Latest / Omni Talk Retail / Amazon’s Temu Rivalry, 7-Eleven & Why Goldman Sachs Thinks 2025 Is The Year Of The Robot | Fast Five

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Amazon’s Temu Rivalry, 7-Eleven & Why Goldman Sachs Thinks 2025 Is The Year Of The Robot | Fast Five · Omni Talk Retail

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1:49
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1:49
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1:49
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1:49
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1:49
smarter,
1:50
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1:50
most
1:50
importantly,
1:51
a
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1:51
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1:52
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1:53
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2:00
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2:00
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2:00
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2:01
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2:01
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2:07
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2:09
Trends.
2:09
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2:10
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2:10
October
2:11
30,
2:11
2024.
2:12
I'm
2:12
one
2:12
of
2:12
your
2:13
hosts
2:13
and
2:13
mazinga.
2:14
And
2:14
I'm
2:15
Chris
2:15
Walton
2:16
and
2:16
we
2:16
are.
2:16
Here
2:17
once
2:17
again
2:17
to
2:17
discuss
2:18
all
2:18
the
2:18
top
2:18
headlines
2:19
from
2:19
the
2:19
past
2:19
week
2:20
making
2:20
waves
2:20
in
2:20
the
2:21
world
2:21
of
2:21
omnichannel
2:22
retailing.
2:22
Now,
2:23
Chris,
2:23
it's
2:24
spooky
2:24
season.
2:25
Apparently
2:26
we
2:26
say
2:26
spooky
2:27
season
2:27
now.
2:27
We
2:27
don't
2:27
say
2:28
Halloween
2:28
anymore.
2:28
I
2:28
don't
2:29
know
2:29
if
2:29
oh
2:29
do
2:29
we?
2:30
Why
2:30
is
2:30
that?
2:31
I
2:31
have
2:32
no
2:32
idea.
2:32
Probably
2:33
Halloween
2:33
has
2:33
got
2:34
some
2:34
negative
2:34
connotation,
2:35
but
2:35
I've
2:35
noticed
2:36
that
2:36
all
2:36
my
2:37
favorite
2:37
retailers
2:38
are
2:38
calling
2:38
it
2:38
spooky
2:39
season
2:39
instead
2:39
of
2:40
Halloween.
2:41
But
2:41
we're
2:41
gonna
2:42
stick
2:42
with
2:42
Halloween
2:42
because
2:43
it's
2:43
your
2:43
favorite
2:43
holiday
2:44
of
2:44
all
2:44
holidays.
2:45
One
2:45
of
2:45
maybe
2:45
after
2:46
4th
2:46
of
2:46
July.
2:46
No,
2:46
no,
2:47
not
2:47
at
2:47
all.
2:48
Not
2:48
Halloween
2:48
doesn't
2:48
even
2:49
make
2:49
the
2:49
top
2:49
five
2:49
for
2:50
me.
2:50
I
2:50
thought
2:50
you
2:51
loved
2:51
it.
2:51
You
2:51
dress
2:52
up
2:52
like
2:52
Darth
2:52
Vader.
2:53
You
2:53
could
2:53
do
2:53
all
2:53
your
2:54
stuff
2:54
like.
2:55
Yeah,
2:55
but
2:55
I
2:55
still
2:56
don't
2:56
love
2:56
it.
2:56
I
2:56
still
2:56
get
2:57
into
2:57
it,
2:57
but
2:57
it's
2:57
not,
2:58
it's
2:58
not
2:58
in
2:58
my
2:58
top
2:59
five
2:59
for
2:59
sure.
2:59
No.
3:00
No
3:00
way.
3:00
No
3:00
way.
3:01
How
3:01
do
3:01
you
3:01
distinguish
3:02
this?
3:02
You,
3:03
how
3:03
do
3:03
you
3:03
distinguish?
3:04
I
3:04
get
3:04
into
3:04
it
3:05
versus
3:05
top
3:06
holidays.
3:06
Oh,
3:07
because,
3:07
because
3:08
it's
3:08
all,
3:08
it's
3:08
all
3:08
about
3:08
the
3:09
family
3:09
interaction,
3:09
the
3:10
eating,
3:10
the
3:10
whole
3:10
nine
3:11
yards.
3:11
You
3:11
know,
3:11
I
3:11
put
3:12
fourth
3:12
of
3:12
July
3:13
and
3:13
Thanksgiving
3:13
at
3:13
the
3:14
top
3:14
of
3:14
the
3:14
list.
3:15
Christmas,
3:15
New
3:16
Year's,
3:16
those
3:16
all
3:17
trump
3:17
Halloween
3:18
for
3:18
me.
3:18
I
3:18
don't
3:18
know.
3:19
We
3:19
got
3:19
to
3:19
do
3:19
a
3:20
whole
3:20
segment
3:20
on
3:20
what
3:21
are
3:21
the
3:21
best
3:21
five
3:22
holidays.
3:22
That's
3:22
what,
3:22
that's
3:23
what
3:23
I'm
3:23
hearing
3:23
from
3:23
this
3:24
conversation.
3:25
I
3:25
feel
3:25
like
3:25
I
3:25
don't
3:26
even
3:26
know
3:26
you
3:26
anymore.
3:27
Like
3:27
you're
3:27
profile
3:28
picture
3:28
was
3:28
you
3:29
as
3:29
Darth
3:29
Vader
3:29
for
3:30
a
3:30
long
3:30
time
3:31
because
3:31
of
3:31
Darth
3:31
Vader.
3:32
Not
3:32
because
3:32
of
3:32
Halloween
3:33
though.
3:33
You
3:33
know,
3:34
like
3:34
that's
3:34
the
3:34
thing,
3:35
you
3:35
know,
3:35
it's,
3:35
it's
3:35
like,
3:36
it's
3:36
like,
3:36
it's
3:37
like,
3:37
it's
3:37
like
3:37
a
3:37
totally
3:38
different
3:38
vibe,
3:38
you
3:39
know,
3:39
for
3:39
me
3:39
with
3:39
Halloween
3:40
and
3:40
Darth
3:40
Vader.
3:40
Anytime
3:41
I
3:41
can
3:41
dress
3:41
up
3:41
as
3:41
Darth
3:41
Vader,
3:42
it's
3:42
a
3:42
win
3:42
for
3:42
me
3:43
and
3:43
my
3:43
family
3:43
and.
3:44
Come
3:44
on,
3:46
for
3:46
you.
3:47
Well,
3:47
maybe
3:48
not
3:48
for
3:48
my
3:48
family.
3:48
That's
3:49
a
3:49
good
3:49
point.
3:49
That's
3:49
why
3:49
I
3:50
thought,
3:50
I
3:50
thought
3:50
we've
3:50
had
3:50
this
3:51
conversation
3:51
before
3:51
too.
3:52
Hey.
3:52
Although
3:53
I
3:53
did
3:53
meet
3:53
my
3:54
husband
3:54
on
3:54
Halloween
3:55
night.
3:55
Guess
3:56
What?
3:56
It's
3:56
our
3:56
10
3:56
year
3:57
anniversary
3:58
of
3:58
our,
3:58
of
3:58
then
3:59
fateful
3:59
night
4:00
that
4:00
we
4:00
met
4:00
tomorrow.
4:01
So
4:02
we
4:02
are.
4:03
Yes.
4:03
So
4:03
that's
4:03
a
4:04
good,
4:04
that's
4:04
a
4:05
good
4:05
part
4:05
of
4:06
Halloween.
4:06
But
4:07
it's
4:07
so
4:07
stressful.
4:08
Like
4:08
I
4:09
already
4:09
lost.
4:10
It
4:10
is
4:11
next
4:11
week,
4:11
so
4:12
I
4:12
think
4:12
my
4:12
kids
4:12
costume
4:13
got
4:13
packed
4:13
somewhere
4:14
so
4:14
now
4:14
we're
4:14
like
4:15
an
4:15
emergency
4:15
costume
4:16
finding
4:16
mode.
4:17
It's
4:17
just.
4:18
Oh,
4:18
it's
4:19
terrible.
4:19
Yeah,
4:20
I
4:20
agree.
4:20
Like
4:21
after,
4:21
after
4:22
Christmas,
4:22
Halloween
4:22
probably
4:23
puts
4:23
the
4:23
most
4:23
pressure
4:23
on
4:24
the
4:24
parent.
4:24
You
4:24
got
4:24
to
4:24
get
4:24
the
4:25
pumpkins
4:25
carved,
4:26
you
4:26
got
4:26
to
4:26
get
4:26
the
4:26
candy
4:27
out,
4:27
you
4:27
got
4:27
to
4:27
get
4:28
the
4:28
costume
4:28
going.
4:29
Lots
4:29
of
4:29
kids
4:30
things
4:30
to
4:30
coordinate.
4:30
Yeah,
4:31
I'm
4:31
with
4:31
you
4:31
but.
4:32
And
4:32
let's
4:32
talk
4:32
about
4:33
the
4:33
decor.
4:33
Like
4:34
Sarah
4:34
Post
4:34
from
4:35
Home
4:35
Depot
4:35
is
4:35
talking
4:35
about
4:36
the
4:36
Giants
4:36
now.
4:37
Like,
4:37
since
4:37
when
4:38
does
4:38
everybody
4:38
have
4:39
massive
4:40
skeletons
4:40
coming
4:41
out
4:41
of
4:41
their
4:41
yard?
4:42
Like,
4:42
this
4:42
is
4:42
bigger
4:43
than
4:43
Christmas,
4:43
I
4:43
think.
4:44
Yeah,
4:44
see,
4:45
I'm
4:45
big
4:45
into
4:45
that,
4:46
though.
4:46
Like,
4:46
if
4:46
I
4:47
could
4:47
do
4:47
that,
4:47
Like,
4:48
I'm
4:48
big
4:48
into
4:48
that
4:49
as
4:49
well.
4:49
Like
4:50
a
4:50
giant
4:50
Darth
4:51
Vader.
4:51
Like
4:51
those
4:52
skeletons.
4:52
That
4:52
would
4:52
be
4:53
huge
4:53
to
4:53
put
4:53
out
4:54
there.
4:54
Like
4:54
a
4:54
Darth
4:54
Vader.
4:55
Darth
4:55
Vader.
4:56
Like
4:56
Halloween
4:56
dressed
4:57
up.
4:57
But
4:57
it's
4:57
not
4:57
your
4:58
favorite
4:58
holiday.
4:58
But
4:59
you
4:59
don't.
4:59
It's
4:59
not
4:59
my
4:59
favorite
5:00
holiday.
5:00
It's
5:00
not
5:00
my
5:00
favorite
5:01
top
5:01
five.
5:02
We're
5:02
gonna
5:02
come
5:03
back
5:03
to
5:03
this.
5:03
We're
5:03
gonna
5:03
do
5:03
a
5:04
special
5:04
segment
5:04
because
5:05
we've
5:05
already
5:05
lost
5:05
track
5:05
of
5:06
this.
5:06
We've
5:07
already
5:07
lost
5:07
track
5:07
of
5:07
the
5:08
show
5:08
from
5:08
a
5:08
timing
5:08
standpoint.
5:09
We're
5:09
gonna
5:09
come
5:09
back
5:09
to
5:10
this.
5:10
We're
5:10
gonna
5:10
do.
5:10
Okay,
5:11
we're
5:11
gonna
5:11
do
5:11
Omnitox
5:12
five
5:13
favorite
5:13
Holidays.
5:13
And
5:13
we
5:13
should
5:14
do
5:14
that
5:14
for
5:14
Chris
5:15
for
5:15
December.
5:15
Let's
5:16
do
5:16
that.
5:16
Let's
5:16
put
5:16
that
5:16
on
5:16
the
5:16
list.
5:17
All
5:17
right,
5:17
five
5:18
favorite
5:18
holidays.
5:18
Let's
5:19
debate
5:19
them,
5:19
the
5:20
merits
5:20
of
5:20
them
5:20
all,
5:21
pros
5:21
and
5:21
cons.
5:22
All
5:22
right.
5:22
All
5:23
right,
5:23
let's
5:23
get
5:23
to
5:24
today's
5:24
headlines.
5:24
What
5:25
a
5:25
great
5:25
show.
5:26
All
5:26
right,
5:26
today's
5:27
Fast
5:27
5.
5:27
We've
5:28
got
5:28
news
5:28
on
5:29
Seven
5:29
Eleven's
5:29
plans
5:30
to
5:30
open
5:30
up
5:31
600
5:31
new
5:31
stores
5:32
with
5:32
a
5:32
new
5:32
design
5:33
format.
5:34
Simi
5:34
Robotics
5:35
raising
5:35
$50
5:36
million
5:36
in
5:37
Series
5:37
C
5:38
funding.
5:38
Wayfair
5:39
launching
5:39
a
5:39
paid
5:40
loyalty
5:40
program.
5:41
Marks
5:42
and
5:42
Spencer's
5:42
adding
5:43
self
5:43
checkout
5:43
to,
5:43
of
5:44
all
5:44
places,
5:45
their
5:45
dressing
5:45
rooms.
5:46
And
5:46
Doug
5:47
Tiffin
5:47
from
5:47
AWS
5:48
stops
5:49
by
5:49
to
5:49
talk
5:49
about
5:49
AI
5:50
investments
5:50
in
5:51
the
5:51
fashion
5:51
and
5:51
apparel
5:52
space.
5:53
But
5:53
we
5:53
begin
5:53
today
5:54
with
5:54
big
5:54
ultra
5:55
low
5:55
pricing
5:56
news
5:56
out
5:56
of
5:57
Amazon.
5:57
And
5:58
there
5:59
were
5:59
more
5:59
headlines
5:59
out
6:00
of
6:00
Amazon
6:00
this
6:00
last
6:01
week
6:01
than
6:01
I
6:02
think
6:02
have
6:02
ever
6:03
happened.
6:03
Chris.
6:03
There
6:04
were
6:04
a
6:04
lot.
6:04
But
6:05
this
6:05
one
6:05
is
6:05
of
6:06
particular
6:06
interest
6:07
that
6:07
we
6:07
picked
6:07
headline
6:08
number
6:08
one.
6:09
Amazon
6:09
appears
6:10
to
6:10
be
6:10
going
6:10
aggressively
6:11
after
6:11
Shein
6:11
and
6:12
Temu
6:12
on
6:12
price.
6:13
According
6:13
to
6:13
Reuters.
6:14
By
6:14
way
6:14
of
6:15
the
6:15
information,
6:16
Amazon
6:16
is
6:17
imposing
6:17
severe
6:17
price
6:18
caps
6:18
on
6:18
what
6:18
merchants
6:19
can
6:19
charge
6:19
for
6:19
their
6:19
products
6:20
on
6:20
a
6:20
new
6:20
low
6:20
cost
6:21
storefront
6:21
that
6:21
the
6:22
e
6:22
commerce
6:22
giant
6:22
is
6:23
preparing
6:23
to
6:23
launch.
6:24
The
6:24
company's
6:25
price
6:25
limits
6:25
include
6:26
$8
6:27
for
6:27
jewelry,
6:28
$13
6:28
for
6:29
guitars,
6:29
and
6:30
this
6:30
one
6:30
blows
6:31
my
6:31
mind,
6:32
$20
6:32
for
6:33
sofas.
6:34
Not
6:34
sure
6:34
what
6:34
that
6:35
sofa
6:35
is
6:35
made
6:35
out
6:35
of.
6:36
That's
6:36
a
6:36
great
6:36
point.
6:37
The
6:37
croissant
6:37
lamp
6:38
sofa
6:38
that
6:39
we
6:39
were
6:39
talking
6:39
about
6:39
a
6:40
few
6:40
weeks
6:40
ago
6:40
on
6:40
the
6:40
lightning
6:40
round.
6:41
Okay,
6:42
but
6:42
anyway,
6:43
according
6:43
to
6:43
the
6:43
information's
6:44
report,
6:44
which
6:45
cited
6:45
messages
6:46
from
6:46
Amazon
6:47
to
6:47
merchants
6:47
and
6:47
included
6:48
a
6:48
list
6:48
of
6:48
700
6:49
items,
6:50
Amazon
6:51
plans
6:51
to
6:51
ship
6:51
orders
6:52
to
6:52
US
6:52
customers
6:53
directly
6:53
from
6:53
a
6:53
facility
6:54
In
6:54
Guangdong,
6:55
China.
6:56
Did
6:56
I
6:56
say
6:56
that
6:56
right?
6:56
Guangdong?
6:57
Yeah,
6:57
you
6:57
did.
6:58
You
6:58
nailed
6:58
it.
6:58
Okay.
6:59
All
6:59
right,
6:59
Good
6:59
enough
6:59
is
7:00
what
7:00
I'd
7:00
say.
7:01
All
7:01
right.
7:01
Adding
7:01
that
7:01
it
7:02
was
7:02
also
7:02
planning
7:02
to
7:03
charge
7:03
sellers
7:04
lower
7:04
fulfillment
7:04
fees
7:05
for
7:05
items
7:05
sold
7:06
through
7:06
the
7:06
new
7:06
storefront.
7:07
Chris,
7:08
why
7:08
do
7:08
you
7:08
think
7:09
Amazon
7:09
is
7:09
getting
7:10
so
7:10
aggressive
7:10
on
7:11
price
7:11
against
7:12
Temu
7:12
and
7:12
Shein?
7:14
Ooh,
7:14
starting
7:14
off
7:15
hot
7:15
and
7:15
all
7:15
right,
7:16
I
7:16
am,
7:16
I
7:17
think,
7:17
yeah,
7:17
I
7:18
think
7:18
because
7:18
they're
7:18
eating,
7:18
I
7:19
think
7:19
they're
7:19
eating
7:19
into
7:19
Amazon's
7:20
business.
7:20
They,
7:20
I
7:20
mean,
7:21
they
7:21
have
7:21
to
7:21
be.
7:22
You've
7:22
seen
7:22
the,
7:23
all
7:23
the
7:23
recent
7:23
numbers
7:23
bear
7:24
that
7:24
out.
7:24
You
7:24
see
7:24
the
7:24
number
7:24
of
7:25
app
7:25
downloads
7:25
in
7:25
the
7:25
US
7:26
like,
7:26
the
7:26
number
7:26
of
7:27
them
7:27
is
7:27
insane.
7:29
Amazon's
7:30
online
7:31
store
7:31
sales
7:32
rose
7:32
just
7:32
5%
7:32
in
7:33
the
7:33
last
7:33
quarter,
7:34
which
7:34
slowed
7:34
down
7:35
from
7:35
a
7:35
7%
7:36
increase
7:36
in
7:36
the
7:36
previous
7:37
quarter.
7:37
So
7:37
in
7:37
the
7:37
first
7:38
quarter
7:38
of
7:38
this
7:38
year.
7:38
So.
7:39
But
7:39
you
7:39
know,
7:40
more
7:40
importantly,
7:40
I
7:41
think
7:41
the
7:41
other
7:41
piece
7:42
of
7:42
this
7:42
is
7:43
it's
7:43
actually
7:43
a
7:44
strategic
7:44
assault
7:45
on
7:45
Amazon's
7:45
E
7:46
commerce
7:46
turf.
7:47
Like
7:47
Amazon
7:47
has
7:48
been,
7:48
has
7:48
been
7:48
known
7:49
as
7:49
the
7:49
low
7:49
price
7:49
leader.
7:50
And
7:51
like
7:51
we've
7:51
talked
7:51
about
7:51
on
7:51
this
7:52
show,
7:52
consumers
7:53
gravitate
7:53
to
7:54
the,
7:54
to
7:55
the
7:55
offering
7:55
that
7:55
gives
7:56
them
7:56
the
7:56
lowest
7:56
price,
7:56
which
7:57
Temu
7:57
and
7:57
Shein
7:57
are
7:58
now
7:58
effectively
7:59
doing.
7:59
So
7:59
then
7:59
I
8:00
have
8:00
to
8:00
ask,
8:00
the
8:00
question
8:01
for
8:01
me
8:01
is
8:01
what
8:02
are
8:02
the
8:02
implications
8:02
of
8:02
this?
8:03
The
8:03
question
8:03
I
8:03
have
8:03
to
8:04
ask
8:04
then,
8:04
Anne,
8:04
is
8:05
can
8:05
they
8:05
actually
8:05
win
8:06
this
8:06
pricing
8:07
war
8:07
in
8:07
this
8:08
way?
8:08
I
8:09
don't
8:09
know
8:09
that
8:09
they
8:09
can
8:10
at
8:10
this
8:10
point
8:10
because
8:10
she
8:11
and
8:11
Tim
8:11
are
8:12
pretty
8:12
entrenched
8:12
with
8:13
consumers.
8:13
Amazon's
8:14
just
8:14
trying
8:14
to
8:15
start
8:15
up
8:15
this
8:15
new,
8:16
you
8:16
know,
8:16
kind
8:16
of
8:16
format
8:17
in
8:17
this
8:17
vein
8:18
or
8:18
this
8:19
storefront
8:19
in
8:19
this
8:19
vein.
8:20
So
8:20
I
8:20
don't
8:21
know
8:21
that
8:21
they're
8:21
going
8:21
to
8:21
make,
8:22
make
8:22
a
8:22
lot
8:22
of
8:22
inroads
8:23
here.
8:23
I
8:23
think,
8:23
I
8:23
think
8:24
this
8:24
part
8:24
of
8:24
the
8:24
business
8:25
might
8:25
be
8:25
lost
8:26
forever,
8:27
especially
8:27
until
8:28
we
8:28
know
8:28
how
8:28
regulation
8:29
is
8:29
going
8:29
to
8:29
continue
8:29
to
8:29
impact
8:30
this,
8:30
this
8:31
direct
8:32
to
8:32
factory
8:33
way
8:34
of
8:34
doing
8:34
E
8:34
commerce
8:35
as
8:35
well.
8:35
But
8:35
what
8:35
do
8:35
you
8:36
think?
8:36
Well,
8:36
Chris,
8:37
but
8:37
I
8:37
guess
8:38
my
8:38
question
8:38
too
8:38
is
8:39
like,
8:39
I
8:40
assume
8:40
we're
8:40
talking
8:41
the
8:41
same
8:41
manufacturers.
8:42
I
8:42
mean,
8:42
from
8:42
my
8:43
experience,
8:43
ordering,
8:43
I
8:43
would
8:43
assume,
8:44
like,
8:45
yeah,
8:45
are
8:45
the,
8:46
are,
8:47
is
8:47
Amazon
8:48
asking
8:48
these
8:49
manufacturers
8:49
to
8:50
make
8:50
further
8:50
concessions
8:51
for
8:51
Amazon
8:51
than
8:52
they
8:52
are
8:52
for
8:52
Temu
8:53
and
8:53
Shein?
8:53
Or
8:53
is
8:53
this
8:54
like
8:54
this
8:54
is
8:54
just
8:55
standard
8:55
across
8:56
the
8:56
board?
8:56
Like
8:56
they're
8:56
already
8:57
doing
8:57
this,
8:57
so
8:57
it's
8:58
going
8:58
to
8:58
be
8:58
fine
8:58
like
8:58
that.
8:59
That
8:59
to
9:00
me
9:00
doesn't
9:00
make
9:00
sense.
9:01
Like
9:01
they've
9:01
already,
9:02
these
9:02
factories
9:02
already
9:02
have
9:03
these
9:03
longstanding
9:03
relationships
9:04
with
9:04
Sheen
9:04
and
9:04
Temu
9:05
and
9:05
who,
9:05
you
9:06
know,
9:06
just
9:06
because
9:06
Amazon
9:07
comes
9:07
in,
9:07
do
9:07
they
9:07
have
9:08
the
9:08
same
9:08
clout
9:08
that
9:08
they
9:09
might
9:09
have
9:09
in
9:09
the
9:10
US
9:10
Market
9:11
when
9:11
we're
9:11
talking
9:12
about,
9:12
you
9:13
know,
9:13
what
9:13
their
9:13
relationships
9:14
are
9:14
over
9:14
in
9:15
China.
9:15
But
9:16
I
9:17
disagree
9:17
with
9:17
you
9:18
a
9:18
little
9:18
bit
9:18
and
9:19
I'm
9:19
curious
9:19
what
9:19
you
9:20
think
9:20
about
9:20
this.
9:20
Let's
9:20
get
9:20
it
9:20
going.
9:21
So
9:22
I
9:22
think
9:23
this
9:23
could
9:23
be
9:23
a
9:23
massive
9:24
opportunity
9:24
for
9:24
Amazon.
9:25
Like
9:25
huge.
9:26
Because
9:27
I
9:27
think
9:27
if
9:27
you
9:28
look
9:28
at
9:28
the
9:29
brands,
9:29
I
9:29
was
9:29
even
9:30
shocked
9:30
by
9:30
this.
9:30
But
9:31
if
9:31
you
9:31
look
9:31
at
9:31
the
9:32
brands
9:32
that
9:32
are
9:33
most
9:33
beloved
9:33
by
9:34
Gen
9:34
Z,
9:35
again,
9:35
the
9:35
generation
9:35
that's
9:36
holding
9:36
the
9:36
most
9:37
buying
9:37
power
9:37
that
9:38
any
9:38
of
9:38
any
9:38
generation
9:39
at
9:39
this
9:40
existing
9:40
age,
9:41
Amazon
9:41
is
9:42
consistently
9:42
ranked
9:43
among
9:43
their
9:43
favorites
9:44
and
9:44
in
9:44
some
9:44
cases
9:45
even
9:45
in
9:45
the
9:45
top
9:46
10
9:46
of
9:47
their
9:47
favorite
9:48
brands.
9:48
So
9:49
I
9:49
have
9:49
to
9:49
ask
9:49
you,
9:50
Chris.
9:50
If
9:51
you're
9:51
another
9:52
question.
9:52
I
9:52
do
9:53
I
9:53
have
9:53
to
9:53
ask
9:53
you
9:54
this
9:54
question.
9:54
So
9:55
if
9:55
you're
9:55
going
9:55
to
9:55
order,
9:56
let's
9:56
talk,
9:56
let's
9:57
say
9:57
like
9:57
shoe
9:57
organizers
9:58
for
9:58
your
9:58
closet
9:59
or
9:59
something,
10:00
something
10:00
like
10:00
that.
10:01
Are
10:01
you
10:02
more
10:02
comfortable
10:02
ordering
10:03
that
10:03
from
10:04
Amazon
10:04
as
10:05
a
10:05
US
10:05
Consumer?
10:05
Are
10:06
you
10:06
more
10:06
comfortable
10:06
ordering
10:06
that
10:07
from
10:07
Amazon
10:07
or
10:07
from
10:08
temu?
10:10
It's
10:10
a
10:10
good
10:10
question.
10:11
Yeah,
10:11
it's
10:11
a,
10:11
it's
10:11
a
10:11
really
10:12
good
10:12
question.
10:12
So
10:12
I,
10:13
that's
10:13
what's
10:13
tough
10:13
for
10:14
me
10:14
on
10:14
this.
10:14
It's,
10:14
it
10:15
depends
10:15
on
10:15
the
10:15
user
10:15
experience
10:16
because
10:16
I
10:16
talked
10:16
to
10:16
the
10:16
folks
10:16
at
10:17
temu
10:17
for
10:17
like
10:17
30,
10:18
45
10:18
minutes
10:18
one
10:19
day.
10:19
Yeah.
10:19
And
10:19
they
10:20
say
10:20
while
10:20
the
10:20
direct
10:20
to
10:20
factory
10:21
model
10:21
is
10:21
part
10:21
of
10:22
it,
10:22
it's
10:22
also
10:22
the
10:22
gamification
10:23
and
10:23
the
10:23
user
10:24
interface
10:24
is
10:24
also
10:25
part
10:25
of
10:25
this.
10:25
True.
10:26
So
10:26
the
10:26
Amazon
10:27
experience,
10:27
as
10:27
you'
10:28
describing
10:28
it,
10:29
operates
10:29
and
10:30
behaves
10:30
differently.
10:31
But
10:31
with
10:31
that
10:32
said,
10:32
like,
10:32
could
10:32
I
10:32
as
10:32
a
10:33
young
10:33
consumer
10:33
be
10:34
browsing
10:34
Amazon
10:34
and
10:34
looking
10:35
for
10:35
storage
10:35
organization
10:36
solutions
10:36
that
10:36
are
10:37
cheap?
10:37
Yes,
10:38
I
10:38
could.
10:39
So
10:39
maybe
10:39
they
10:39
get
10:40
some
10:40
of
10:40
this
10:40
business,
10:41
you
10:41
know,
10:41
that
10:41
they've
10:42
been
10:42
losing
10:42
to
10:43
TEU
10:43
and
10:43
Sheen.
10:43
But,
10:44
but
10:44
I
10:44
don't
10:44
know
10:45
that
10:45
they
10:45
can
10:45
ever
10:45
get
10:46
the
10:46
total
10:47
amount.
10:47
I
10:47
don't
10:47
know
10:47
that
10:47
they
10:48
can
10:48
ever
10:48
just
10:48
like
10:48
shut
10:48
them
10:49
out
10:49
of
10:49
the
10:49
market
10:49
at
10:49
this
10:49
point.
10:50
I
10:50
think
10:50
that
10:50
that's
10:50
the
10:51
point
10:51
I'm
10:51
trying
10:51
to
10:51
make
10:51
here
10:51
is
10:52
like,
10:52
yeah,
10:52
true.
10:52
They,
10:53
they,
10:53
it
10:53
just
10:53
seems
10:54
like
10:54
this
10:54
is
10:55
a
10:55
hard
10:55
game
10:55
for
10:55
Amazon
10:56
to
10:56
stand
10:56
up
10:56
and
10:57
play.
10:57
Entirely
10:58
new.
10:58
Because
10:58
it,
10:59
it's
10:59
a
10:59
different
10:59
way
11:00
of
11:00
doing
11:00
E
11:00
commerce.
11:01
I
11:01
don't
11:01
know.
11:01
It
11:01
totally
11:02
is.
11:02
But,
11:02
but
11:02
I,
11:03
but
11:03
answer
11:03
the
11:04
question.
11:04
Who
11:04
would
11:04
you
11:04
rather
11:05
order
11:05
from
11:05
Amazon
11:05
or
11:06
team?
11:06
As
11:07
a
11:07
US
11:07
Consumer?
11:08
Probably
11:08
Amazon.
11:09
Yeah,
11:09
I
11:09
think,
11:09
I
11:09
think
11:10
that
11:10
I
11:10
would
11:10
concede
11:11
to
11:11
you.
11:11
I
11:11
would
11:11
agree
11:12
if,
11:12
if
11:13
all
11:13
things
11:13
are
11:13
equal,
11:14
like
11:14
price
11:15
is
11:15
comparable.
11:17
You.
11:17
I
11:17
mean
11:18
everything
11:18
else,
11:18
the
11:18
quality
11:19
of
11:19
the
11:19
product,
11:19
it
11:20
looks
11:20
the
11:20
same.
11:20
The
11:20
images
11:21
are
11:21
the
11:21
same.
11:22
I
11:22
would
11:22
also
11:22
go
11:22
with
11:23
Amazon
11:23
and
11:23
my
11:23
hunch
11:23
is
11:24
there's
11:24
a
11:24
lot
11:24
of
11:24
people
11:25
in
11:25
the
11:25
US
11:25
that
11:25
would
11:26
also
11:26
go
11:26
to
11:26
Amazon
11:27
before
11:27
ordering
11:28
something
11:28
from
11:29
Temu
11:29
or
11:30
from
11:30
Shein
11:30
if
11:30
it's
11:31
the
11:31
same
11:31
thing.
11:32
So
11:32
you
11:32
make
11:32
a
11:32
great
11:33
point.
11:33
I
11:33
think
11:33
about
11:34
making
11:34
sure
11:34
that
11:34
the
11:34
gamification
11:35
and
11:35
the
11:35
shopping
11:36
experience
11:36
is
11:36
there,
11:37
but
11:37
I
11:37
think
11:37
if
11:37
they
11:38
can
11:38
do
11:38
it,
11:39
there's
11:39
a
11:39
huge
11:40
opportunity
11:40
in
11:40
the
11:40
US
11:41
for
11:41
them.
11:42
Yeah.
11:42
The
11:42
other
11:43
part
11:43
about
11:43
this
11:43
though
11:43
you
11:43
got
11:43
me
11:44
think
11:44
about
11:44
is
11:44
seller
11:44
ratings
11:45
are
11:45
also
11:45
really
11:45
important
11:46
on
11:46
Amazon
11:47
and
11:47
so
11:47
Amazon's
11:47
always
11:47
very
11:48
transparent
11:48
of
11:48
that.
11:48
So
11:49
like,
11:49
if
11:49
customers
11:49
start
11:50
to
11:50
get
11:50
dissatisfied
11:51
with
11:51
that,
11:51
Amazon's
11:52
going
11:52
to
11:52
probably
11:52
showcase
11:53
that
11:53
a
11:53
little
11:54
bit
11:54
more
11:54
too.
11:54
So.
11:55
So
11:55
yeah,
11:55
this
11:56
is
11:56
a
11:56
really
11:56
great
11:56
conversation.
11:57
I
11:57
have
11:57
no
11:57
idea
11:57
which
11:58
way
11:58
it's
11:58
going
11:58
to
11:58
play,
11:58
but
11:59
you
11:59
can
11:59
tell
11:59
that
12:00
Amazon
12:00
is
12:00
definitely,
12:01
definitely
12:01
focused
12:02
on
12:02
trying
12:02
to
12:02
figure
12:03
this
12:03
out.
12:03
All
12:04
right,
12:04
headline
12:04
number
12:05
two
12:06
Seven
12:06
Eleven
12:07
plans
12:07
to
12:07
open
12:07
over
12:08
600
12:08
stores
12:09
under
12:09
a
12:09
new
12:10
design
12:10
by
12:10
2027,
12:11
according
12:11
to
12:12
Retail
12:12
Dive.
12:12
Seven
12:13
Eleven
12:13
is
12:14
planned
12:14
to
12:14
open
12:15
over
12:15
600
12:16
large
12:16
format
12:16
food
12:17
focused
12:17
convenience
12:17
stores
12:18
in
12:18
North
12:18
America
12:18
by
12:19
the
12:19
end
12:19
of
12:19
2027,
12:20
according
12:20
to
12:21
an
12:21
investor
12:21
presentation
12:22
posted
12:22
last
12:23
Thursday.
12:23
These
12:24
locations
12:24
will
12:24
showc
12:25
prototype
12:25
the
12:26
company
12:26
internally
12:26
calls
12:27
its
12:27
standard
12:28
its
12:28
new
12:29
Standard
12:29
stores.
12:30
They
12:31
are,
12:31
quote,
12:31
more
12:32
contemporary
12:32
facilities,
12:33
end
12:33
quote,
12:33
that
12:33
offer
12:34
quote,
12:34
a
12:34
large
12:35
product
12:35
assortment
12:35
and
12:36
expanded
12:36
food
12:37
and
12:37
beverage
12:37
offerings,
12:38
end
12:38
quote.
12:38
Compared
12:39
to
12:39
the
12:39
rest
12:39
of
12:39
its
12:40
stores,
12:41
Seven
12:41
Eleven's
12:41
new
12:42
standard
12:42
format
12:42
is
12:42
the
12:43
first
12:43
prototype
12:43
the
12:43
convenience
12:44
retailer
12:44
has
12:45
launched
12:45
since
12:45
it
12:45
rolled
12:45
out
12:46
its
12:46
Evolution
12:46
store
12:47
concept
12:47
in
12:47
March
12:47
2019.
12:49
Those
12:49
locations
12:50
featured
12:50
Seven
12:50
Elevens,
12:51
Mexican
12:52
QSR
12:52
Laredo
12:53
Taco,
12:54
as
12:54
well
12:54
as
12:55
made
12:55
to
12:55
order
12:55
specialty
12:56
beverages,
12:56
self
12:57
serve
12:57
specialty
12:58
coffee,
12:58
a
12:59
cold
12:59
treats
12:59
bar,
13:00
mobile
13:00
checkout
13:00
and
13:01
delivery
13:01
capabilities.
13:03
Seven
13:03
Eleven
13:03
CEO
13:04
and
13:04
Omnitalk
13:05
fan
13:06
Joseph
13:06
DiPinto
13:07
said
13:07
on
13:07
Thursday
13:08
that
13:08
Seven
13:08
Eleven
13:08
has,
13:08
quote,
13:09
leveraged
13:09
key
13:09
learnings
13:10
from
13:10
its
13:10
Evolution
13:11
stores
13:11
over
13:11
the
13:11
past
13:11
few
13:12
years
13:12
and
13:12
that
13:13
beyond
13:13
the
13:13
increased
13:13
food
13:13
and
13:14
beverage
13:14
offerings,
13:14
the
13:15
new
13:15
Standard
13:15
C
13:16
stores
13:16
feature,
13:16
quote,
13:17
many
13:17
of
13:17
the
13:17
same
13:17
elements
13:18
of
13:18
the
13:18
Evolution
13:19
stores
13:20
as
13:20
well
13:20
as
13:21
in
13:21
store
13:22
seating
13:22
and
13:22
electric
13:23
vehicle
13:23
charging
13:24
stations.
13:25
And
13:25
this
13:25
is
13:25
also
13:25
the
13:26
A
13:26
and
13:26
M
13:26
put
13:26
you
13:27
on
13:27
the
13:27
spot
13:27
question
13:28
this
13:28
week.
13:28
Oh
13:29
boy,
13:30
better
13:30
you
13:30
than
13:30
me
13:31
on
13:31
this
13:31
one.
13:31
All
13:31
right.
13:32
Will
13:32
Seven
13:33
Eleven's
13:33
new
13:34
format
13:34
be
13:34
the
13:34
move
13:35
the
13:35
convenience
13:35
store
13:35
industry
13:36
needs
13:36
to
13:36
lessen
13:37
Its
13:37
dependent
13:37
on
13:38
historically
13:38
declining
13:39
fuel
13:39
and
13:39
tobacco
13:39
volumes?
13:40
And
13:41
how
13:41
much
13:41
should
13:41
QSR
13:42
players
13:42
be
13:43
looking
13:43
over
13:43
their
13:43
shoulder
13:44
to
13:44
see
13:45
what
13:45
happens?
13:45
God,
13:46
they're
13:46
so
13:46
good.
13:47
They
13:47
are.
13:47
I
13:48
mean
13:48
this
13:48
reminds
13:48
me
13:49
of
13:49
like
13:49
when
13:49
we
13:50
left
13:50
the
13:50
nacs
13:50
the
13:51
national
13:51
association
13:51
of
13:52
Convenience
13:52
Stores
13:52
Conference
13:53
last
13:53
year,
13:53
Chris.
13:53
I
13:53
mean,
13:54
Chad
13:55
and
13:55
the
13:56
team
13:56
at
13:56
A
13:56
and
13:56
M
13:57
are
13:57
hitting
13:57
on
13:57
the
13:57
exact
13:58
question
13:58
that
13:58
I
13:58
think
13:59
was
13:59
on
13:59
top
13:59
of
13:59
everyone's
14:00
minds
14:01
when
14:01
we
14:01
left
14:01
that
14:02
show.
14:02
Because
14:03
these,
14:04
these
14:04
fueling
14:05
stations
14:05
are
14:06
definitely
14:06
doubling
14:06
down
14:07
on
14:08
these
14:08
QSR
14:09
concepts
14:09
and
14:09
really
14:09
making
14:10
that
14:10
their
14:10
growth
14:11
opportunity
14:11
to,
14:12
like,
14:12
make
14:12
sure
14:12
that
14:12
they
14:13
have
14:13
a
14:13
reason
14:14
for
14:14
you
14:14
to
14:14
come
14:14
to
14:15
their
14:15
location
14:16
time
14:16
and
14:16
time
14:17
again,
14:17
whether
14:17
you're
14:17
filling
14:18
up
14:18
with
14:18
gas
14:18
or
14:19
it's
14:19
just
14:19
the
14:19
most
14:19
convenient
14:20
option.
14:20
So,
14:21
I
14:21
mean,
14:21
I'm
14:21
really.
14:22
I
14:22
think
14:22
this
14:22
story
14:23
is
14:23
important,
14:23
and
14:23
I'm
14:23
really
14:24
going
14:24
based
14:24
off
14:24
of
14:24
what
14:25
we
14:25
saw
14:25
five
14:26
years
14:26
ago,
14:26
Chris.
14:27
We
14:27
went
14:27
to
14:27
this
14:27
Evolution
14:28
store
14:28
in
14:28
Dallas
14:29
five
14:29
years
14:30
ago.
14:30
They
14:30
have
14:30
five
14:30
years
14:31
of
14:31
learning
14:32
that
14:32
they've
14:32
put
14:32
into
14:33
these
14:33
new
14:33
concepts,
14:34
and
14:34
they're
14:34
scaling
14:35
this
14:35
to
14:35
600
14:36
stores.
14:36
So
14:37
I
14:37
think
14:37
it's
14:37
absolutely
14:38
something
14:38
that
14:38
the
14:39
convenience
14:39
and
14:39
QSR
14:40
industries
14:40
need
14:41
to
14:41
be
14:41
paying
14:41
attention
14:41
to.
14:42
I
14:42
mean,
14:42
they
14:43
are
14:43
making
14:43
massive
14:44
investments
14:44
here.
14:45
We
14:45
are
14:45
seeing
14:46
investments
14:46
in
14:46
like,
14:47
full
14:47
kitchen
14:48
buildouts
14:48
to
14:48
support
14:48
the
14:49
Laredo
14:49
Tacos.
14:50
They
14:50
are
14:50
putting
14:51
in
14:51
new
14:51
fixturing
14:52
and
14:52
infrastructure
14:53
to
14:53
support
14:53
things
14:54
like
14:54
mobile
14:55
checkout
14:55
and
14:55
scan
14:55
and
14:56
go
14:56
and
14:56
in
14:56
the
14:56
future,
14:57
possibly
14:57
even
14:58
entry
14:58
and
14:58
exit
14:59
that
14:59
would
14:59
be
14:59
controlled.
15:00
They're
15:00
doing,
15:01
you
15:01
know,
15:01
setting
15:02
up
15:02
better
15:02
throughput
15:03
for
15:03
the
15:03
delivery
15:03
of
15:03
fresh
15:04
food
15:04
items
15:04
and
15:04
then
15:05
the
15:05
supplies
15:05
for
15:05
the
15:06
restaurant.
15:06
And
15:06
then
15:06
finally
15:07
they
15:07
have
15:08
to
15:08
really
15:08
be
15:08
thinking,
15:08
and
15:09
they
15:09
did
15:09
in
15:09
the
15:09
store
15:09
that
15:10
we
15:10
visited
15:10
in
15:10
Dallas,
15:11
about
15:11
accommodating
15:12
seating
15:13
and
15:14
an
15:14
environment
15:14
where
15:15
people
15:15
can
15:15
stay.
15:15
Now
15:16
that
15:16
EV
15:16
chargers
15:17
are
15:17
a
15:17
component
15:17
of
15:17
this,
15:18
and
15:18
we're
15:18
really
15:18
not
15:19
seeing
15:19
that
15:19
with
15:19
many
15:20
other
15:20
C
15:21
store
15:21
retailers
15:21
yet,
15:22
with
15:22
the
15:22
exception
15:22
of
15:22
maybe
15:23
Gelson's
15:23
that's
15:23
piloting
15:24
this
15:24
out
15:24
in
15:25
California.
15:26
But
15:26
I
15:27
think
15:27
that
15:27
what
15:28
this
15:28
investment,
15:29
the
15:29
pure
15:29
investment
15:30
that
15:30
seven
15:30
Eleven
15:31
is
15:31
making
15:31
here
15:31
is
15:32
a
15:32
reason
15:32
for
15:32
us
15:32
to
15:33
be
15:33
paying
15:33
attention
15:33
to
15:33
this,
15:34
both
15:34
in
15:35
the
15:35
C
15:35
store
15:35
space
15:36
and
15:36
in
15:36
the
15:36
QSR
15:37
space,
15:37
because
15:37
I
15:37
think
15:37
that
15:38
there's
15:38
a
15:38
lot
15:38
of
15:38
room
15:39
and
15:39
seven
15:39
Eleven
15:40
is
15:40
betting
15:41
on
15:41
this
15:41
being
15:41
their
15:42
growth
15:42
engine
15:42
for
15:42
the
15:43
future.
15:43
But
15:44
where
15:44
do
15:44
you
15:44
land?
15:45
I
15:45
mean,
15:45
what
15:45
were
15:45
your
15:45
thoughts
15:46
when
15:46
we
15:46
were
15:46
in
15:46
that
15:46
store
15:47
in
15:47
Dallas?
15:47
Yeah,
15:48
I
15:48
think
15:48
my
15:48
thoughts
15:48
are
15:49
similar.
15:49
And
15:49
honestly,
15:50
I'm
15:50
dying
15:50
to
15:50
ask
15:51
Chad
15:51
Lusk,
15:51
who
15:52
potentially
15:52
is
15:52
the
15:52
originator
15:53
of
15:53
this
15:53
A
15:53
and
15:54
M
15:54
question
15:54
and
15:54
a
15:54
former
15:55
C
15:55
store
15:55
operator,
15:55
what
15:56
his
15:56
take
15:56
is
15:56
on
15:56
his
15:57
question.
15:57
But,
15:57
you
15:58
know,
15:58
I
15:58
think
15:58
it's
15:59
something
15:59
that
15:59
everyone
16:00
has
16:00
to
16:00
be
16:00
paying
16:00
attention
16:01
to.
16:01
And
16:01
the
16:02
key,
16:02
the
16:02
reason
16:02
I
16:02
say
16:03
that
16:03
is
16:03
I
16:03
think
16:03
the
16:04
key
16:04
here
16:04
lies
16:05
in
16:05
the
16:05
names
16:05
that
16:06
711
16:06
is
16:06
using
16:07
they're
16:08
going
16:08
from
16:08
evolution,
16:09
taking
16:10
the
16:10
lessons
16:10
learned
16:11
from
16:11
that.
16:11
Which,
16:11
by
16:11
the
16:11
way,
16:11
learnings
16:12
is
16:12
not
16:12
a
16:12
word.
16:12
I
16:12
hate
16:13
when
16:13
people
16:13
say
16:13
that.
16:13
It's
16:13
lessons.
16:14
Sorry,
16:14
Learning.
16:15
No,
16:15
it
16:15
wasn't
16:16
you.
16:16
It
16:16
was
16:16
in
16:16
the
16:16
article.
16:17
The
16:17
article
16:17
said
16:17
learnings.
16:19
And
16:19
then
16:19
we
16:19
all
16:19
do
16:19
it.
16:20
I
16:20
do
16:20
it
16:20
all
16:20
the
16:20
time,
16:20
too.
16:21
So
16:21
it's
16:21
no
16:21
big
16:21
deal,
16:21
but
16:21
it's
16:21
just
16:22
a
16:22
little
16:22
pet
16:22
peeve
16:22
of
16:22
mine.
16:23
But
16:23
they're
16:23
taking
16:23
the
16:24
lessons
16:24
learned
16:24
from
16:25
that
16:25
and
16:25
now
16:25
calling
16:26
this
16:26
new
16:26
format
16:27
the
16:27
new
16:27
standard,
16:28
which
16:29
tells
16:29
me
16:29
this
16:29
store
16:30
is
16:30
actually
16:30
just
16:30
an
16:31
evolution
16:31
against
16:32
the
16:32
trends
16:33
711
16:33
is
16:33
seeing,
16:34
like
16:34
what
16:34
you
16:34
named,
16:34
like,
16:35
EV
16:35
charging,
16:36
expanded
16:36
food
16:37
and
16:37
beverage
16:37
offerings,
16:37
which,
16:38
as
16:38
you
16:38
said,
16:38
we
16:38
heard
16:38
it.
16:38
Next
16:39
we
16:39
shot
16:40
a
16:40
video
16:40
of
16:40
their
16:40
evolution
16:41
store.
16:41
It
16:41
was
16:41
really
16:42
impressive.
16:42
We'll
16:42
try
16:42
to
16:42
include
16:43
it
16:43
in
16:43
the
16:43
show
16:43
notes
16:43
as
16:44
well.
16:44
But.
16:45
And
16:45
the
16:45
other
16:46
point
16:46
that
16:46
I'd
16:46
make
16:47
is
16:47
it
16:48
seems
16:48
like
16:48
the
16:48
right
16:49
way
16:49
to
16:49
experiment
16:50
when
16:50
you're
16:50
talking
16:50
about
16:51
retail.
16:51
Physical
16:52
footprints,
16:53
design
16:53
big
16:54
and
16:54
bold
16:55
and
16:55
then
16:55
work
16:56
backwards.
16:56
Which
16:57
is
16:57
an
16:57
interesting
16:57
approach
16:58
when
16:58
you
16:58
compare
16:58
it.
16:58
In
16:59
contrast
16:59
to,
16:59
like,
17:00
how
17:00
Wayfair
17:00
tried
17:01
to
17:01
experiment
17:01
with
17:01
their
17:02
stores,
17:02
how
17:02
Amazon's
17:03
been
17:03
trying
17:03
to
17:03
experiment
17:04
with
17:04
their
17:04
stores
17:04
in
17:05
grocery.
17:05
I
17:06
actually
17:06
like
17:06
this
17:06
approach
17:07
a
17:07
lot
17:07
better
17:07
because
17:08
you
17:08
spend
17:08
a
17:08
little
17:08
bit
17:08
more
17:09
upfront,
17:09
but
17:09
you
17:10
get
17:10
better
17:10
answers
17:10
in
17:11
the
17:11
long
17:11
term
17:11
and
17:11
you
17:11
see
17:12
what's
17:12
possible.
17:13
So.
17:14
And
17:14
then
17:14
the
17:14
other
17:14
point
17:14
about
17:15
this
17:15
is
17:15
they
17:16
must
17:16
have
17:16
the
17:16
confidence
17:17
that
17:17
it
17:17
works,
17:18
right?
17:18
They're
17:19
thinking
17:19
this
17:19
is
17:19
going
17:19
to
17:20
work
17:20
if
17:20
they're
17:20
going
17:20
out
17:21
publicly
17:21
and
17:21
saying
17:22
600
17:22
stores.
17:22
We're
17:22
going
17:23
to
17:23
build
17:23
600
17:23
stores
17:24
with
17:24
this
17:24
in
17:24
a
17:24
pretty
17:24
short
17:25
time
17:25
horizon,
17:25
too.
17:26
This
17:26
is
17:26
not
17:26
like
17:27
targets.
17:27
We're
17:27
going
17:27
to
17:27
build
17:28
X
17:28
number
17:28
of
17:28
stores
17:29
in
17:29
10
17:29
years
17:30
baloney
17:30
that
17:30
they're
17:31
putting
17:31
out
17:31
there.
17:31
So.
17:32
So
17:32
that.
17:33
That's
17:33
my
17:33
take,
17:33
I
17:33
think.
17:34
I
17:34
think
17:34
the
17:34
whole.
17:34
I
17:35
think
17:35
QSR
17:36
and
17:36
the
17:36
convenience
17:37
store
17:37
industry
17:37
both
17:37
have
17:38
to
17:38
take
17:38
a
17:38
close
17:38
look
17:38
at
17:39
this
17:39
to
17:39
see
17:39
how.
17:40
How
17:40
things
17:40
are
17:40
still
17:40
evolving.
17:41
Now
17:41
you
17:42
got
17:42
me
17:42
craving
17:42
a
17:42
Laredo
17:43
Taco,
17:43
Chris
17:44
early
17:44
in
17:44
the
17:45
radio.
17:46
Or
17:47
a
17:47
Del
17:47
Taco.
17:49
Oh,
17:49
God,
17:50
no.
17:51
Or
17:51
Jack
17:52
in
17:52
the
17:52
Box
17:52
Taco.
17:53
Oh,
17:53
my
17:54
God.
17:54
Now
17:54
you're
17:54
just
17:55
spouting
17:55
off
17:55
QSRs.
17:56
I
17:56
was,
17:56
like,
17:57
sticking
17:57
with
17:57
the
17:58
711
17:58
one.
17:58
Whatever
17:59
I
17:59
am,
17:59
I
17:59
am
18:00
a
18:00
big
18:00
QSR
18:01
fan.
18:01
Ed,
18:01
that
18:01
is.
18:02
You
18:02
know
18:02
that.
18:03
Oh,
18:03
my
18:03
God.
18:03
All
18:04
right,
18:04
headline
18:04
number
18:04
three.
18:05
Simby
18:05
has
18:06
raised
18:06
$50
18:07
million
18:07
in
18:08
its
18:08
latest
18:08
funding
18:08
round,
18:09
according
18:09
to
18:09
Grocery
18:10
Dive
18:10
Simbi,
18:10
the
18:10
robotics
18:11
company
18:11
whose
18:11
aisle
18:12
scanning
18:12
bots
18:12
are
18:13
in
18:13
several
18:13
U.S.
18:14
grocery
18:14
chains,
18:14
announced
18:15
last
18:15
Thursday.
18:15
It
18:16
has
18:16
raised
18:16
$50
18:17
million
18:17
in
18:17
a
18:17
Series
18:18
C
18:18
round
18:19
led
18:19
by
18:19
Growth
18:19
Equity
18:20
at
18:20
Goldman
18:20
Sachs.
18:21
The
18:21
robotics
18:22
company
18:22
said
18:22
it
18:22
plans
18:23
to
18:23
use
18:23
the
18:23
new
18:23
funding
18:24
to
18:24
expand
18:24
into
18:24
product
18:25
areas,
18:25
scale
18:26
its
18:26
solutions
18:26
with
18:27
global
18:27
deployments
18:28
and,
18:28
quote,
18:29
pursue
18:29
strategic
18:30
growth
18:31
opportunities,
18:31
end
18:32
quote.
18:32
The
18:32
company
18:33
also
18:33
plans
18:33
to
18:34
expand
18:34
its
18:34
team,
18:34
which
18:35
it
18:35
has
18:35
doubled
18:36
in
18:36
the
18:36
past
18:37
year.
18:38
Simby
18:38
noted
18:39
in
18:39
the
18:39
Thursday
18:39
announcement
18:40
that
18:40
it
18:40
unveiled
18:40
this
18:41
year
18:42
new
18:42
and
18:43
expanded
18:43
partnerships
18:44
with
18:44
retailers
18:44
including
18:44
Spartan,
18:45
Nash,
18:46
Shoprite,
18:46
Northeast
18:47
Grocery,
18:47
Care4and3
18:49
Albertsons
18:49
banners,
18:50
Market
18:50
Street,
18:51
United
18:51
Supermarkets
18:52
and
18:52
Albertsons
18:53
Market.
18:53
The
18:54
technology
18:54
company
18:54
also
18:55
counts
18:55
BJ
18:55
Whole,
18:56
BJ's
18:56
Wholesale
18:57
Club
18:57
and
18:57
Schnook
18:57
Markets
18:58
among
18:58
its
18:59
current
18:59
clients.
18:59
Chris,
19:00
what
19:00
do
19:00
you
19:00
think
19:00
that
19:01
Simby's
19:01
$50
19:02
million
19:02
Series
19:02
C
19:03
signals
19:03
about
19:04
the
19:04
trajectory
19:04
of
19:05
retail
19:05
technology
19:06
investments?
19:07
Man,
19:08
and
19:08
I
19:08
love
19:09
this
19:09
headline.
19:10
This
19:10
is
19:10
one
19:10
where
19:10
we
19:10
were
19:10
like
19:11
unanimous
19:11
on
19:12
this
19:12
week.
19:12
You
19:12
know,
19:12
which,
19:12
you
19:13
know,
19:13
which
19:13
tends,
19:14
which
19:14
tends
19:14
to
19:14
happen.
19:14
There's
19:14
usually
19:15
two
19:15
or
19:15
three
19:15
a
19:15
week
19:15
like
19:15
that.
19:16
But,
19:16
but
19:16
I
19:16
love
19:17
this,
19:17
I
19:17
love
19:17
this
19:17
announcement
19:18
because
19:19
it
19:19
tells
19:19
all
19:19
of
19:20
our
19:20
listeners,
19:20
like,
19:20
why
19:21
you
19:21
should
19:21
listen
19:21
and
19:21
tune
19:22
into
19:22
us
19:22
each
19:22
week
19:22
because
19:23
we
19:23
are
19:23
trying
19:23
to
19:23
stay
19:24
on
19:24
top
19:24
of
19:24
the
19:24
trends.
19:24
We
19:25
are
19:25
trying
19:25
to
19:25
predict
19:26
where
19:27
things
19:27
are
19:27
going.
19:27
And
19:28
I
19:28
feel
19:28
like
19:28
we
19:28
had,
19:28
we,
19:29
you
19:29
know,
19:29
we
19:29
had
19:29
some
19:29
insight,
19:30
insight
19:30
into
19:30
this
19:30
based
19:31
on
19:31
the
19:31
retailers
19:32
we're
19:32
talking
19:32
to
19:33
regularly,
19:34
because
19:34
I
19:34
think
19:35
it
19:35
shines
19:35
light
19:35
on
19:36
what
19:36
we've
19:36
been
19:36
saying
19:37
for
19:37
the
19:37
past
19:38
few
19:38
years
19:38
now.
19:38
And
19:38
it's
19:39
very
19:39
validating
19:39
of
19:40
our
19:40
overall
19:40
thesis
19:41
that
19:41
money,
19:42
number
19:42
one,
19:42
money
19:43
is
19:43
still
19:43
flowing
19:44
to
19:44
tech
19:44
that
19:45
will
19:45
show
19:45
a
19:45
return.
19:46
Because
19:47
what's
19:47
the
19:47
one
19:47
thing,
19:48
what's
19:48
the
19:48
one
19:48
thing
19:48
the
19:48
grocers
19:49
have
19:49
told
19:49
us
19:49
that
19:49
have
19:50
deployed
19:50
the
19:50
robots?
19:50
And
19:51
what's
19:51
the
19:51
one
19:52
thing
19:52
they've
19:52
all.
19:52
Said
19:53
they
19:53
won't
19:54
let
19:54
them
19:55
go.
19:55
Like
19:55
they're
19:55
just
19:56
a
19:56
part
19:56
of
19:56
the
19:57
whole
19:57
team
19:58
at
19:58
the
19:58
grocery
19:58
store.
19:59
Like,
19:59
no
19:59
one
19:59
wants
19:59
them
19:59
to
20:00
walk.
20:00
Out
20:00
of
20:00
the
20:00
door
20:01
100%.
20:02
Like
20:02
they
20:02
basically
20:02
say.
20:03
They
20:03
basically
20:03
say
20:03
to
20:03
us
20:03
every
20:04
time
20:04
we
20:04
ask
20:04
them,
20:04
you
20:04
can
20:05
take
20:05
anything
20:05
you
20:05
want,
20:06
but
20:06
you
20:06
cannot
20:07
take
20:07
my
20:07
robot.
20:08
And
20:08
that's
20:08
pretty
20:09
telling.
20:09
And
20:09
the
20:09
reason
20:09
is
20:10
because
20:10
they
20:10
work,
20:11
you
20:11
get
20:11
inventory,
20:12
you
20:12
get
20:12
pricing
20:12
accuracy,
20:13
you
20:13
get
20:13
planogram
20:14
compliance,
20:14
plus
20:14
you
20:15
get
20:15
all
20:15
the
20:15
operational
20:16
offshoots
20:16
you
20:16
can
20:16
when
20:17
you
20:17
combine
20:17
them
20:17
with
20:17
ESLs.
20:18
So
20:19
the
20:19
industry
20:19
is
20:20
seeing
20:20
it,
20:20
which
20:21
is
20:21
again,
20:21
why
20:22
I
20:22
think
20:22
all
20:22
signs
20:23
point
20:23
to
20:23
2025
20:24
being
20:24
the
20:24
year
20:25
of
20:25
the
20:25
robot.
20:26
And
20:26
by
20:26
that
20:26
I
20:26
mean
20:27
the
20:27
reach
20:27
of
20:27
the
20:27
robot
20:28
not
20:28
just
20:28
continuing
20:29
in
20:29
grocery,
20:29
but
20:29
starting
20:30
to
20:30
extend
20:30
deeper
20:31
like
20:31
traditional
20:32
grocery,
20:32
but
20:32
starting
20:32
to
20:32
extend
20:33
deeper
20:33
into
20:33
other
20:34
verticals
20:34
in
20:34
retail
20:35
as
20:35
well.
20:35
And
20:35
Goldman
20:36
Sachs
20:36
alternatives
20:37
seems
20:38
like
20:38
they
20:38
tend
20:38
to
20:38
agree
20:39
with
20:39
that
20:39
sentiment,
20:39
at
20:39
least
20:40
from
20:40
this,
20:40
from
20:40
the
20:41
size
20:41
of
20:41
the
20:42
investment
20:42
here
20:42
and
20:42
the
20:42
round.
20:43
Yes.
20:43
And
20:44
Simby's
20:45
strategic
20:45
growth
20:46
opportunities
20:47
that
20:47
they're
20:47
working
20:47
on.
20:48
We'll
20:48
be
20:48
excited
20:49
to
20:49
see
20:49
what,
20:50
what
20:50
kind
20:50
of
20:51
retailers
20:51
they
20:51
land
20:52
in
20:52
next.
20:52
And
20:52
yeah,
20:53
I
20:53
don't
20:53
have
20:53
much
20:53
to
20:53
add,
20:54
Chris.
20:54
I
20:54
mean,
20:54
I
20:54
think
20:55
anecdotally,
20:56
I
20:56
will
20:57
say
20:57
that
20:57
since
20:57
we
20:58
released
20:58
that
20:58
Schnooks
20:59
video
21:00
with
21:00
the
21:00
robot
21:01
last
21:01
year
21:01
about
21:02
this
21:02
time,
21:02
and
21:03
even
21:03
just
21:03
after
21:04
talking
21:04
to
21:04
the
21:04
Schnooks
21:05
team
21:05
and
21:06
I'm
21:06
still
21:06
getting
21:07
emails
21:07
and
21:07
direct
21:08
messages
21:08
via
21:08
LinkedIn
21:09
today
21:10
where
21:10
people
21:10
are
21:11
asking
21:11
to
21:11
get
21:11
connected
21:12
with
21:12
them
21:12
from
21:13
other
21:13
retailers
21:14
so
21:14
that
21:14
they
21:14
can
21:14
find
21:15
out
21:15
more
21:15
about
21:16
why,
21:16
like
21:16
the
21:17
why
21:17
and
21:17
the
21:17
how
21:18
related
21:18
to
21:18
the
21:18
robots.
21:19
Because
21:19
this
21:19
is
21:19
an
21:20
area
21:20
that
21:20
people
21:21
are
21:21
seriously
21:22
considering
21:22
and
21:23
seriously
21:23
investing
21:24
money
21:24
in
21:24
right
21:24
now,
21:25
like
21:25
you
21:25
said.
21:26
Yeah,
21:26
and
21:26
we
21:26
got
21:26
it.
21:27
We
21:27
got
21:27
to
21:27
talk
21:27
to
21:27
like
21:27
BJ's
21:28
too,
21:28
and
21:28
see
21:28
how
21:28
they're
21:29
working
21:29
this
21:29
thing,
21:29
see
21:30
how
21:30
they're
21:30
doing
21:30
the
21:30
robot
21:31
too,
21:31
now
21:31
that
21:31
I
21:31
think
21:31
about
21:31
it.
21:31
We
21:32
got
21:32
to
21:32
get
21:32
on
21:32
the
21:32
horn
21:32
with
21:32
them
21:32
and
21:33
see
21:33
what
21:33
they're
21:33
learning
21:34
from
21:34
this
21:34
as
21:34
well.
21:35
All
21:35
right,
21:36
now
21:36
let's
21:37
take
21:37
a
21:37
break
21:38
and
21:38
welcome
21:39
Doug
21:39
to
21:39
the
21:40
show.
21:40
ANN
21:41
Joining
21:42
us
21:42
now
21:42
for
21:42
five
21:42
insightful
21:43
minutes
21:43
is
21:43
Doug
21:44
Tiffin.
21:44
Doug
21:45
is
21:45
the
21:45
head
21:45
of
21:45
solutions
21:46
strategy
21:46
for
21:47
fashion
21:47
and
21:47
apparel
21:48
at
21:48
Amazon
21:48
Web
21:49
Services.
21:50
Doug,
21:50
first
21:50
question,
21:51
what
21:51
is
21:51
taking
21:52
place
21:52
in
21:52
the
21:53
fashion
21:53
and
21:53
apparel
21:54
space
21:54
right
21:54
now?
21:55
And
21:55
how
21:55
are
21:55
you
21:56
seeing
21:56
retailers
21:56
invest
21:57
in
21:57
cloud
21:57
technologies?
21:59
So
22:00
the
22:00
rapid
22:01
growth
22:01
of
22:01
E
22:01
commerce
22:02
that
22:02
was
22:02
spurred
22:02
by
22:02
the
22:03
pandemic
22:03
is
22:03
mostly
22:04
stabilized
22:04
right
22:05
now.
22:05
But
22:06
what
22:06
has
22:06
changed
22:07
is
22:07
consumer
22:08
behavior
22:08
and
22:08
I
22:09
believe
22:09
it's
22:09
going
22:09
to
22:09
continue
22:10
to
22:10
change.
22:10
And
22:11
the
22:11
expectations
22:12
now
22:13
are
22:13
kind
22:13
of
22:13
higher
22:14
than
22:14
level
22:15
for
22:16
the
22:16
retailers
22:17
and
22:17
brands.
22:18
So
22:19
customers
22:20
today,
22:20
they're,
22:20
they're
22:20
less
22:21
loyal
22:21
to
22:21
brands
22:22
and
22:22
they're
22:22
expecting
22:23
great
22:23
shopping
22:24
experiences
22:24
that
22:24
are
22:25
connected
22:26
no
22:26
matter
22:26
where
22:27
they
22:27
interact
22:27
with
22:27
the
22:27
retailer,
22:28
whether
22:28
it
22:28
be
22:29
online
22:29
or
22:30
in
22:30
an
22:30
app,
22:31
in
22:31
the
22:31
store
22:31
or
22:32
in
22:32
social
22:32
media.
22:34
So
22:34
retailers
22:35
must
22:36
rapidly
22:36
adapt
22:36
and
22:37
change
22:37
investing
22:38
in
22:38
technology
22:38
to
22:39
meet
22:39
their
22:40
customers,
22:40
changing
22:41
expectations.
22:42
So
22:42
this
22:42
includes
22:43
investing
22:43
in
22:43
AI
22:44
and
22:44
cloud
22:44
technologies
22:45
that
22:45
power
22:45
better
22:46
shopping
22:46
experiences
22:47
like
22:48
personalization
22:49
or
22:50
improving
22:50
business
22:51
processes
22:52
like
22:52
leveraging
22:53
AI
22:53
to
22:53
create
22:53
product
22:54
images
22:54
or
22:55
product
22:55
descriptions
22:57
and
22:57
then
22:58
using
22:58
AI
22:59
to
22:59
create
22:59
the
22:59
next
23:00
level
23:00
of
23:00
customer
23:01
services
23:01
that
23:02
involve
23:02
all
23:02
these
23:03
things
23:03
before
23:03
personalization,
23:04
product
23:05
data,
23:05
all
23:05
into
23:05
one
23:06
great
23:06
customer
23:07
experience.
23:08
Doug
23:09
Inflation
23:09
has
23:09
eased.
23:10
Certainly
23:10
the
23:11
industry
23:11
has
23:11
not
23:12
yet
23:12
recovered
23:13
though
23:13
to
23:13
pre
23:14
pandemic
23:14
levels.
23:14
For
23:14
example,
23:15
we're
23:15
seeing
23:15
supply
23:16
chain
23:16
disruptions,
23:17
high
23:17
interest
23:18
rates,
23:18
geopolitical
23:19
uncertainties
23:19
and
23:20
all
23:20
this
23:20
may
23:20
lead
23:21
executives
23:21
to
23:21
be
23:21
a
23:21
little
23:21
bit
23:22
more
23:22
cautious
23:22
about
23:22
their
23:23
technology
23:23
investments.
23:24
So
23:24
I'm
23:24
curious,
23:25
what
23:25
AI
23:25
investments
23:26
you
23:26
think
23:26
are
23:26
going
23:26
to
23:27
have
23:27
the
23:27
biggest
23:27
impact
23:28
on
23:28
profitability
23:28
and
23:29
customer
23:29
loyalty
23:30
within
23:30
the
23:30
fashion
23:31
and
23:31
apparel
23:31
space?
23:32
Yeah,
23:33
fashion
23:33
brands
23:34
and
23:34
retailers
23:34
are
23:35
concerned
23:35
about
23:36
customer
23:36
acquisition,
23:37
but
23:37
mostly
23:37
about
23:38
customer
23:38
retention.
23:39
They're
23:39
constant
23:40
things
23:41
like
23:41
personalization
23:42
and
23:44
enhancing
23:45
digital
23:45
engagement,
23:46
next
23:46
level
23:47
customer
23:47
service,
23:48
all
23:48
with
23:48
the
23:49
intent
23:49
of
23:49
creating
23:50
delightful
23:51
shopping
23:51
experiences.
23:52
So
23:53
the
23:53
AI
23:53
behind
23:54
that
23:54
can
23:55
be
23:55
in
23:55
things
23:55
like
23:55
personalization.
23:56
For
23:56
example,
23:57
AI
23:58
can
23:58
understand
24:00
vast
24:00
amounts
24:01
of
24:01
data
24:01
like
24:02
shopping
24:02
history,
24:03
browsing
24:04
history,
24:04
and
24:04
pull
24:05
all
24:05
that
24:05
together
24:06
to
24:06
give
24:06
relevant
24:07
product
24:07
recommendations
24:08
in
24:09
session
24:09
for
24:09
each
24:10
customer
24:10
as
24:10
they
24:10
shop.
24:11
Personalization
24:12
can
24:12
even
24:12
reach
24:13
into
24:13
marketing.
24:14
And
24:14
instead
24:14
of
24:15
marketing
24:15
to
24:16
giant
24:16
segments
24:17
like
24:17
we've
24:17
done
24:17
in
24:17
the
24:17
past,
24:18
we
24:18
can
24:18
literally
24:18
cater
24:19
marketing
24:19
messaging
24:20
to
24:20
the
24:20
individual.
24:21
Another
24:22
area
24:23
that
24:23
I
24:23
see
24:24
investment
24:24
in
24:24
is
24:24
product
24:25
search
24:25
and
24:25
discovery.
24:26
60%
24:26
of,
24:27
yeah,
24:28
60%
24:28
of
24:29
shoppers
24:29
will
24:29
go
24:29
straight
24:30
to
24:30
the
24:30
search
24:30
bar
24:30
when
24:31
they
24:31
hit
24:31
a
24:31
retailer
24:31
site.
24:32
And
24:32
if
24:32
they
24:33
don't
24:33
find
24:33
what
24:33
they're
24:33
looking
24:33
for
24:34
within
24:34
a
24:34
few
24:34
clicks,
24:35
80%
24:35
of
24:35
the
24:35
time
24:35
they're
24:36
going
24:36
to
24:36
bolt
24:36
for
24:36
another
24:36
website.
24:37
So
24:38
AI
24:39
technologies
24:39
can
24:40
help
24:41
by
24:41
letting
24:42
customers
24:43
search
24:43
by
24:43
using
24:44
product
24:44
images
24:45
and
24:45
statements
24:46
instead
24:46
of
24:46
just
24:46
keywords.
24:47
They
24:47
can
24:48
ask
24:48
a
24:48
question
24:48
and
24:49
AI
24:49
can
24:49
identify
24:50
items
24:51
in
24:51
that
24:51
retailer's
24:52
assortment
24:52
that
24:53
meet
24:53
the
24:53
need
24:53
of
24:53
that
24:54
consumer
24:55
and
24:55
then
24:56
give
24:56
them
24:56
that
24:56
offering.
24:57
Shoppers
24:58
can
24:58
find
24:58
exactly
24:58
what
24:59
they're
24:59
looking
24:59
for
25:00
and
25:00
then
25:01
walk
25:01
away
25:01
with
25:01
a
25:02
great
25:02
customer
25:02
experience.
25:03
And
25:03
then
25:04
finally,
25:04
the
25:04
last
25:04
place
25:05
I
25:05
see,
25:05
AI
25:05
investments
25:06
are
25:06
really
25:06
in
25:06
the
25:07
customer
25:07
service
25:07
space.
25:08
So
25:08
AI
25:09
powered
25:09
chatbots
25:10
can
25:10
offer
25:10
24
25:11
hours
25:12
customer
25:13
help
25:14
and
25:15
customers
25:15
can
25:16
come
25:16
in
25:16
and
25:17
the
25:17
AI
25:18
can
25:18
understand
25:18
their
25:18
intent
25:19
and
25:19
give
25:20
them
25:20
the
25:20
answers
25:20
they
25:20
need
25:21
to
25:21
get
25:21
to
25:21
what
25:21
they're
25:21
looking
25:22
for.
25:22
That
25:22
would
25:22
be
25:22
help
25:22
with
25:23
a
25:23
problem
25:23
or
25:24
finding
25:24
a
25:24
product.
25:25
And
25:25
another
25:25
version
25:26
of
25:26
a
25:27
AI
25:28
chatbot
25:28
is
25:28
personal
25:29
stylus
25:29
that
25:29
I
25:29
see
25:30
happening
25:30
a
25:30
lot
25:30
where
25:31
either
25:32
in
25:32
an
25:32
app
25:32
or
25:32
in
25:32
a
25:33
website,
25:33
a
25:33
customer
25:33
go
25:34
in
25:34
and
25:34
ask
25:35
questions
25:35
on
25:35
like
25:35
what
25:35
to
25:36
wear.
25:36
Like,
25:36
for
25:36
example,
25:37
you
25:37
know,
25:37
if
25:37
you
25:37
want
25:38
to
25:38
find
25:38
a
25:38
dress
25:38
for
25:38
New
25:39
Year's
25:39
Eve
25:39
in
25:39
Manhattan,
25:40
which
25:40
I
25:40
buy
25:40
in,
25:40
AI
25:41
can
25:42
not
25:42
only
25:42
give
25:42
you
25:42
the
25:42
dress,
25:43
but
25:43
also
25:43
round
25:43
it
25:43
out
25:44
with
25:44
the
25:44
handbag
25:45
and
25:45
the
25:45
shoes
25:45
to
25:46
go
25:46
with
25:46
it.
25:46
So
25:46
let's
25:46
get
25:47
you
25:47
out
25:47
of
25:47
here
25:47
on
25:47
this.
25:48
If
25:48
we
25:48
consider
25:48
a
25:48
long
25:49
term
25:49
or
25:49
take
25:49
a
25:49
longer
25:50
term
25:50
view,
25:51
what
25:51
do
25:51
retailers
25:51
need
25:52
to
25:52
take
25:52
action
25:52
on
25:53
now
25:53
to
25:53
drive
25:54
more
25:54
value
25:55
in
25:55
the
25:55
future?
25:55
Right
25:56
now,
25:56
right
25:56
this
25:56
second,
25:57
Doug,
25:57
what
25:57
would
25:57
you
25:57
tell
25:58
retailers?
25:59
Top
25:59
of
25:59
my
25:59
mind
26:00
is
26:00
develop
26:01
and
26:01
enforce
26:01
a
26:02
complete
26:02
data
26:03
strategy.
26:03
All
26:03
the
26:04
cool
26:04
AI
26:04
in
26:04
the
26:05
world
26:05
won't
26:06
help
26:06
you
26:06
if
26:06
the
26:06
foundational
26:07
data
26:07
is
26:08
not
26:08
in
26:08
good
26:08
shape.
26:09
The
26:09
second
26:09
thing
26:09
would
26:10
be
26:10
take
26:11
your
26:11
vision
26:11
for
26:12
a
26:12
differentiated
26:13
customer
26:13
experience
26:13
and
26:13
invest
26:14
in
26:14
the
26:14
technology
26:15
that
26:15
you
26:16
need
26:16
to
26:16
support
26:16
that
26:17
vision.
26:18
Anticipate
26:18
that
26:19
your
26:19
customers
26:20
demands
26:20
and
26:21
expectations
26:22
are
26:22
going
26:22
to
26:22
continue
26:23
to
26:23
change
26:24
and
26:24
so
26:24
you
26:25
want
26:25
to
26:25
make
26:25
sure
26:25
that
26:25
you're
26:26
positioned
26:26
to
26:26
be
26:26
able
26:26
to
26:27
meet
26:27
those
26:27
changes.
26:29
And
26:29
then
26:30
also
26:30
think
26:30
of
26:30
AI
26:31
as
26:31
a
26:31
member
26:32
of
26:32
your
26:32
team.
26:32
There
26:32
are
26:33
highly
26:33
potential
26:34
a
26:35
team
26:35
member
26:35
that
26:35
is
26:36
capable
26:36
of
26:36
great
26:36
things,
26:37
but
26:37
they
26:38
need
26:38
time
26:38
and
26:38
training
26:38
to
26:39
get
26:39
up
26:39
to
26:39
speed.
26:39
So
26:40
start
26:40
now.
26:42
You
26:42
know,
26:42
if
26:42
your
26:43
team
26:43
is
26:43
new
26:43
to
26:43
AI,
26:44
get
26:44
them
26:44
started
26:44
on
26:45
internal
26:45
projects,
26:46
then
26:46
some
26:46
short
26:46
ones
26:47
to
26:47
get
26:47
some
26:47
quick
26:47
wins
26:48
and
26:48
build
26:48
that
26:48
muscle
26:49
memory
26:49
so
26:49
then
26:50
they
26:50
can
26:50
turn
26:50
around
26:51
and
26:51
work
26:51
on
26:51
some
26:51
longer
26:52
term
26:52
strategic
26:53
projects
26:53
that
26:53
could
26:53
really
26:54
deliver
26:54
big
26:54
value.
26:55
And
26:55
then
26:55
finally
26:56
plan
26:56
for
26:57
the
26:57
long
26:57
term.
26:58
Clearly
26:59
define
26:59
and
27:00
communicate
27:01
the
27:01
vision
27:02
for
27:02
your
27:02
organization
27:02
to
27:03
focus
27:03
on.
27:03
So
27:03
as
27:04
AI
27:04
projects
27:05
come
27:05
up,
27:06
you
27:06
can
27:06
make
27:07
everybody
27:07
knows
27:07
they
27:07
need
27:07
to
27:08
be
27:08
aligned
27:08
to
27:08
those
27:08
goals
27:09
and
27:09
help
27:09
drive
27:09
them.
27:10
And
27:10
just
27:11
know
27:11
that
27:11
you're
27:11
not
27:11
alone
27:11
in
27:12
this
27:12
AWS
27:13
and
27:13
our
27:13
partners
27:13
are
27:14
here
27:14
to
27:14
help
27:15
to
27:16
give
27:16
you
27:16
the
27:17
technology
27:17
and
27:17
solutions
27:18
that
27:18
you
27:18
need
27:18
to
27:19
power
27:19
your
27:19
success.
27:21
Thanks.
27:21
Great
27:21
stuff,
27:22
Doug.
27:22
Thank
27:22
you.
27:23
Headline
27:24
number
27:24
four.
27:24
Wayfair
27:25
has
27:25
launched
27:25
a
27:26
new
27:26
paid
27:26
loyalty
27:27
program.
27:27
According
27:27
to
27:28
retail
27:28
Dive,
27:28
Wayfair
27:29
has
27:29
launched
27:29
a
27:29
new
27:29
membership
27:30
loyalty
27:30
program
27:31
across
27:31
all
27:31
of
27:31
its
27:32
banners,
27:32
including
27:33
Wayfair,
27:33
All
27:34
Modern,
27:34
Birch
27:34
Lane,
27:34
Jocelyn
27:35
Main
27:35
and
27:36
Paragould.
27:37
I
27:37
think,
27:37
I
27:38
think,
27:38
I
27:38
think
27:38
Wayfair
27:38
ascribes
27:39
too,
27:39
too
27:39
much
27:40
value
27:40
to
27:40
all
27:40
those
27:40
brands.
27:41
But
27:41
I
27:41
don't
27:41
know.
27:41
That's
27:41
just
27:41
my
27:42
opinion.
27:42
The
27:42
program
27:43
costs
27:43
29
27:44
per
27:44
year.
27:44
They
27:44
put
27:44
them
27:44
in
27:45
every
27:45
press
27:45
release.
27:46
The
27:46
program
27:46
costs
27:46
29
27:47
per
27:47
year
27:48
with
27:48
rewards
27:48
that
27:48
never
27:49
expire
27:49
as
27:50
long
27:50
as
27:50
subscriptions
27:51
do
27:51
not
27:51
lapse.
27:52
According
27:52
to
27:52
a
27:53
company
27:53
press
27:53
Release,
27:54
members
27:54
get
27:54
5%
27:55
back
27:55
in
27:55
rewards
27:56
on
27:56
all
27:56
purchases,
27:57
early
27:57
access
27:57
to
27:58
major
27:58
sales
27:58
events
27:59
and
27:59
free
27:59
shipping
27:59
on
27:59
orders
28:00
of
28:00
any
28:00
size,
28:01
among
28:01
other
28:01
perks.
28:02
Ann?
28:03
Yes.
28:04
Are
28:04
you
28:04
buying?
28:05
I
28:05
have
28:05
no
28:05
idea
28:05
which
28:05
way
28:05
you're
28:06
gonna
28:06
go
28:06
on
28:06
this.
28:06
Are
28:06
you
28:07
buying
28:07
or
28:07
selling
28:08
Wayfair's
28:09
new
28:09
paid
28:10
subscription
28:10
program?
28:10
Because
28:11
as
28:11
you
28:11
mentioned
28:11
at
28:11
the
28:11
outset,
28:12
you
28:12
are
28:12
in
28:12
the
28:13
middle
28:13
of
28:13
a
28:13
home
28:14
move.
28:15
Yes,
28:16
I'm
28:16
selling.
28:17
I'm
28:17
not
28:17
interested
28:18
in.
28:18
You're
28:18
selling.
28:19
I.
28:20
Well,
28:20
let
28:20
me
28:20
clarify.
28:21
Okay.
28:21
Okay.
28:22
As
28:22
we've
28:22
said
28:23
with
28:23
just
28:23
about
28:23
three.
28:23
Weeks,
28:23
you're
28:23
not
28:23
signing
28:24
up.
28:24
You're
28:24
not
28:24
signing
28:25
up.
28:25
I'm
28:25
definitely
28:26
not
28:26
signing
28:26
up.
28:27
Okay.
28:27
As
28:28
we've
28:28
said
28:28
though,
28:29
with
28:29
just
28:29
about
28:29
every
28:30
subscription
28:30
program
28:31
like
28:31
this,
28:31
it
28:32
costs
28:32
you
28:32
absolutely
28:33
nothing
28:33
but
28:34
time
28:34
and
28:35
probably
28:35
not
28:35
that
28:35
much
28:36
time
28:36
to
28:36
try
28:37
something
28:37
like
28:37
this.
28:38
So
28:38
if
28:39
you
28:39
want
28:39
to
28:40
put
28:40
it
28:40
out
28:40
there
28:40
and
28:40
see
28:41
who's
28:41
willing
28:41
to
28:41
pay
28:41
you
28:42
for
28:42
it
28:42
and
28:42
just
28:42
get
28:43
the
28:43
data
28:43
about
28:43
how
28:43
they're
28:44
using
28:44
it,
28:44
like
28:45
go
28:45
for
28:45
it,
28:45
be
28:45
my
28:46
guest.
28:46
But
28:46
great
28:47
point
28:47
with
28:47
subscription
28:47
programs,
28:48
great
28:48
point.
28:48
Yeah.
28:49
But
28:50
you
28:50
get
28:50
free
28:50
shipping
28:51
right
28:51
now
28:51
on
28:51
Wayfair
28:52
for
28:52
anything
28:52
you
28:53
order
28:53
over
28:53
$35.
28:54
And
28:55
my
28:55
guess
28:55
is
28:56
that
28:56
the
28:56
majority
28:56
of
28:57
people
28:57
who
28:57
are
28:57
ordering
28:58
things
28:58
from
28:58
Wayfair
28:59
are
28:59
at
29:00
least
29:00
spending
29:00
$35.
29:01
So
29:01
that
29:02
$30
29:02
a
29:02
year
29:03
is
29:03
really
29:03
of
29:04
no
29:04
value.
29:05
And
29:05
I,
29:05
you
29:05
know,
29:05
I
29:06
looked
29:06
in
29:06
specifically,
29:07
I
29:07
went
29:07
to
29:08
Wayfair,
29:08
I
29:09
do
29:09
have
29:09
the
29:09
tab
29:09
open,
29:11
but
29:11
I
29:12
went
29:12
in
29:12
there
29:12
and
29:12
I
29:12
checked
29:13
like
29:13
price
29:14
low
29:14
to
29:14
high
29:15
even.
29:15
They're
29:15
like
29:15
under
29:16
$20
29:16
section,
29:17
which
29:17
wouldn't
29:18
qualify
29:18
for
29:19
the,
29:19
you
29:19
know,
29:19
free
29:19
shipping.
29:20
And
29:20
it's
29:21
just
29:21
basic
29:21
stuff
29:22
like
29:22
mugs,
29:23
shower
29:23
organizers,
29:24
reed
29:24
diffuse,
29:25
like,
29:25
you
29:25
know,
29:25
that
29:25
kind
29:25
of
29:25
stuff.
29:26
And
29:26
I
29:26
think
29:26
that
29:27
if
29:27
I'm
29:27
shopping
29:28
for
29:28
that
29:28
stuff,
29:29
like
29:29
I
29:29
can
29:29
get
29:29
that
29:30
faster
29:30
and
29:30
cheaper
29:31
using
29:31
Amazon,
29:32
going
29:32
to
29:32
Walmart
29:33
or
29:33
going
29:33
to
29:33
Target
29:34
to
29:34
get
29:34
all
29:34
that
29:34
stuff
29:35
because
29:35
it's
29:35
really
29:36
basic,
29:36
nondescript
29:37
stuff.
29:37
But
29:37
pretty
29:38
much
29:38
everything
29:38
else
29:39
that
29:39
you're
29:39
ordering
29:39
from
29:40
Wayfair
29:40
is
29:40
going
29:41
to
29:41
be
29:41
above
29:41
that
29:41
$35
29:42
threshold.
29:42
And
29:43
I
29:43
just,
29:43
I
29:44
don't
29:44
see
29:45
the
29:45
5%
29:46
cash
29:46
back
29:46
as
29:46
like
29:47
something
29:47
that
29:47
you're
29:47
going
29:48
to
29:48
use
29:48
all
29:48
that
29:48
often
29:49
because
29:50
Wayfair
29:50
to
29:50
me
29:51
is
29:51
so
29:51
much
29:51
more
29:52
of
29:52
like
29:52
a
29:52
one
29:53
or
29:53
once
29:53
or
29:53
twice
29:54
a
29:54
year
29:54
time,
29:54
purchase
29:56
time.
29:56
It's
29:56
not
29:56
like
29:57
something
29:57
consistent
29:57
that
29:58
I'm
29:58
going
29:58
to
29:58
time
29:58
and
29:58
time
29:59
again
29:59
like
29:59
Walmart
30:00
or
30:00
like
30:00
Amazon.
30:01
But
30:02
you,
30:02
you
30:03
probably,
30:03
I
30:04
don't
30:04
know,
30:04
you
30:04
love
30:04
this,
30:05
I
30:05
think,
30:05
right.
30:06
This
30:06
is
30:06
your.
30:07
You're
30:07
in.
30:07
I
30:08
kind
30:08
of
30:08
do
30:10
explain
30:10
to
30:11
you
30:11
why
30:11
I'm
30:11
wrong.
30:12
Yeah,
30:12
I
30:12
don't.
30:14
Okay,
30:14
all
30:14
right.
30:15
Why?
30:15
I
30:15
don't
30:15
know.
30:16
I
30:16
don't
30:16
know
30:16
that
30:16
you're
30:16
wrong.
30:17
I
30:17
think
30:17
it's
30:17
just
30:17
perspective.
30:18
I
30:18
think,
30:19
I
30:19
think
30:19
the
30:19
audience
30:20
they're
30:20
trying
30:20
to
30:20
hit
30:20
is
30:20
exactly
30:21
the
30:21
audience
30:21
that
30:22
they're
30:22
trying
30:22
to
30:22
hit.
30:23
I
30:23
mean,
30:23
I,
30:23
I
30:24
mean,
30:24
what
30:24
do.
30:24
You
30:24
mean
30:24
by
30:24
that?
30:25
Well,
30:26
so,
30:26
okay,
30:26
if
30:26
I
30:27
step
30:27
back,
30:27
I
30:27
think,
30:28
I
30:28
think
30:28
this
30:29
announcement
30:29
or
30:30
this
30:30
headline
30:30
in
30:30
particular,
30:31
it
30:31
shows
30:32
just
30:32
how
30:32
left
30:33
brained
30:33
Wayfair's
30:34
management
30:34
is.
30:35
Which,
30:36
and
30:36
this
30:37
type
30:37
of
30:37
idea
30:37
works
30:38
in
30:38
instances
30:38
where
30:39
you're
30:39
talking
30:39
about
30:39
things
30:39
related
30:40
to
30:40
E
30:40
commerce.
30:40
Like
30:40
this
30:41
is
30:41
a
30:41
great
30:41
E
30:41
commerce
30:42
idea.
30:42
So
30:42
first
30:43
off,
30:43
and
30:44
right
30:44
Wayfair
30:45
knows
30:45
that
30:46
everyone
30:46
has
30:46
subscription
30:47
fatigue
30:47
so
30:47
there's
30:47
no
30:48
way
30:48
they're
30:48
going
30:48
to
30:48
get
30:48
someone
30:49
to
30:49
pay
30:49
like
30:49
$99
30:50
like
30:51
people
30:51
are
30:51
for
30:51
Walmart
30:52
plus
30:52
or
30:52
something
30:52
comparable
30:53
for
30:53
Amazon
30:53
Prime.
30:54
So
30:55
they
30:55
have
30:55
smartly
30:56
just
30:56
computed
30:56
the
30:57
inflection
30:57
point
30:58
of
30:58
where
30:58
the
30:59
customer
30:59
sees
30:59
value
31:00
and
31:00
hopefully
31:01
they're
31:01
going
31:01
to
31:01
get
31:01
the
31:01
incremental
31:02
revenue.
31:02
So
31:02
there's
31:02
some
31:02
portion
31:03
of
31:03
their
31:03
customers
31:03
that
31:04
are
31:04
probably
31:04
not
31:04
hitting
31:05
the
31:05
free
31:05
shipping
31:05
threshold
31:06
and
31:06
the
31:07
value
31:07
is
31:07
relatively
31:08
equivalent
31:08
to
31:08
them
31:09
signing
31:09
up
31:09
for
31:10
this.
31:10
And
31:10
therefore
31:11
they're
31:11
going
31:11
to
31:11
sign
31:11
up
31:12
for
31:12
it
31:12
because
31:12
it
31:12
just
31:13
makes
31:13
sense
31:13
economically.
31:14
And
31:15
therefore
31:15
they're
31:16
going
31:16
to
31:16
get
31:16
more
31:16
loyalty
31:17
too
31:17
in
31:17
the
31:17
long
31:17
run
31:17
because
31:17
you
31:17
get
31:18
the
31:18
5%
31:18
discount
31:19
and
31:19
then
31:19
people
31:19
generally
31:20
are.
31:20
The
31:20
general
31:21
concept
31:21
around
31:21
a
31:21
loyalty
31:22
program
31:22
is
31:22
you
31:22
pay
31:22
for
31:23
it,
31:23
you're
31:23
going
31:23
to
31:23
shop
31:24
there
31:24
more
31:24
often.
31:24
That's
31:24
just
31:25
kind
31:25
of
31:25
tried
31:25
and
31:25
true.
31:26
A
31:26
tried
31:26
and
31:26
true
31:27
axiom.
31:28
But
31:28
so
31:28
you
31:29
know,
31:29
net
31:29
net.
31:29
I
31:29
think
31:30
it's
31:30
a
31:30
very
31:30
smart,
31:31
analytical
31:32
left
31:32
brain
31:32
move
31:32
from
31:33
a
31:33
retail
31:33
company
31:34
run
31:34
by
31:34
the
31:34
most
31:35
left
31:35
brain
31:36
CEO
31:36
in
31:37
the
31:37
industry,
31:37
Nerd
31:37
Shaw.
31:38
And
31:38
you
31:39
know
31:39
I
31:39
throw
31:39
a
31:39
lot
31:39
of
31:39
at
31:40
them
31:40
but
31:40
you
31:40
know,
31:40
when
31:40
it
31:40
comes
31:40
to
31:41
E
31:41
commerce
31:41
they
31:41
just
31:42
get
31:42
it
31:42
and
31:42
they
31:42
understand
31:43
how
31:43
the
31:43
economics
31:44
of
31:44
it
31:44
work
31:44
and
31:45
how
31:45
to
31:45
drive
31:45
incremental
31:46
profit
31:46
from
31:46
thinking
31:47
in
31:47
this
31:47
manner.
31:48
Am
31:48
I
31:49
just
31:49
in
31:49
the,
31:50
in
31:50
like
31:50
the
31:51
outsider
31:52
group?
31:52
Like
31:52
how
31:52
much
31:52
are,
31:53
how
31:53
often
31:54
are
31:54
you
31:54
buying
31:55
home
31:55
decor?
31:55
Stuff
31:56
like
31:56
that
31:56
just
31:56
seems
31:57
so
31:57
crazy
31:58
to
31:58
me.
31:59
It's
31:59
all
31:59
incremental.
31:59
Well,
32:00
you're
32:00
the
32:00
one.
32:00
Yeah,
32:00
I
32:00
mean
32:01
I
32:01
remember
32:01
back
32:01
when
32:02
I
32:02
made
32:02
the,
32:02
I
32:02
made
32:02
the
32:03
argument
32:03
on
32:03
this
32:03
show,
32:04
if
32:04
we
32:04
played
32:04
back
32:05
the
32:05
tape
32:05
where
32:05
I
32:05
said
32:05
like
32:06
home
32:06
furnishings
32:06
is
32:07
generally
32:07
speaking
32:07
about
32:08
big
32:08
purchases
32:09
moments
32:09
in
32:09
your
32:10
life,
32:10
like
32:10
having
32:10
a
32:11
new
32:11
kid,
32:11
moving
32:12
a
32:12
second
32:12
home,
32:13
retiring,
32:13
going
32:13
to
32:14
college,
32:14
it's
32:14
generally
32:15
about
32:15
that.
32:16
But
32:16
there
32:16
are
32:16
the
32:16
top
32:17
up
32:17
purchases.
32:17
You
32:17
know,
32:18
that's
32:18
what
32:18
Target
32:18
has
32:19
made
32:19
its
32:19
bread,
32:20
bread
32:20
and
32:20
butter
32:20
on.
32:20
There's
32:21
like
32:21
the
32:21
throw
32:21
pillows,
32:21
the
32:22
decorative
32:22
things
32:22
that
32:22
you
32:23
add.
32:23
Those
32:23
throw
32:23
pillows
32:24
are
32:24
all
32:24
over
32:25
$35.
32:26
Like
32:26
you're
32:26
not
32:26
going
32:26
to
32:26
get
32:27
out
32:27
of
32:27
Wayfair.
32:28
Like
32:28
that's
32:28
what
32:28
doesn't
32:29
make
32:29
sense
32:29
to
32:29
me.
32:30
Like
32:30
I
32:30
guess
32:31
you
32:31
have
32:31
consumers.
32:32
Like
32:33
I
32:33
just
32:33
would
32:33
want
32:33
to
32:33
see
32:34
the
32:34
data
32:34
of
32:34
like
32:35
how
32:35
many
32:35
people
32:35
are
32:36
paying
32:36
for.
32:37
Well
32:37
the
32:37
other
32:37
point
32:37
of
32:37
this,
32:38
if
32:38
you're
32:38
saving
32:38
5%
32:39
on
32:39
your
32:40
purchases,
32:40
the
32:40
29
32:41
gets
32:41
to
32:41
be
32:42
a
32:42
pretty,
32:42
pretty
32:43
economically
32:44
advantageous
32:45
thing
32:45
to
32:45
sign
32:46
up
32:46
for
32:46
because
32:47
5%
32:47
is
32:47
$29
32:48
is
32:48
not
32:49
5%
32:49
of
32:49
all
32:50
that
32:50
much
32:50
too.
32:50
I
32:50
think
32:51
that's
32:51
another
32:51
Point
32:51
of
32:51
this,
32:52
which
32:52
I
32:52
think
32:52
we
32:53
probably
32:53
didn't
32:53
give.
32:53
It's
32:54
just
32:54
due
32:54
here
32:54
now
32:55
that
32:55
I'm
32:55
thinking
32:55
about
32:55
it
32:56
as
32:56
well.
32:56
It's
32:56
more
32:56
than
32:56
the
32:57
29
32:57
year,
32:58
I
32:58
guess
32:59
I
32:59
just.
33:00
Or
33:00
the
33:00
free,
33:00
you
33:00
know,
33:01
getting
33:01
past
33:01
the
33:01
shipping
33:02
costs.
33:02
It's.
33:03
All
33:03
right,
33:03
let's
33:03
close
33:03
up.
33:04
It's
33:04
not
33:04
your.
33:04
You're
33:04
not,
33:05
you're
33:05
just
33:05
not
33:05
into
33:05
it.
33:06
Yeah,
33:06
you're
33:06
not
33:06
into
33:06
it.
33:07
But.
33:07
But
33:07
Wafer
33:08
is
33:08
happy
33:08
to
33:08
know
33:08
that
33:09
you're.
33:09
You're
33:09
shopping
33:10
at
33:10
their.
33:10
I
33:10
am
33:11
shopping.
33:11
I
33:11
am
33:12
check
33:12
out
33:12
their
33:12
house
33:13
with
33:13
all
33:13
their
33:13
wares,
33:14
but
33:14
I
33:15
am
33:15
not
33:15
buying
33:16
your
33:17
subscription
33:17
program.
33:18
All
33:18
right.
33:19
Speaking
33:19
of,
33:19
speaking
33:19
of
33:19
this.
33:20
So,
33:20
Ann,
33:20
before
33:20
we
33:20
move
33:20
on,
33:21
random
33:21
aside,
33:22
we're
33:22
going
33:22
to
33:22
talk
33:22
about
33:23
this
33:23
next
33:23
week,
33:23
but
33:23
Walmart+
33:24
half
33:24
off
33:24
right
33:25
now.
33:25
Oh,
33:26
my
33:26
God.
33:26
We're
33:27
official
33:27
Walmart+
33:28
members.
33:28
I'm
33:28
going
33:28
to
33:28
do
33:28
all
33:28
my
33:29
shopping
33:29
from
33:29
Walmart
33:30
this
33:30
holiday.
33:31
I,
33:31
I
33:31
like.
33:32
We,
33:32
like
33:33
watched
33:33
Paramount
33:34
plus
33:34
last
33:34
night,
33:35
Chris.
33:35
We
33:35
were
33:35
like
33:36
in
33:36
it
33:36
and
33:36
I
33:36
was
33:37
started.
33:37
I
33:37
already
33:37
placed
33:38
a
33:38
grocery
33:38
order.
33:39
It
33:39
was
33:39
amazing.
33:39
I'm
33:39
like
33:40
super
33:40
into
33:41
it.
33:41
So,
33:41
yes,
33:41
Walmart
33:42
plus,
33:43
big
33:43
deal,
33:44
big.
33:44
Time
33:44
and
33:45
fun
33:45
tip
33:46
too.
33:46
All
33:46
of
33:46
those
33:47
brands
33:47
you're
33:47
probably
33:47
shopping
33:47
on
33:48
Wayfair
33:48
are
33:48
also
33:49
available
33:49
on
33:49
Walmart
33:50
most
33:50
likely.
33:51
So
33:51
I
33:51
would
33:51
check
33:51
them
33:52
out
33:52
as
33:52
second.
33:53
I
33:53
know
33:53
you
33:53
have
33:53
told
33:53
me,
33:54
you
33:54
have
33:54
told
33:54
me
33:55
to
33:55
use
33:55
Google
33:55
Lens
33:56
to
33:56
look
33:56
at
33:57
the
33:57
furniture
33:57
that
33:57
I'm
33:58
interested
33:58
in
33:58
and
33:58
then
33:59
see
33:59
where
33:59
I
33:59
can
33:59
find
33:59
it
34:00
for
34:00
the
34:00
best
34:00
price.
34:01
Just
34:01
a
34:01
little
34:01
shout
34:02
out
34:02
to
34:02
Google
34:02
Lens
34:03
again.
34:04
Okay,
34:04
let's
34:05
move
34:05
on
34:05
to
34:05
headline
34:06
number
34:06
five.
34:07
Marks
34:07
and
34:07
Spencer
34:08
is
34:08
adding
34:09
self
34:09
checkouts
34:10
in
34:10
the
34:11
dressing
34:11
rooms,
34:12
according
34:12
to
34:12
Chain
34:12
Storage,
34:13
the
34:13
British
34:13
apparel
34:14
and
34:14
food
34:14
giant
34:14
is
34:14
adding
34:15
self
34:15
checkouts
34:15
to
34:16
fitting
34:16
rooms
34:16
in
34:16
its
34:17
180
34:18
clothing
34:18
stores.
34:19
The
34:19
move
34:19
is
34:19
to
34:19
prevent
34:20
shoppers
34:20
from
34:20
having
34:21
to
34:21
get
34:21
in
34:21
line
34:21
twice
34:22
during
34:22
the
34:22
shopping
34:22
experience.
34:23
And
34:23
the
34:23
self
34:24
checkouts
34:24
are
34:24
expected
34:24
to
34:25
be
34:25
rolled
34:25
out
34:25
to
34:25
about
34:26
100
34:26
stores
34:27
by
34:27
early
34:28
2028.
34:28
The
34:28
initial
34:29
plan
34:29
is
34:29
to
34:29
add
34:30
one
34:30
of
34:30
the
34:30
checkouts
34:31
per
34:31
changing
34:31
room
34:32
area
34:32
with
34:32
a
34:32
number
34:33
to
34:33
increase
34:33
depending
34:33
on
34:34
consumer
34:34
demand
34:35
to
34:36
protect
34:36
against
34:36
shoplifting.
34:37
The
34:37
stores
34:37
would
34:37
have
34:37
staff
34:38
quote,
34:39
hosting,
34:39
end
34:40
quote,
34:40
the
34:40
changing
34:40
room
34:41
areas
34:41
to
34:41
make
34:41
sure
34:42
customers
34:42
did
34:42
not
34:42
leave
34:43
without
34:43
paying.
34:44
Chris,
34:44
do
34:44
you
34:44
think
34:44
we're
34:45
going
34:45
to
34:45
see
34:45
other
34:46
apparel
34:46
retail
34:47
retailers
34:48
follow
34:48
Marks
34:48
and
34:49
Spencer's
34:49
lead
34:49
in
34:50
trying
34:50
self
34:51
checkout
34:51
in
34:51
the
34:51
fitting
34:52
rooms?
34:53
Ooh,
34:53
that's.
34:54
That's
34:54
also
34:54
a
34:54
good
34:55
question.
34:55
I
34:56
think.
34:56
Sadly,
34:57
no.
34:57
But
34:58
I'd
34:58
say
34:58
that
34:58
I
34:58
think
34:58
they
34:59
should.
35:00
Right.
35:00
There's
35:00
a
35:01
tell
35:01
for
35:01
me.
35:01
There's
35:02
A
35:02
tell
35:02
for
35:02
me
35:02
that
35:03
that
35:03
Marks
35:03
and
35:03
Spencer's
35:04
doesn't
35:04
have
35:04
this
35:04
all
35:04
figured
35:04
out
35:05
yet.
35:05
And
35:05
it's
35:05
the
35:05
20.
35:06
What
35:06
is
35:07
the
35:07
2028
35:08
date
35:09
that
35:09
they're
35:09
putting
35:09
this.
35:09
That's
35:10
four
35:10
years
35:10
away.
35:11
So
35:11
that's
35:11
kind
35:11
of
35:11
nuts.
35:12
And,
35:12
and
35:13
the
35:13
idea
35:13
in
35:13
general
35:14
an
35:14
raises
35:14
so
35:14
many
35:15
questions
35:15
like
35:15
how
35:16
do
35:16
you
35:16
take
35:16
off
35:16
the
35:16
security
35:17
tags?
35:17
How
35:18
do
35:18
you
35:18
handle
35:18
bagging?
35:19
But
35:19
if
35:20
we
35:20
step
35:20
beyond
35:21
all
35:21
of
35:21
those,
35:21
like
35:21
what
35:21
do
35:22
you
35:22
have
35:22
to
35:22
figure
35:22
out
35:23
things
35:23
and
35:24
think
35:24
about
35:24
the
35:24
possible,
35:25
particularly
35:25
in
35:25
a
35:26
world
35:26
with
35:26
RFID
35:27
and
35:27
overhead
35:28
sensors.
35:29
I
35:30
wonder
35:30
if
35:30
this
35:30
setup
35:31
doesn't
35:31
actually
35:31
help
35:32
to
35:32
thwart
35:32
theft
35:33
more
35:33
in
35:33
the
35:33
long
35:34
run
35:34
because
35:35
you
35:35
can
35:35
better
35:35
monitor
35:35
the
35:36
garments
35:36
going
35:36
in
35:37
and
35:37
out
35:37
of
35:37
the
35:37
fitting
35:37
room
35:38
and
35:38
you
35:38
have
35:38
controlled
35:39
exit
35:39
and
35:39
entry
35:40
points
35:40
that
35:40
can
35:40
be
35:40
monitored
35:41
by
35:41
a
35:41
single
35:42
sales
35:42
associate.
35:43
And
35:43
then
35:43
of
35:43
course
35:43
you
35:43
don't
35:44
have
35:44
the
35:44
double
35:44
queuing
35:44
either.
35:45
So,
35:45
so
35:45
as
35:46
an
35:46
idea,
35:46
I,
35:47
I
35:47
love
35:47
where,
35:48
I
35:48
love
35:48
that
35:48
they're
35:49
doing
35:49
this
35:49
and
35:50
I
35:50
think
35:50
we're
35:50
going
35:50
to
35:50
see
35:50
more
35:51
experimentation
35:51
of
35:52
how
35:52
ultimately
35:53
it
35:53
should
35:53
work
35:53
best
35:54
in
35:54
a
35:54
fashionable
35:55
apparel.
35:55
Fashion.
35:56
Apparel
35:56
setting.
35:57
That's
35:57
my
35:57
take.
35:58
Yeah,
35:58
I
35:58
mean
35:58
we
35:59
did
35:59
the,
35:59
the
36:00
like
36:00
security
36:01
tag
36:01
removal
36:01
and
36:01
begging
36:02
at
36:02
the
36:02
Zara
36:02
in
36:02
Madrid.
36:03
And
36:03
I
36:03
think
36:03
that
36:03
it,
36:04
and
36:05
especially
36:05
if
36:05
you
36:05
have
36:05
an
36:05
associate
36:06
right
36:06
there,
36:06
I
36:06
mean
36:06
Uniqlo
36:07
is
36:07
doing
36:07
this
36:08
too
36:08
where
36:08
you
36:08
have
36:08
to
36:08
remove
36:09
tags
36:09
for
36:09
their
36:10
RFID
36:10
based
36:11
checkout.
36:11
I
36:11
mean
36:11
it
36:12
can
36:12
be
36:12
done.
36:13
And
36:14
with
36:14
RFID
36:14
you
36:14
don't
36:15
even
36:15
really
36:15
need
36:15
the
36:15
security
36:16
tags
36:16
anymore.
36:16
True.
36:17
That's
36:17
the
36:17
other
36:17
point
36:17
of
36:18
this.
36:18
Right?
36:18
Yes,
36:19
yes.
36:19
And
36:19
you
36:20
know,
36:20
in
36:21
talking
36:21
with
36:21
rfid,
36:22
we
36:22
just,
36:22
you
36:22
know,
36:23
we
36:23
tested
36:23
this
36:24
out,
36:24
you
36:24
know,
36:24
in
36:25
H
36:25
and
36:25
M
36:25
when
36:26
we
36:26
were
36:26
in
36:26
New
36:26
York
36:27
and
36:27
being
36:28
able
36:28
to
36:28
like
36:28
order.
36:29
That's
36:29
something
36:29
that
36:29
they're
36:29
working
36:30
on
36:30
too
36:30
at
36:30
H
36:30
and
36:30
M
36:31
is
36:31
how
36:31
the,
36:31
how
36:32
they
36:32
can
36:32
have
36:32
transactions
36:33
happen
36:33
from
36:34
the
36:34
fitting
36:34
room
36:35
and
36:35
you
36:36
just
36:36
walk
36:36
out.
36:36
Because
36:37
that
36:37
is
36:37
still
36:37
the
36:38
biggest
36:38
frustration
36:39
in
36:40
all
36:40
these
36:40
apparel
36:40
stores
36:41
that
36:41
have
36:41
invested
36:42
so
36:42
much
36:42
money
36:42
in
36:43
technology.
36:43
You
36:43
still
36:43
end
36:44
up
36:44
sitting
36:44
in
36:44
a
36:44
line
36:45
and
36:45
it's
36:45
one
36:45
of
36:45
the
36:45
most
36:46
frustrating
36:46
experiences
36:47
alive.
36:48
So
36:48
I
36:48
think
36:49
it's
36:49
going
36:49
to
36:49
be
36:49
really
36:49
cool
36:50
to
36:50
see
36:51
to
36:51
your
36:51
point
36:51
what
36:52
RFID
36:52
enables
36:53
and
36:53
how
36:53
that
36:53
can
36:54
hopefully
36:54
speed
36:54
this
36:55
process
36:55
so
36:55
that
36:55
they're
36:56
rolling
36:56
this
36:56
out
36:56
in
36:56
more
36:57
stores
36:57
more
36:58
quickly
36:58
than
36:58
2028.
36:59
And
36:59
I
36:59
just
37:00
give
37:00
a
37:00
shout
37:00
out
37:01
to.
37:01
We
37:02
just
37:02
interviewed
37:02
Troy
37:03
Cywick
37:03
from
37:03
Gray
37:04
Orange
37:04
who
37:04
talks
37:05
about
37:05
G
37:06
store
37:06
and
37:07
how
37:07
stores
37:08
like
37:08
H
37:08
M
37:09
have
37:09
used
37:09
the,
37:09
some
37:10
of
37:10
the
37:10
RFID
37:10
overhead
37:12
arrays
37:13
like
37:13
you
37:13
were
37:13
talking
37:14
about,
37:14
Chris,
37:14
to
37:15
help
37:15
enable
37:15
this
37:16
kind
37:16
of
37:16
stuff
37:16
in
37:16
stores,
37:17
I
37:17
think
37:17
we
37:17
can
37:17
get
37:17
there.
37:18
But
37:19
that's
37:19
a
37:19
great
37:19
podcast
37:20
to
37:20
just
37:20
learn
37:20
more
37:21
about
37:21
the
37:21
how
37:21
of
37:21
it.
37:22
And
37:22
then
37:22
finally
37:23
we're
37:23
going
37:23
to
37:24
be
37:24
going
37:24
out
37:24
to
37:25
Lumen
37:26
Field
37:26
in
37:26
a
37:26
few
37:26
weeks
37:27
to
37:27
shoot
37:28
the
37:28
Just
37:28
Walk
37:28
out
37:29
technology
37:29
with
37:30
apparel
37:31
in
37:32
in
37:32
Seattle.
37:33
And
37:33
I'm
37:33
really
37:33
excited
37:33
to
37:34
see
37:34
how
37:34
that
37:34
plays
37:34
out
37:34
as
37:35
well
37:35
because
37:35
I
37:36
think
37:36
that
37:36
hits
37:37
on
37:37
this,
37:37
this
37:38
theft
37:39
issue
37:39
of,
37:39
you
37:40
know,
37:40
if
37:40
there's
37:41
a
37:41
controlled
37:41
entry
37:42
and
37:42
exit
37:42
and
37:42
then
37:42
you
37:43
can
37:43
just
37:43
walk
37:43
out
37:43
with
37:44
that
37:44
stuff.
37:44
I
37:44
think
37:44
that's
37:45
another
37:45
way
37:46
that
37:46
we
37:46
could
37:46
start
37:47
to
37:47
see
37:47
some
37:48
of
37:48
this
37:48
apparel
37:49
shopping
37:50
experience
37:50
changing
37:51
for
37:51
consumers
37:52
for.
37:52
The
37:52
better,
37:53
which
37:53
is
37:53
all
37:54
done
37:54
with
37:54
RFID
37:54
too.
37:55
That's
37:55
why
37:55
this
37:55
story
37:56
is
37:56
so
37:57
important
37:57
to
37:57
pay
37:58
attention
37:58
to.
37:58
All
37:58
right,
37:59
and
37:59
let's
37:59
close
37:59
this
38:00
show
38:00
up
38:00
and
38:00
let's
38:00
go
38:00
to
38:00
the
38:01
lightning
38:01
round.
38:02
All
38:02
right,
38:03
Chris,
38:03
question
38:04
number
38:04
one
38:04
goes
38:04
to
38:05
you.
38:05
Walmart
38:05
is
38:05
doing
38:05
a
38:06
series
38:06
of
38:06
parodies
38:07
on
38:07
popular
38:07
TV
38:08
series
38:08
like
38:08
Yellowstone
38:09
Bridgerton,
38:09
Real
38:10
Housewives,
38:10
Friday
38:11
Night
38:11
Lights
38:11
and
38:11
more
38:11
for
38:12
their
38:12
Black
38:12
Friday
38:13
deals
38:13
campaign.
38:13
Which
38:14
one
38:14
are
38:14
you
38:14
most
38:15
excited
38:15
to
38:15
watch
38:16
or
38:17
which
38:17
series
38:18
do
38:18
you
38:18
wish
38:18
they
38:19
would
38:19
have
38:19
parodied
38:20
and
38:20
didn't?
38:21
Oh
38:22
my
38:22
God.
38:22
The
38:22
one
38:22
I.
38:23
The
38:23
Bridgerton
38:23
one
38:23
looks
38:24
classic.
38:24
Like,
38:24
I
38:24
can't
38:25
wait
38:25
to
38:25
see
38:25
what
38:25
they
38:25
do.
38:26
That
38:26
one
38:26
is
38:27
now
38:27
selling
38:27
a
38:27
tiny
38:28
house
38:28
online
38:28
for
38:29
$15,900.
38:30
The
38:30
19
38:31
by
38:32
20
38:32
foot
38:33
expandable
38:33
prefab
38:34
prefab
38:35
house
38:35
is
38:36
delivered
38:36
by
38:36
flatbed
38:37
truck
38:37
and
38:37
requires
38:38
a
38:38
forklift
38:38
for
38:39
unloading.
38:39
According
38:40
to
38:40
the
38:40
online
38:40
listing.
38:41
Were
38:41
you
38:41
to
38:41
purchase
38:42
said
38:42
prefab
38:43
house,
38:43
what
38:43
name
38:43
would
38:43
you
38:44
give
38:44
it?
38:45
Alone
38:45
time.
38:48
Nicely
38:49
done.
38:49
Nicely
38:49
done
38:50
for
38:50
me
38:50
or
38:51
somebody.
38:51
But
38:52
I
38:52
would
38:53
definitely
38:54
take
38:54
that
38:54
thing
38:54
and
38:54
put
38:55
it
38:55
in
38:55
my
38:55
backyard
38:56
and
38:57
it
38:57
would
38:57
be
38:58
time
38:58
for
38:58
myself,
38:59
me,
38:59
myself
38:59
and
38:59
I.
39:00
No,
39:00
I
39:01
literally,
39:01
I
39:02
literally
39:02
just
39:02
thought
39:02
of
39:02
this.
39:03
Mine
39:03
would
39:03
be
39:03
absolutely
39:04
pretty
39:04
fabulous.
39:05
Oh
39:06
my
39:06
God.
39:08
We
39:08
went
39:08
in
39:09
two
39:09
very
39:09
different
39:09
directions
39:10
with.
39:10
Right.
39:11
I
39:11
literally
39:11
just
39:11
came
39:11
up
39:11
with
39:12
that.
39:12
I
39:12
did
39:12
not
39:12
know
39:12
that
39:13
beforehand.
39:13
Question
39:14
number
39:14
three.
39:15
Game
39:15
changer
39:15
owned
39:16
by
39:16
Dick's
39:16
Sporting
39:16
Goods,
39:17
launched
39:17
Film
39:18
Room,
39:18
an
39:18
app
39:18
that
39:19
helps
39:19
tap
39:20
AI
39:21
to
39:21
help
39:21
coaches
39:22
analyze
39:22
game
39:22
footage
39:23
for
39:23
youth
39:23
basketball
39:24
and
39:24
volleyball
39:24
games
39:25
and
39:25
shares
39:25
those
39:26
highlights
39:26
with
39:26
team
39:27
members.
39:27
Chris,
39:28
what
39:28
would
39:29
Film
39:29
Room
39:29
call
39:29
out
39:30
as
39:30
one
39:30
of
39:31
a
39:31
strapping
39:32
young
39:32
Chris
39:32
Walton's
39:33
greatest
39:34
basketball
39:34
highlights?
39:35
Well,
39:36
I'm
39:36
not
39:36
sure
39:36
that
39:36
anyone
39:37
in
39:37
my
39:37
history
39:37
of
39:37
my
39:38
47
39:38
year
39:38
old
39:39
life
39:39
has
39:39
ever
39:39
called
39:39
me
39:39
Strapping
39:40
Ann,
39:40
but
39:41
thank
39:41
you
39:41
for
39:41
at
39:41
least.
39:42
Yes,
39:42
thinking
39:43
that
39:43
that's
39:43
what
39:43
I
39:43
look
39:44
like
39:44
in
39:44
high
39:44
school.
39:44
But
39:45
the
39:46
answer
39:46
for
39:46
me
39:47
is
39:47
freshman
39:48
year
39:48
against
39:49
North
39:49
High
39:49
basketball
39:50
Came,
39:51
got
39:51
sent
39:52
into
39:52
the
39:52
game
39:52
just
39:52
to
39:53
shoot
39:53
the
39:53
technical
39:53
free
39:54
throws
39:54
to
39:54
ice
39:54
the
39:54
game.
39:55
That
39:55
was.
39:55
That
39:55
was
39:56
my
39:56
crowning,
39:57
crowning
39:58
high
39:58
school
39:58
basketball
39:59
achievement.
40:00
So
40:00
proud
40:00
of
40:00
you.
40:00
All
40:00
right.
40:01
It
40:01
would
40:01
be
40:01
just
40:02
everyone
40:02
on
40:03
the.
40:03
Everyone
40:04
on
40:04
the
40:04
team
40:04
would
40:04
get
40:04
that
40:05
footage.
40:05
Yeah,
40:06
right.
40:06
And
40:06
no
40:06
one
40:07
would
40:07
watch
40:07
it.
40:07
Just
40:07
like
40:08
my
40:08
basketball
40:08
career.
40:09
All
40:09
right,
40:09
and
40:09
headline
40:10
number
40:10
or
40:11
lightning
40:11
round,
40:11
Question
40:11
number
40:12
four.
40:13
A
40:13
museum
40:14
owner
40:14
recently
40:14
uncovered
40:15
a
40:15
previously
40:16
unknown
40:16
waltz
40:17
composed
40:17
by
40:17
Frederick
40:18
Chopin.
40:19
When
40:19
was
40:19
the
40:20
last
40:20
time
40:20
you
40:21
waltzed?
40:22
Does
40:23
playing
40:23
a
40:23
waltz
40:24
on
40:24
the
40:24
piano
40:25
count?
40:26
Yeah,
40:26
sure.
40:26
Why
40:26
not
40:27
actually
40:27
dance?
40:28
Okay.
40:28
You're
40:28
dancing
40:28
in
40:29
your
40:29
head.
40:29
I
40:29
was
40:29
curious
40:29
about
40:30
more
40:30
when
40:30
you
40:30
danced.
40:31
Oh,
40:31
I
40:31
don't
40:32
think
40:32
I've
40:32
ever.
40:32
Because
40:32
you
40:32
gotta,
40:33
like,
40:33
you
40:33
know,
40:34
you
40:34
gotta
40:34
put
40:34
your
40:34
hand
40:34
out
40:35
like
40:35
this
40:35
for
40:35
those
40:35
watching
40:36
and
40:36
like,
40:36
all
40:36
that
40:37
kind
40:37
of
40:37
stuff.
40:37
Yeah,
40:37
you
40:37
never
40:38
waltz.
40:38
I
40:39
don't
40:39
think
40:39
I've
40:39
ever
40:39
waltzed,
40:40
but
40:40
I
40:40
did
40:40
have
40:40
to
40:40
learn
40:41
one
40:42
on
40:42
the
40:42
piano.
40:43
I
40:43
think
40:43
I
40:43
was
40:43
in
40:44
fifth
40:44
grade
40:44
with
40:45
my
40:45
piano
40:45
teacher,
40:46
Virginia
40:46
Schmidt,
40:47
whose
40:47
perfume
40:47
I
40:48
can
40:48
still
40:48
smell
40:49
to
40:49
this
40:49
day.
40:50
Virginia
40:50
Schmidt
40:51
sounds
40:51
exactly
40:52
like
40:52
the
40:52
name
40:52
of
40:52
a
40:52
piano
40:53
teacher.
40:53
Like,
40:54
you
40:54
know,
40:54
piano
40:54
teacher.
40:55
Yep.
40:55
He
40:55
couldn't
40:56
even
40:56
make
40:56
that
40:56
up.
40:57
Piano
40:57
Virginia
40:58
Schmidt
40:58
and
40:59
her
40:59
fancy
41:00
smells.
41:00
All
41:00
right,
41:01
happy
41:01
birthday
41:01
today
41:02
to
41:02
Harry
41:03
Winkler.
41:03
Nia
41:04
Long.
41:04
And.
41:04
And
41:04
to
41:04
the
41:04
man
41:05
who
41:05
is
41:05
the
41:05
real
41:05
reason
41:06
Mrs.
41:07
Omnitok
41:07
was
41:07
a
41:07
huge
41:08
Glee
41:09
fan,
41:09
Matthew
41:10
Morrison.
41:11
Huge
41:11
Glee
41:12
fan
41:12
Matthew
41:13
Morrison.
41:13
And
41:14
remember,
41:14
if
41:14
you
41:14
can
41:14
only
41:14
read
41:15
or
41:15
listen
41:15
to
41:15
one
41:15
retail
41:16
blog
41:16
in
41:16
the
41:16
business,
41:16
Make
41:16
It
41:17
Omnietalk,
41:17
the
41:17
only
41:18
retail
41:18
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41:18
outlet
41:19
run
41:19
by
41:19
two
41:19
former
41:20
executives
41:20
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41:20
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41:20
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41:20
top
41:21
10
41:21
US
41:21
retailer.
41:22
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41:22
Fast
41:22
Five
41:23
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41:23
is
41:23
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41:23
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41:24
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41:24
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41:24
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41:24
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41:24
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41:25
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41:25
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41:25
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41:25
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41:26
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41:26
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41:26
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41:26
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41:27
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41:27
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41:27
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41:28
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41:28
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41:28
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41:28
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41:28
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41:28
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41:28
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41:29
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41:29
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41:29
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41:29
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41:29
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41:29
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41:30
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41:30
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41:30
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41:30
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41:30
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41:31
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41:31
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41:32
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41:32
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41:32
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41:32
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41:33
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41:33
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41:34
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41:34
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41:34
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41:34
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41:34
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41:35
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41:35
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41:35
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41:35
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41:35
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41:35
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41:35
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41:36
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41:36
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41:36
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41:36
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41:36
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41:36
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41:37
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41:37
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41:37
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41:38
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41:38
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41:38
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41:38
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41:38
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41:39
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41:39
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41:39
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41:39
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41:40
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41:40
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41:40
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41:40
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41:40
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41:41
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41:41
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41:41
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41:41
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41:41
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41:42
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41:42
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41:43
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41:43
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41:44
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41:44
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41:45
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41:45
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41:45
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41:46
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41:46
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41:46
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41:47
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41:48
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41:49
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41:49
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41:49
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41:49
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41:50
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41:50
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41:50
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41:50
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41:51
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41:51
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41:52
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41:52
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41:52
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41:53
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41:53
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41:53
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41:54
So
41:54
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41:54
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41:54
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41:55
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41:55
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41:55
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41:55
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41:55
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41:55
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41:56
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41:56
Omnitalk
41:56
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41:57
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41:57
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41:57
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41:58
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41:58
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41:58
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