:33
all
43:33
the
43:33
data
43:33
we're
43:33
seeing
43:33
is
43:34
converging
43:34
to
43:35
this,
43:35
this
43:35
answer,
43:36
this,
43:36
you
43:36
know,
43:36
eventual
43:37
thing.
43:37
Like
43:37
we
43:37
saw
43:37
a
43:38
report
43:38
yesterday
43:38
on
43:39
just
43:39
E
43:39
commerce
43:39
and
43:40
who's
43:40
gaining
43:40
the
43:40
share
43:40
in
43:41
E
43:41
commerce
43:41
that
43:41
Mercados
43:42
put
43:42
out
43:42
and
43:42
it
43:42
was
43:42
saying
43:43
the
43:43
same
43:43
thing,
43:43
the
43:44
same
43:44
people
43:44
are
43:44
winning.
43:44
Walmart,
43:45
Aldi
43:46
got
43:46
highlighted
43:46
in
43:46
that
43:46
too.
43:47
And
43:47
close
43:47
us
43:48
out
43:48
here,
43:48
what
43:48
are
43:48
your
43:48
thoughts?
43:49
I
43:49
think
43:49
price
43:50
is
43:50
the
43:50
biggest
43:51
concern.
43:51
Like
43:51
I
43:52
think
43:52
you
43:52
have
43:52
to
43:52
be
43:53
making
43:53
sure
43:53
that
43:53
you're
43:54
investing
43:54
to
43:55
make
43:55
sure
43:55
that
43:55
your
43:55
pricing
43:56
is
43:56
competitive
43:57
in
43:57
those
43:58
areas.
43:58
And
43:59
the
43:59
second
43:59
thing
43:59
I
43:59
would
43:59
say
44:00
is
44:00
content
44:00
creation.
44:01
Like
44:01
I
44:02
think
44:02
that
44:02
even
44:02
though
44:02
you're
44:03
a
44:03
regional
44:03
grocer,
44:04
I
44:04
think
44:04
it's
44:04
important
44:04
to
44:05
be
44:05
thinking
44:05
about
44:06
how
44:06
you're
44:06
finding
44:07
those
44:07
news,
44:07
new
44:08
consumers
44:08
and
44:08
connecting
44:09
with
44:09
them.
44:09
And
44:10
I
44:10
think
44:10
of
44:10
you
44:11
know,
44:12
creating
44:12
video
44:13
or
44:13
creating
44:14
other,
44:14
like
44:15
other
44:15
types
44:16
of
44:16
engaging
44:16
content
44:17
that
44:17
will
44:17
show
44:18
up
44:18
in
44:18
some
44:18
of
44:18
the
44:18
places
44:19
where
44:19
Gen
44:19
Z
44:20
is
44:20
too.
44:20
Because
44:20
they
44:21
don't
44:21
know
44:21
about
44:21
you.
44:21
Like
44:22
unless
44:22
you
44:22
know
44:22
Walmart,
44:23
Target,
44:24
Amazon.
44:25
Like
44:25
these
44:25
people
44:26
are
44:26
investing
44:27
in
44:27
creating
44:28
content,
44:28
capturing
44:29
interest,
44:30
sending
44:31
out
44:31
recipes,
44:31
being,
44:32
saying
44:33
we
44:33
have
44:33
the
44:34
trending
44:34
product
44:35
that
44:35
you're
44:35
talking
44:35
about
44:35
on
44:36
Tik
44:36
Tok.
44:36
Like
44:36
they're
44:37
investing
44:37
in
44:37
those
44:38
areas
44:38
and
44:38
there
44:38
are
44:38
partners
44:39
that
44:39
I
44:39
think
44:39
these
44:40
regional
44:40
grocers
44:40
can
44:41
find
44:41
to
44:41
help
44:41
do
44:42
that
44:43
so
44:43
that
44:43
they
44:43
remain
44:44
relevant.
44:44
Because
44:44
like
44:45
you
44:45
said,
44:45
you
44:45
know,
44:45
then
44:45
the
44:46
research
44:46
showed
44:46
they're,
44:47
they're,
44:47
they're
44:47
having
44:48
this
44:48
consistent
44:49
audience
44:49
across,
44:49
you
44:50
know,
44:50
boomers
44:50
and
44:51
even
44:51
some
44:52
older
44:52
Gen
44:52
Xers,
44:53
but
44:53
that's
44:53
going
44:54
to
44:54
go
44:54
by
44:54
the
44:54
wayside.
44:55
So
44:55
I'd
44:55
be
44:55
invested
44:56
in
44:56
how
44:56
am
44:57
I
44:57
creating
44:57
content
44:57
so
44:58
that
44:58
I
44:58
show
44:58
up
44:58
for
44:59
these
44:59
audiences
45:00
that
45:00
are
45:00
coming
45:00
into
45:01
the
45:01
market
45:01
in
45:02
the
45:02
places
45:02
that
45:02
they're
45:03
spending
45:03
the
45:03
most
45:03
time.
45:04
That's
45:04
a
45:04
great
45:05
point.
45:05
It
45:05
calls
45:05
to
45:05
mind
45:06
what
45:06
was
45:06
it,
45:07
was
45:07
it
45:07
stop
45:07
and
45:08
shop
45:08
that
45:08
was
45:08
doing
45:08
the
45:09
kiosks
45:09
for
45:09
the
45:09
mobile
45:10
couponing
45:10
in
45:10
store,
45:11
you
45:11
know,
45:11
and
45:11
like,
45:12
who's
45:12
your
45:12
muse
45:13
as
45:13
you're
45:13
designing
45:13
this?
45:13
Is
45:14
it
45:14
the
45:14
silent
45:14
generation
45:15
that's
45:15
probably
45:15
likely
45:15
to
45:16
use
45:16
that
45:16
kiosk?
45:16
Or
45:17
is
45:17
or
45:17
are
45:17
you,
45:17
you
45:18
know,
45:18
putting
45:18
your
45:18
resources
45:19
towards
45:19
what
45:19
you're
45:20
going
45:20
to
45:20
be
45:20
in
45:20
the
45:20
future
45:21
and
45:21
what
45:21
you
45:21
want
45:21
to
45:21
be?
45:22
That's
45:22
a
45:22
great
45:22
point,
45:22
Anne.
45:23
All
45:23
right,
45:23
let's
45:23
go
45:23
to
45:23
headline
45:24
number
45:24
five.
45:24
Shopify
45:25
is
45:25
setting
45:26
boundaries
45:26
for
45:26
AI
45:27
agents
45:27
on
45:27
its
45:27
merchant
45:28
sites.
45:28
According
45:28
to
45:29
modern
45:29
retail,
45:29
Shopify
45:30
is
45:30
drawing
45:30
a
45:30
line
45:30
in
45:31
the
45:31
sand
45:31
on
45:31
agentic
45:32
AI,
45:32
the
45:33
type
45:33
of
45:33
bots
45:33
that
45:34
autonomously
45:34
complete
45:35
tasks
45:35
on
45:36
their
45:36
own
45:36
without
45:36
human
45:37
input.
45:38
With
45:38
new
45:38
language
45:39
across
45:39
merchant
45:40
websites
45:40
that
45:40
appears
45:41
aimed
45:41
at
45:41
blocking
45:42
agentic
45:42
AI
45:43
systems,
45:43
Shopify
45:44
now
45:45
includes
45:45
a
45:45
warning
45:46
in
45:46
their
45:46
code
45:47
that
45:47
powers
45:47
merchant
45:48
storefronts,
45:48
telling
45:48
bots
45:49
what
45:49
they
45:49
can
45:49
and
45:50
can't
45:50
do.
45:51
The
45:51
message
45:51
appears
45:51
in
45:52
each
45:52
site's
45:52
robots
45:53
txt
45:54
file,
45:55
a
45:55
standard
45:55
tool
45:55
websites
45:56
use
45:56
to
45:56
give
45:56
instructions
45:57
to
45:57
automated
45:57
crawlers
45:58
like
45:58
search
45:58
engines.
45:59
The
46:00
new
46:00
line
46:00
states,
46:01
quote,
46:01
automated
46:02
scraping
46:03
buy
46:03
for
46:03
me
46:03
agents
46:04
or
46:04
any
46:05
end
46:05
to
46:05
end
46:06
function
46:06
flow
46:06
that
46:06
completes
46:07
payment
46:07
without
46:08
a
46:08
final
46:08
review
46:09
step
46:09
is
46:10
not
46:10
permitted.
46:10
End
46:11
quote.
46:11
The
46:11
move,
46:12
however,
46:12
is
46:12
not
46:12
likely
46:13
an
46:13
outright
46:13
rejection
46:14
of
46:14
agentic
46:14
AI.
46:15
The
46:15
language
46:16
direct.
46:16
The
46:17
added
46:17
language
46:17
directs
46:18
legitimate
46:18
integrators
46:19
to
46:20
use
46:20
its
46:20
official
46:20
checkout
46:21
kit.
46:22
In
46:22
other
46:22
words,
46:22
the
46:22
change
46:23
shows
46:23
Shopify
46:23
is
46:24
thinking
46:24
ahead,
46:24
drawing
46:25
early
46:25
boundaries
46:26
between
46:26
controlled
46:26
integration
46:27
and
46:27
unregulated
46:28
automation.
46:29
Shopify
46:29
merchants
46:30
could
46:30
theoretically
46:31
override
46:31
the
46:32
robot
46:33
file
46:34
as
46:34
Shopify
46:35
is
46:35
a
46:35
content
46:36
management
46:36
system.
46:37
In
46:37
other
46:37
words,
46:38
the
46:38
change
46:38
shows
46:38
Shopify
46:39
is
46:39
thinking
46:39
ahead,
46:40
drawing
46:40
early
46:40
boundaries
46:41
between
46:41
controlled
46:41
integration
46:42
and
46:42
unregulated
46:43
automation.
46:44
But
46:44
the
46:44
default
46:45
settings
46:45
suggest
46:46
the
46:46
platform
46:46
is
46:46
trying
46:47
to
46:47
protect
46:47
its
46:47
ecosystem
46:48
by
46:48
discouraging
46:50
unauthorized
46:51
AI
46:51
scraping
46:51
and
46:52
checkout
46:52
information.
46:53
David,
46:54
we're
46:55
going
46:55
to
46:55
ask
46:55
you
46:56
a
46:56
more
46:56
top
46:56
level
46:57
question
46:57
here.
46:57
I
46:57
won't
46:58
ask
46:58
you
46:58
about
46:58
robots
46:59
txt
46:59
files,
47:00
but
47:00
our
47:00
retail
47:01
boardrooms
47:02
giving
47:02
enough
47:03
attention
47:03
to
47:03
agentic
47:04
AI.
47:04
Or
47:04
is
47:04
Shopify
47:05
ahead
47:05
of
47:05
the
47:06
curve
47:06
and
47:06
trying
47:06
to
47:06
curve
47:07
AI
47:07
bot
47:08
activity
47:08
on
47:09
its
47:09
properties?
47:11
So
47:11
a
47:12
couple
47:12
things
47:12
here
47:12
and
47:13
one,
47:13
I
47:13
think
47:14
this
47:14
is
47:14
the
47:14
best
47:14
news
47:14
I
47:15
have
47:15
heard
47:15
this
47:16
year
47:16
from
47:16
a
47:16
shop.
47:17
Yeah,
47:18
yeah,
47:19
I'll
47:19
tell
47:20
you
47:20
why,
47:20
like
47:22
if
47:23
you,
47:24
you
47:24
know,
47:24
try
47:25
to
47:26
book
47:26
a
47:26
reservation
47:27
in
47:27
New
47:28
York
47:28
City
47:28
for
47:29
any
47:29
restaurant
47:29
that's
47:30
worth
47:30
going.
47:31
If
47:31
you,
47:32
you
47:32
want
47:32
the
47:33
latest
47:33
collab
47:33
with,
47:34
you
47:34
know,
47:35
Adidas
47:35
and
47:35
Bonner,
47:36
or,
47:36
you
47:36
know,
47:36
pick
47:36
any
47:37
collabs
47:37
that
47:37
are
47:37
out
47:38
when
47:38
they
47:38
drop.
47:39
You
47:39
want
47:39
to
47:39
try
47:39
to
47:40
buy
47:40
concert
47:40
tickets
47:41
on
47:41
the
47:41
day
47:42
of
47:42
release,
47:42
you
47:43
can't
47:43
do
47:43
any
47:44
of
47:44
that
47:44
anymore.
47:45
As
47:45
a
47:45
person
47:46
that
47:46
is
47:46
sitting
47:46
in
47:46
front
47:47
of
47:47
a
47:47
computer
47:48
and
47:48
waiting
47:49
for
47:49
10am
47:50
and
47:50
then
47:50
clicking.
47:51
Right.
47:51
It
47:51
just
47:51
doesn't
47:51
happen.
47:52
Right.
47:52
Because
47:52
all
47:52
of
47:53
the
47:53
bots
47:53
have
47:53
completely
47:54
taken
47:54
over.
47:55
So
47:55
I
47:55
actually
47:56
think
47:56
this
47:56
brings
47:57
some
47:57
validity
47:58
back
47:58
to
47:58
the
47:59
online
47:59
shopping
48:00
experience
48:01
and
48:01
allows
48:02
humans
48:03
to
48:03
participate,
48:04
which
48:05
I
48:05
think
48:05
is,
48:05
which
48:06
is
48:06
a
48:06
great
48:06
thing.
48:08
To
48:08
your
48:08
broader
48:09
question.
48:10
I
48:10
think
48:11
boardrooms
48:11
are
48:12
starting
48:12
to
48:13
pay
48:13
attention
48:14
to
48:14
agentic
48:15
AI
48:16
in
48:16
a
48:17
lot
48:17
of
48:17
different
48:17
ways.
48:18
Right.
48:18
I
48:19
think
48:20
it's
48:21
very
48:21
analogous
48:22
to
48:22
almost
48:22
the
48:23
outsourcing
48:23
journey.
48:25
We,
48:25
you
48:26
know,
48:26
there's
48:26
the
48:26
commodity
48:27
stuff
48:27
you
48:27
can
48:27
do
48:27
with,
48:28
with
48:28
agentic
48:29
AI
48:29
of
48:29
data
48:30
aggregation
48:30
and,
48:31
and
48:31
things
48:32
like
48:32
that
48:32
and,
48:32
you
48:33
know,
48:33
and
48:33
like
48:34
automating
48:34
certain
48:35
things
48:35
or
48:35
eliminating
48:36
certain
48:36
things.
48:37
I
48:37
think
48:37
it's
48:38
really
48:38
tip
48:38
of
48:39
spear
48:39
stuff.
48:39
And
48:40
very
48:40
few
48:40
people
48:41
are
48:41
doing
48:42
really
48:43
cool
48:44
pricing,
48:44
personalization,
48:47
merchandising
48:48
stuff
48:48
yet
48:49
because
48:49
they
48:51
a,
48:51
the
48:51
skill
48:52
set
48:52
is
48:53
outrageously
48:53
expensive
48:54
to
48:54
hire
48:55
right
48:55
now
48:55
because
48:56
there's
48:56
not
48:56
enough
48:56
of
48:57
it.
48:58
So
48:58
you're
48:58
only
48:59
seeing
48:59
kind
48:59
of
48:59
the
48:59
largest
49:00
players
49:01
primarily
49:02
in
49:02
the
49:02
tech
49:02
space
49:03
that
49:03
are
49:03
kind
49:03
of
49:04
really
49:04
pushing
49:04
the
49:04
envelope.
49:06
I
49:06
think
49:06
retailers
49:07
are
49:07
a
49:07
step
49:07
or
49:08
two
49:08
behind
49:08
the
49:09
curve,
49:10
but
49:12
I
49:12
think
49:12
they're
49:12
starting
49:13
to
49:13
realize
49:13
that
49:13
they
49:14
are
49:14
a
49:14
step
49:14
or
49:14
two
49:14
behind
49:15
the
49:15
curve.
49:16
And
49:16
the
49:17
next
49:17
couple
49:17
years
49:17
are
49:18
going
49:18
to
49:18
be
49:18
interesting
49:18
to
49:18
see
49:20
A,
49:20
the
49:20
talent
49:20
war
49:21
and
49:22
then
49:22
B,
49:22
how
49:22
that
49:22
talent
49:23
is
49:23
deployed
49:24
to,
49:24
to
49:24
help
49:25
retailers.
49:26
Right.
49:26
Well,
49:26
certainly
49:27
a
49:27
reason,
49:27
I
49:27
think,
49:28
like
49:28
you
49:28
said,
49:28
I
49:28
thought
49:28
this
49:29
was
49:29
the,
49:29
one
49:29
of
49:29
the
49:29
most
49:30
intriguing
49:30
stories
49:31
that
49:31
we
49:31
had
49:31
this
49:32
week
49:32
on
49:32
the
49:32
Fast
49:33
five,
49:33
but
49:33
certainly
49:34
something
49:34
that,
49:34
you
49:35
know,
49:35
is
49:35
going
49:35
to
49:35
push
49:36
hopefully
49:36
more
49:36
retailers
49:37
to
49:37
start
49:37
putting
49:38
more
49:38
focus
49:38
on
49:39
this
49:40
as
49:40
a
49:40
priority
49:41
for
49:41
them.
49:41
Chad,
49:42
where
49:42
do
49:42
you,
49:42
where
49:43
do
49:43
you
49:43
sit
49:43
on
49:43
this?
49:43
Are
49:44
you,
49:44
are
49:44
you
49:44
feeling
49:45
like
49:45
this
49:45
is
49:45
being
49:46
talked
49:47
about
49:47
enough
49:47
in
49:47
boardrooms
49:48
that
49:48
you're
49:49
sitting
49:49
in?
49:50
Well,
49:51
I
49:51
think
49:51
there's
49:51
probably
49:52
lots
49:52
of
49:52
talk
49:52
in
49:53
boardrooms
49:53
about
49:54
agentic
49:55
AI,
49:55
but
49:55
maybe
49:56
not
49:56
from
49:56
the,
49:58
I
49:59
don't
49:59
know,
49:59
kind
49:59
of
50:00
ethical
50:00
or
50:01
perspective
50:02
that
50:02
Shopify
50:03
is
50:03
coming
50:03
at
50:03
it.
50:03
Right.
50:04
So
50:04
it's
50:05
about
50:05
commerce
50:06
maximization
50:06
and
50:07
I
50:07
do
50:07
think
50:08
Shopify
50:08
is
50:08
ahead
50:09
of
50:09
the
50:09
curve
50:09
in
50:09
terms
50:09
of
50:10
thinking
50:10
about
50:10
that
50:11
activity.
50:11
Right.
50:12
I
50:12
mean,
50:12
this
50:12
raises
50:14
huge
50:14
questions
50:15
around
50:15
enforceability
50:16
and
50:17
legal
50:17
consent.
50:18
And
50:18
E
50:19
commerce.
50:19
And
50:20
personally
50:21
to
50:21
me
50:21
I'm
50:22
all
50:22
in
50:23
favor
50:23
for
50:23
slow
50:24
playing
50:24
AI
50:24
in
50:25
places
50:25
where
50:25
AI
50:26
decision
50:26
making
50:27
imposes
50:27
risk.
50:28
I
50:28
mean
50:29
I
50:29
love
50:29
the
50:29
idea
50:30
of
50:30
it.
50:30
Right.
50:30
I
50:30
mean
50:31
the
50:31
consequences
50:32
of
50:32
allowing
50:32
AI
50:33
free
50:33
reign
50:34
to
50:35
make
50:35
mistakes
50:35
or
50:37
whatever
50:38
the
50:38
ramifications,
50:39
like
50:39
it
50:39
can
50:39
cost
50:39
a
50:39
lot
50:40
of
50:40
money
50:40
at
50:40
the
50:40
very
50:41
least
50:41
piss
50:41
a
50:41
lot
50:41
of
50:42
people
50:42
off.
50:43
So
50:43
there
50:43
is
50:43
a
50:44
spectrum
50:44
in
50:45
terms
50:45
of,
50:45
in
50:45
its
50:46
development
50:46
how
50:46
AI
50:47
should
50:47
be
50:47
used
50:48
in
50:48
decision
50:48
making.
50:49
Right.
50:49
And
50:50
as
50:50
David
50:50
said,
50:51
you
50:51
know,
50:51
the
50:51
super
50:52
repetitive
50:52
lower
50:53
risk,
50:53
quite
50:53
frankly,
50:54
if
50:54
there's
50:54
little
50:54
for
50:55
the
50:55
human
50:55
to
50:55
add.
50:56
Yeah,
50:57
let
50:57
AI
50:57
run
50:58
wild.
50:58
Right.
50:58
But
50:58
in
50:59
these
50:59
cases
50:59
where
51:00
either
51:00
AI
51:01
can
51:01
err
51:02
or
51:02
it,
51:03
it
51:03
provides
51:03
an
51:03
imbalance
51:04
in
51:04
the
51:04
market
51:05
so
51:06
either
51:06
around
51:07
what
51:07
the
51:07
AI
51:08
will
51:08
do,
51:08
so
51:08
it's
51:09
a
51:09
risk
51:09
based
51:09
decision
51:10
or
51:11
you
51:11
know,
51:11
if
51:11
there's
51:11
something
51:11
that
51:12
a
51:12
human
51:12
can
51:12
add
51:13
to
51:13
the
51:13
decision
51:13
or
51:14
execution,
51:14
so
51:15
more
51:15
of
51:15
a
51:15
value
51:15
based
51:16
decision.
51:16
We,
51:16
we
51:17
need
51:17
the
51:17
human
51:17
intervention
51:18
at
51:18
least
51:18
until,
51:19
you
51:19
know,
51:19
we're
51:20
developed
51:20
at
51:20
that
51:20
point
51:20
and
51:21
Shopify
51:22
is
51:22
saying
51:22
that's
51:23
the
51:23
case
51:23
for
51:23
the
51:23
gentic
51:24
AI
51:24
and
51:24
frankly
51:25
I'm
51:25
not
51:25
going
51:25
to
51:26
push
51:26
back
51:26
on
51:26
that.
51:27
Yeah,
51:27
I
51:27
mean
51:27
I
51:28
think
51:28
it,
51:28
you
51:29
make
51:29
a
51:29
really
51:29
good
51:29
point,
51:30
Chad.
51:30
And
51:30
I
51:30
think
51:30
it,
51:30
it
51:31
just
51:31
re
51:31
emphasizes
51:32
how
51:32
important
51:32
this
51:33
is
51:33
because
51:33
I
51:34
think
51:34
we,
51:34
we
51:35
have
51:35
to
51:35
all
51:36
be
51:36
agile
51:37
and
51:37
ready
51:37
to
51:38
react
51:39
and
51:39
adapt
51:40
our
51:40
businesses
51:41
to,
51:42
you
51:42
know,
51:42
to
51:42
be,
51:43
you
51:43
know,
51:44
in
51:44
a
51:44
position
51:44
to
51:45
change
51:45
if
51:45
we
51:45
need
51:45
to
51:46
based
51:46
on
51:46
how
51:46
search
51:47
is
51:47
going
51:47
to
51:47
be
51:47
happening.
51:48
I
51:48
mean,
51:48
I
51:48
think
51:48
we
51:48
look
51:49
at
51:49
how
51:49
Amazon
51:50
was
51:50
doing
51:50
this.
51:51
You
51:51
know,
51:51
you,
51:51
you
51:51
could
51:52
shop
51:52
aloe
51:52
yoga
51:53
and
51:53
buy
51:53
a
51:53
bra
51:54
on
51:54
Amazon
51:54
even
51:55
though
51:55
they
51:55
weren't
51:56
in
51:56
the,
51:56
in
51:57
the
51:57
Amazon
51:57
marketplace.
51:58
I
51:58
think
51:59
it's
51:59
going
51:59
to
51:59
be
52:00
really
52:00
important
52:00
for
52:01
all
52:01
brands,
52:02
all
52:02
retailers
52:03
to
52:03
focus
52:03
on
52:04
how
52:04
this
52:04
is
52:04
going
52:04
to
52:04
continue
52:05
to
52:05
shift
52:05
and
52:05
then
52:06
how
52:06
search
52:06
behavior
52:06
is
52:07
going
52:07
to
52:07
shift
52:07
as
52:07
a
52:07
result.
52:08
But,
52:08
but
52:08
Chris
52:09
Walton,
52:09
close
52:09
us
52:10
out.
52:11
Oh
52:11
my
52:11
God.
52:11
Yeah,
52:11
I've
52:12
got
52:12
a
52:12
lot
52:12
of,
52:12
a
52:12
lot
52:13
of
52:13
thoughts
52:13
on
52:13
this
52:13
one.
52:13
I
52:14
mean
52:14
I
52:14
think,
52:14
you
52:14
know,
52:15
if
52:15
I
52:15
look
52:15
at,
52:16
from
52:16
the
52:16
executive
52:16
perspective,
52:17
the
52:17
first
52:17
question
52:17
I
52:18
ask
52:18
myself
52:18
is
52:19
why
52:19
do
52:19
we
52:19
allow
52:20
any
52:20
of
52:20
this?
52:20
You
52:21
know,
52:21
why
52:21
do
52:21
we
52:21
allow
52:22
bots
52:22
to
52:22
come
52:22
in
52:23
and
52:23
scrape
52:24
pricing?
52:24
Like
52:24
if
52:24
I'm
52:24
Walmart,
52:25
why
52:25
do
52:25
I
52:25
want
52:25
my
52:25
pricing
52:26
out
52:26
in,
52:26
in
52:27
the,
52:27
the,
52:27
in
52:27
the,
52:28
in
52:28
the
52:28
Internet
52:29
sphere?
52:29
Like
52:29
why
52:29
does
52:29
that,
52:30
why
52:30
do
52:30
we
52:30
allow
52:30
that
52:31
to
52:31
happen?
52:31
And
52:31
so
52:31
then
52:31
I
52:31
start
52:32
thinking
52:32
about
52:32
the
52:32
lobby
52:32
efforts
52:33
across
52:33
the
52:33
retail
52:33
industry
52:34
and
52:34
I'm
52:34
like,
52:34
like,
52:34
you
52:35
know,
52:35
we're
52:35
spending
52:35
all
52:35
this
52:35
time
52:35
lobbying
52:36
for
52:36
credit
52:36
card
52:37
processing
52:37
fees.
52:37
Why
52:37
aren't
52:38
we
52:38
lobbying
52:38
for
52:38
regulation
52:39
to,
52:39
you
52:40
know,
52:40
limit
52:40
bot
52:40
activity
52:41
or
52:41
to
52:41
control
52:42
bot
52:42
activity
52:42
in
52:42
some
52:43
way,
52:43
shape
52:43
or
52:43
form?
52:43
So
52:43
that's
52:44
one
52:44
question.
52:44
But
52:45
given
52:45
that
52:45
there's
52:46
an
52:46
absence
52:46
of
52:46
that,
52:46
then
52:47
the
52:47
bigger
52:47
question
52:47
for
52:47
me
52:48
is
52:48
how
52:49
does
52:49
what
52:49
we're
52:49
talking
52:49
about
52:50
evolve?
52:50
And
52:50
my
52:51
gut
52:51
tells
52:51
me
52:52
that
52:53
the
52:53
agentic
52:54
AI
52:54
platforms
52:55
are
52:55
going
52:55
to
52:55
start,
52:55
it's
52:56
going
52:56
to
52:56
become
52:56
Marketplace
52:57
2.0,
52:58
and
52:58
those
52:58
agentic
52:59
AI
52:59
platforms
53:00
are
53:00
going
53:00
to
53:00
get
53:00
a
53:00
cut
53:00
of
53:01
the
53:01
revenue
53:02
directed
53:02
from
53:03
those
53:03
retailers
53:03
that
53:03
ultimately
53:04
allow
53:04
them
53:05
to
53:05
plug
53:05
in
53:05
simply
53:06
and
53:06
easily.
53:06
It
53:06
won't
53:07
be
53:07
everybody,
53:07
but
53:07
it's
53:08
going
53:08
to
53:08
be
53:08
some
53:08
of
53:09
them.
53:09
And
53:10
so
53:10
the
53:10
task
53:10
list
53:10
for
53:11
me,
53:11
if
53:11
I'm
53:11
a
53:12
CEO
53:12
or,
53:13
you
53:13
know,
53:13
I'm
53:13
in
53:13
that
53:13
boardroom
53:14
trying
53:14
to
53:14
say,
53:15
how
53:15
do
53:15
I
53:15
do
53:15
this?
53:15
Is
53:16
I
53:16
have
53:16
to
53:16
ask
53:16
myself,
53:17
what
53:18
am
53:18
I
53:18
okay
53:18
with
53:19
getting
53:19
scraped
53:19
and
53:20
what
53:20
am
53:20
I
53:20
not
53:20
okay
53:21
with
53:21
getting
53:21
scraped?
53:22
Like,
53:22
do
53:22
I
53:22
want
53:23
agentic
53:23
agents
53:24
on
53:24
my
53:24
site
53:24
checking
53:25
out
53:25
for
53:25
someone
53:26
without
53:26
my,
53:26
without
53:27
that
53:27
customer
53:27
ever
53:28
entering
53:28
into
53:28
my
53:29
property?
53:29
My,
53:29
my
53:30
guess
53:30
is
53:30
they,
53:30
a
53:31
lot
53:31
of
53:31
people
53:31
probably
53:31
don't.
53:32
So
53:32
then
53:33
it
53:33
comes
53:33
down
53:33
to
53:34
what's
53:34
it
53:34
going
53:34
to
53:34
cost
53:35
for
53:35
me
53:35
to
53:36
prevent
53:36
certain
53:36
information
53:37
from
53:37
getting
53:37
transmitted
53:38
that
53:38
way?
53:38
I
53:38
don't
53:39
know
53:39
the
53:39
answer
53:39
to
53:39
that.
53:40
I
53:40
don't
53:40
even
53:40
know
53:40
if
53:40
it's
53:40
even
53:41
possible.
53:41
But
53:42
those
53:42
are
53:42
the
53:42
discussions
53:43
you've
53:43
got
53:43
to
53:43
start
53:43
outlining
53:44
what
53:44
are
53:44
we
53:44
okay
53:44
with,
53:45
what
53:45
are
53:45
we
53:45
not,
53:45
and
53:46
then
53:46
go
53:46
from
53:46
there,
53:46
in
53:47
my
53:47
opinion.
53:47
Yeah,
53:48
and
53:48
not
53:48
just
53:48
the,
53:48
the
53:49
economic
53:49
costs,
53:50
but
53:50
what
53:50
are
53:50
the
53:50
costs
53:50
if
53:51
the
53:51
customer
53:51
can't
53:51
purchase?
53:52
Like,
53:52
are
53:52
you
53:53
going
53:53
to
53:53
see
53:53
a
53:54
reduction
53:54
in
53:54
shop,
53:55
in
53:55
customer
53:55
shop
53:56
spend
53:56
or
53:56
awareness
53:57
of
53:57
your
53:57
product
53:57
if
53:58
you're
53:58
not
53:58
allowing
53:59
that
53:59
activity
53:59
to.
54:00
You
54:00
don't
54:00
get
54:00
the
54:00
first
54:01
party
54:01
data.
54:01
You
54:01
don't
54:01
get
54:02
anything
54:02
that
54:02
you're
54:03
used
54:03
to
54:03
getting.
54:03
There's
54:04
a
54:04
lot
54:04
of
54:04
costs
54:04
that
54:05
come
54:05
with
54:05
allowing
54:06
sites
54:06
or
54:07
bots
54:07
to
54:07
scrape
54:08
you
54:08
in
54:08
ways
54:09
that
54:09
you're
54:09
not
54:09
ready
54:09
for.
54:10
Right.
54:11
All
54:11
right,
54:11
you
54:11
guys,
54:12
let's
54:12
close
54:12
it
54:12
up
54:12
with
54:12
the
54:12
lightning
54:13
round.
54:14
Chad,
54:14
you
54:14
get
54:14
question
54:15
number
54:15
one.
54:16
Morrisons
54:17
recently
54:17
announced
54:17
that
54:17
it
54:18
will
54:18
limit
54:18
which
54:18
colleagues
54:19
it
54:19
allows
54:20
it
54:20
in
54:20
its
54:21
stores,
54:21
back
54:22
rooms
54:22
to
54:22
prevent
54:23
what
54:23
they're
54:23
calling,
54:24
quote,
54:24
idling
54:25
and
54:25
promote
54:26
more
54:26
service
54:27
on
54:27
the
54:27
shop
54:27
floor.
54:28
Did
54:28
you
54:28
ever
54:28
idle
54:29
in
54:29
a
54:29
stockroom
54:30
back
54:30
in
54:30
your
54:30
early
54:30
career
54:31
days,
54:31
Chad?
54:32
You
54:33
know,
54:33
my,
54:33
my
54:33
first
54:34
real
54:34
job
54:35
was
54:35
I
54:35
worked
54:36
at
54:36
a
54:36
grocery
54:36
store
54:37
in
54:37
the
54:37
grill
54:37
area
54:39
when
54:39
I
54:39
was
54:39
in
54:40
high
54:40
school.
54:40
Chef's
54:41
hat
54:41
and
54:42
everything.
54:42
Yes,
54:43
I
54:43
was
54:43
the
54:43
panini
54:44
king.
54:45
You
54:45
know,
54:46
there
54:46
were
54:46
likely.
54:48
There
54:49
were,
54:49
there
54:49
were
54:49
likely
54:49
some
54:50
times
54:50
that
54:50
I
54:50
Idled
54:51
in
54:51
the
54:51
back,
54:52
maybe
54:52
took
54:52
a
54:52
stroll
54:53
through
54:53
the,
54:54
you
54:54
know,
54:54
refrigerated
54:55
cooler
54:55
room.
54:56
And
54:56
I
54:57
didn't
54:57
want
54:58
to
54:58
maybe
54:58
be
54:58
next
54:58
up
54:59
for
54:59
a
54:59
customer
55:00
order,
55:00
you
55:00
know,
55:00
if
55:00
I
55:00
got
55:01
through
55:01
a
55:01
lunch
55:01
crowd
55:02
or
55:02
something.
55:02
So.
55:03
Yeah,
55:03
probably
55:04
prone
55:04
to
55:04
happen
55:04
a
55:04
few
55:05
times.
55:05
My
55:06
gosh.
55:06
Played
55:06
some
55:07
games
55:07
with
55:07
this
55:07
pricing
55:08
sticker
55:08
gun
55:09
behind
55:09
the
55:10
scenes.
55:10
Sure,
55:10
I
55:11
see
55:11
what
55:11
you're
55:12
doing
55:12
there.
55:13
All
55:14
right,
55:14
next
55:14
one.
55:14
Call
55:15
her
55:15
daddy.
55:15
Host
55:15
Alex
55:16
Cooper
55:16
got
55:16
booed
55:17
mercilessly
55:17
for
55:17
her
55:18
rendition
55:18
of
55:18
Take
55:18
Me
55:19
out
55:19
to
55:19
the
55:19
Ball
55:19
Game
55:19
at
55:19
Wrigley
55:20
Field
55:20
last
55:20
week.
55:21
David,
55:22
I'm
55:22
guessing
55:22
you,
55:22
you
55:23
saw
55:23
the
55:23
video
55:23
of
55:24
this.
55:24
So
55:24
if
55:24
you
55:25
were
55:25
to
55:25
serenade
55:25
the
55:26
crowd
55:26
during
55:26
the
55:26
seventh
55:26
inning
55:27
stretch,
55:27
how
55:28
would
55:28
you
55:28
handle
55:28
it?
55:28
Would
55:29
you
55:29
straight
55:29
sing
55:29
it
55:29
or
55:30
would
55:30
you
55:30
ham
55:30
it
55:30
up?
55:32
Yeah,
55:33
you
55:33
know,
55:33
well,
55:33
hey,
55:34
I'm
55:34
the
55:34
world's
55:34
worst
55:35
singer,
55:35
so
55:35
I
55:35
would
55:35
never
55:36
get
55:36
asked
55:36
to.
55:37
To
55:37
sing
55:37
it,
55:37
but
55:39
I
55:39
think
55:39
I'd
55:39
have
55:39
to
55:40
go
55:40
very.
55:41
It's
55:41
one
55:41
of
55:41
the
55:41
great
55:42
traditions
55:43
and
55:43
it's
55:43
so
55:43
classical.
55:44
I.
55:44
So
55:44
I.
55:45
I
55:45
think
55:45
you
55:45
gotta
55:45
go
55:46
straight
55:47
sing
55:47
it,
55:47
engage
55:48
the
55:48
crowd
55:49
and,
55:49
and
55:50
do
55:50
it
55:50
by
55:51
the
55:51
book.
55:51
It's
55:51
the
55:52
only
55:52
other.
55:52
Otherwise
55:53
you.
55:53
It's
55:53
just
55:53
way
55:54
too
55:54
risky.
55:54
Right.
55:55
And
55:55
it's
55:55
not
55:55
as
55:55
much
55:55
fun.
55:57
Yeah.
55:58
All
55:58
right,
55:59
David,
55:59
you
55:59
get
55:59
question
56:00
number
56:00
three
56:00
as
56:00
well.
56:01
Nextdoor
56:02
just
56:02
announced
56:02
that
56:02
they're
56:03
re
56:03
platforming
56:04
with
56:04
the
56:04
help
56:04
of
56:04
AI
56:05
to
56:05
focus
56:05
on
56:05
more
56:06
real
56:06
time
56:06
news
56:07
and
56:07
safety
56:07
updates
56:08
for
56:08
neighbors
56:09
and
56:09
cut
56:09
back
56:10
on
56:10
the
56:10
cranky
56:11
neighbor
56:11
posts.
56:12
Have
56:12
you
56:12
ever
56:12
posted
56:13
on
56:13
the
56:13
app
56:14
and
56:14
if
56:14
so,
56:15
why?
56:16
And
56:16
extra
56:17
points
56:17
here.
56:17
If
56:17
it
56:18
was
56:18
to
56:18
shut
56:18
down
56:19
one
56:19
of
56:19
those
56:19
cranky
56:20
neighbors.
56:21
Yeah.
56:22
So
56:23
a
56:24
little
56:24
embarrassed
56:25
to
56:25
admit
56:25
this,
56:25
but
56:26
I'll
56:26
admit
56:27
it
56:27
anyways.
56:27
Are
56:28
you
56:28
the
56:28
cranky
56:28
neighbor?
56:33
I
56:33
am
56:33
not
56:33
the
56:33
cranky
56:34
neighbor,
56:35
but
56:35
I
56:35
have
56:35
shut
56:36
down
56:36
a
56:36
cranky
56:36
neighbor.
56:37
Oh.
56:38
Using
56:38
my
56:38
wife's
56:39
account.
56:40
Oh,
56:40
okay,
56:41
nice.
56:43
Without
56:44
her
56:44
authorization,
56:45
of
56:45
course.
56:46
Which
56:47
when
56:47
it
56:47
was
56:48
found
56:48
out,
56:48
did
56:50
make
56:50
me
56:50
contribute
56:51
to
56:51
the
56:51
luxury
56:52
goods
56:52
market
56:53
as.
56:53
As
56:54
a
56:54
doghouse
56:56
to
56:56
get
56:56
myself
56:57
out
56:57
of
56:57
the
56:57
doghouse.
56:58
But
56:58
yeah,
56:58
I
56:59
actually
56:59
think
56:59
it's
56:59
a
56:59
really
56:59
good
57:00
thing
57:00
like
57:00
that
57:00
they're
57:00
re
57:01
platforming.
57:01
Wow.
57:02
Great
57:02
story,
57:02
David.
57:03
God.
57:03
Yeah,
57:03
I
57:03
100
57:04
agree.
57:05
All
57:05
right.
57:05
An
57:05
influencer,
57:06
Mia
57:06
Zilou.
57:07
I
57:07
think
57:07
I'm
57:08
pronouncing
57:08
that
57:08
name.
57:08
Right.
57:09
An
57:09
AI
57:09
powered
57:10
social
57:10
media
57:10
star
57:11
who
57:11
has
57:11
amassed
57:11
over
57:12
150
57:12
Instagram
57:13
followers
57:13
by
57:14
sharing
57:14
sexy
57:14
pics
57:15
of
57:15
herself
57:15
at
57:16
various
57:16
tennis
57:16
events.
57:17
Took
57:17
Wimbledon
57:18
by
57:18
storm
57:19
last
57:19
week.
57:19
But
57:19
there's
57:19
a
57:19
catch.
57:20
If
57:20
you
57:20
caught
57:20
that
57:21
Mia
57:21
is
57:21
not
57:21
real.
57:22
She
57:22
is
57:23
100%
57:23
AI
57:24
generated.
57:24
I
57:25
looked
57:25
at
57:25
the
57:25
photos
57:25
and
57:26
I
57:26
cannot
57:26
tell
57:27
the
57:27
difference,
57:28
folks.
57:29
Chad,
57:29
how
57:29
long
57:30
do
57:30
you
57:30
think
57:30
before
57:31
AI
57:31
influencers
57:32
start
57:32
popping
57:32
up
57:32
inside
57:33
of
57:33
retail
57:34
stores
57:34
like
57:34
actual
57:35
shoppers?
57:37
I.
57:37
And
57:37
I'm.
57:38
Well,
57:38
I
57:38
guess
57:38
I'm
57:38
glad
57:39
that
57:39
you're
57:39
asking
57:39
me
57:39
a
57:40
more
57:40
professionally
57:41
oriented
57:42
question
57:42
related
57:43
to
57:43
this
57:43
could
57:43
have
57:44
gone
57:44
in.
57:44
So
57:44
many
57:44
directions
57:45
otherwise.
57:45
I
57:46
don't
57:46
even
57:46
know
57:46
what
57:46
I
57:46
would
57:47
say.
57:47
Like,
57:47
you
57:48
know,
57:48
do
57:48
we
57:48
get
57:48
sexy
57:49
AI
57:49
and
57:49
Lululemon?
57:50
What
57:50
does
57:50
that
57:51
mean?
57:51
I.
57:52
Listen,
57:52
I.
57:53
I
57:53
don't
57:53
actually
57:53
think
57:54
AI
57:54
modeling
57:55
is
57:55
that
57:55
far
57:56
off.
57:56
Honestly.
57:57
The
57:58
economics
57:59
of
57:59
cutting
58:00
down
58:00
and
58:00
marketing,
58:01
creative
58:01
and
58:01
photo
58:02
shoots
58:02
and
58:03
all,
58:03
like
58:04
the
58:04
first
58:04
ones
58:05
who
58:05
do
58:05
it
58:05
are
58:05
going
58:05
to
58:06
get
58:06
some,
58:06
you
58:06
know,
58:07
public
58:07
backlash
58:08
for
58:08
sure.
58:08
But
58:09
I
58:09
think
58:09
it'll
58:09
be
58:09
short
58:09
lived
58:10
and
58:10
this
58:11
actually
58:11
will
58:12
happen.
58:13
Yeah.
58:13
Wow.
58:14
Yeah,
58:14
it's
58:14
probably,
58:14
it's
58:15
probably
58:15
closer
58:15
than
58:15
it
58:16
appears.
58:16
The
58:16
objects
58:16
in
58:17
the
58:17
mirror
58:17
are
58:17
closer
58:17
than
58:18
they
58:18
appear.
58:18
Is
58:18
that
58:18
what
58:18
you're
58:19
saying,
58:19
Chad?
58:19
But
58:19
closer
58:20
than
58:20
maybe
58:20
we'll
58:21
realize,
58:21
given
58:21
that
58:22
no
58:22
one
58:22
even
58:22
knew
58:22
that
58:23
this
58:23
per,
58:23
you
58:23
know,
58:23
that
58:24
this
58:24
person,
58:24
that
58:25
this
58:25
wasn't
58:25
a
58:26
person.
58:26
So
58:26
I
58:27
honestly
58:28
could
58:28
not
58:28
tell
58:28
the
58:28
difference.
58:29
All
58:29
right,
58:29
well,
58:29
that
58:29
closes
58:30
us
58:30
up.
58:31
Thanks
58:31
for
58:31
a
58:31
great
58:31
show.
58:31
You
58:31
too.
58:32
Happy
58:32
birthday
58:32
today
58:33
to
58:33
Fatboy
58:33
Slim,
58:34
Corey
58:34
Feldman
58:35
and
58:35
to
58:35
the
58:35
man
58:36
who
58:36
helped
58:36
us
58:36
all
58:36
wonder
58:37
if
58:37
there
58:37
is
58:38
enough
58:38
time
58:38
on
58:39
Saturday
58:39
to
58:40
go
58:40
to
58:40
Home
58:40
Depot
58:41
and
58:41
Bed
58:41
Bath
58:42
and
58:42
Beyond
58:42
in
58:42
the
58:42
same
58:43
day,
58:43
the
58:43
incomparable
58:44
Will
58:45
Ferrell.
58:45
And
58:46
remember,
58:46
if
58:46
you
58:46
can
58:46
only
58:47
read
58:47
or
58:47
listen
58:47
to
58:47
one
58:47
retail
58:48
blog
58:48
in
58:48
the
58:48
business,
58:48
Make
58:49
It
58:49
Omnitok,
58:49
the
58:49
only
58:50
retail
58:50
media
58:50
outlet
58:50
run
58:51
by
58:51
two
58:51
former
58:51
executives
58:52
from
58:52
a
58:52
current
58:52
top
58:52
10
58:53
US
58:53
retailer.
58:54
Our
58:54
fast
58:54
Buy
58:54
podcast
58:55
is
58:55
the
58:55
quickest,
58:55
fastest
58:56
rundown
58:56
of
58:56
all
58:56
the
58:56
week's
58:57
top
58:57
news.
58:57
And
58:57
our
58:57
daily
58:58
newsletter,
58:58
the
58:58
Retail
58:59
Daily
58:59
Minute,
58:59
tells
59:00
you
59:00
all
59:00
you
59:00
need
59:00
to
59:01
know
59:01
each
59:01
day
59:01
to
59:01
stay
59:01
on
59:02
top
59:02
of
59:02
your
59:02
game
59:02
as
59:02
a
59:02
retail
59:03
executive
59:03
and
59:03
also
59:04
regularly
59:04
feature
59:04
special
59:05
content
59:05
that
59:05
is
59:06
exclusive
59:06
to
59:06
us
59:06
and
59:07
that
59:07
Ann
59:07
and
59:07
I
59:07
take
59:08
a
59:08
lot
59:08
of
59:08
pride
59:08
in
59:08
doing
59:09
just
59:09
for
59:09
you.
59:09
Thanks
59:09
as
59:09
always
59:10
for
59:10
listening
59:10
in.
59:10
Please
59:10
remember
59:11
to
59:11
like
59:11
and
59:11
leave
59:11
us
59:11
a
59:11
review.
59:12
Wherever
59:12
you
59:12
happen
59:12
to
59:13
listen
59:13
to
59:13
your
59:13
podcast
59:14
or
59:14
on
59:14
YouTube,
59:15
you
59:15
can
59:15
watch
59:16
this
59:16
episode
59:16
in
59:17
its
59:17
entirety
59:18
by
59:18
Simply
59:18
going
59:18
to
59:19
YouTube.com
59:20
Amitalkretail
59:22
Chad,
59:22
if
59:22
people
59:23
were
59:23
listening,
59:23
they
59:23
want
59:23
to
59:23
get
59:24
in
59:24
touch
59:24
with
59:24
the
59:24
A
59:24
and
59:24
M
59:25
consumer
59:25
and
59:25
retail
59:25
group.
59:26
Pick
59:26
your
59:27
brains,
59:27
you
59:27
and
59:27
David's
59:28
brains
59:28
about
59:28
anything
59:29
that's
59:29
on
59:29
their
59:29
minds.
59:29
What's
59:30
the
59:30
best
59:30
way
59:30
for
59:30
them
59:30
to
59:30
do
59:31
that?
59:32
You
59:32
can
59:32
always
59:32
learn
59:33
more
59:33
about
59:34
us
59:34
and
59:34
our
59:34
practice
59:35
at
59:35
Alvarez
59:36
and
59:36
marsal-crg.com
59:39
find
59:40
us
59:40
on
59:40
our
59:40
LinkedIn
59:41
@
59:41
Alvarez
59:42
and
59:42
Marsal
59:42
Consumer
59:43
and
59:43
Retail
59:43
Group.
59:43
But
59:44
because
59:44
we're
59:45
so
59:45
gosh
59:45
darn
59:45
approachable,
59:46
feel
59:46
free
59:46
to
59:47
reach
59:47
out
59:47
directly
59:48
to
59:48
David
59:48
and
59:48
I.
59:49
And
59:50
happy
59:50
to.
59:51
Happy
59:51
to
59:51
connect.
59:53
All
59:53
right,
59:53
well,
59:53
thank
59:54
you
59:54
again
59:54
to
59:54
David
59:55
Brown
59:55
and
59:55
Chad
59:55
Lusk
59:56
of
59:56
the
59:56
A
59:56
and
59:56
M
59:56
Consumer
59:57
and
59:57
Retail
59:57
Group
59:57
for
59:58
joining
59:58
us,
59:58
as
59:58
they
59:58
do
59:59
every
59:59
month.
1:00:00
And
1:00:00
on
1:00:00
behalf
1:00:00
of
1:00:01
all
1:00:01
of
1:00:01
us
1:00:01
at
1:00:01
Omnitalk
1:00:02
Retail,
1:00:02
as
1:00:02
always,
1:00:02
be
1:00:03
careful
1:00:03
out
1:00:03
there.