- Hi, good afternoon
everybody and welcome back.
So, we're going to talk a little bit
about the evolution of retail
and how we're powering
some of that revolution
with awesome data.
So with me today,
I have Russell Scherwin from IBM
and he actually runs some
of the Watson technology,
AI services.
And he's been thinking about how that
and marketing come together.
So let me have him introduce himself
and then we'll get started.
- Hey good afternoon.
I am Russell Scherwin.
And I believe I'm looking
at that camera right there.
How are you all doing?
Russell Scherwin, I run the marketing
for IBM Watson Commerce.
Which means I have a team
responsible for helping retailers.
So also b2b organizations.
Market, sell and fulfill more effectively
in an ever-changing omnichannel world.
- That's awesome.
It's going to be exciting.
So last month,
you published a really great article
that talked about the insights
of how you take some of this AI work
and start to help retailers
look at that information
and drive their business.
Tell us a little bit about that.
- I appreciate the question.
And if I recall the article right,
it was when we spoke about
some of our customers
like Carhartt and Calvin Klein brands.
And if you've watched
TV over the past year,
you know that IBM and
probably the rest of the world
is talking about Artificial Intelligence.
Artificial Intelligence,
it's not new technology.
But the hardware's caught up
so we can make it a reality.
And what you're starting to see,
and we're starting to see,
is those first couple of use cases
are going from concept and imagination
to having an impact in the real world.
So I'll give you a couple
areas where we're seeing
impact happening today.
One retailer during the holiday season.
I mean, a little known part
about site merchandising.
You have a website,
you have product category pages,
and people think it's simple.
You go to the website,
you pick out the dress you want,
you click buy and you buy.
Well who decides how to sequence products
on a catalog page,
on a category page?
There are merchandisers whose sole job
is to sequence those products effectively.
- It's a great point.
- So in the previous world,
this is the formal decision making process
the 26 year old would make that decision.
All right, it's a gut feel.
Watson understands lots of information.
So during the holiday season,
Watson understanding inventory positions
would make recommendations or
on his own where permitted,
would drive intelligence sequencing
to put, let's say,
a piece of inventory that was
out of stock off the page.
Whereas a lot of times,
inventory that's out of stock
will get the top billing on a page.
Or inventory that was
about to go on markdown
will get top billing to
optimize for profitability.
And so that's one example of
where Artificial Intelligence
is being used.
And I could give you more
examples if you'd like.
- Well let's talk about that example.
So in the holidays,
you had some customers,
they were starting to use this.
What was the impact of that?
How were they able to change the business?
- Oh, it's huge.
And obviously I can't
talk specific results.
Just you know, out of stocks, down.
Because you're putting out
inventory you could sell.
And when you factor in the fact
that IBM Sterling Order Management
understands inventory
positions at a store level
and understands the geography of a store
and also understands where that audience,
that person on the page is coming from,
it can map up local inventory.
And hyper localization to
that particular individual.
- That's very cool.
And I can imagine that
actually probably drives
the consumer's experience up
because now they're getting information
that they can actually act on
versus things that are out of stock
or us merchandising things
that they can't have.
- Absolutely, let's take an
out of stock for a second.
You go to your favorite store.
You go to the
menswearhouse.com, let's say,
a nice generic place.
That looks well beyond menswearhouse.com.
But let's just go generic.
And they're a great customer tailor brand.
So I gotta give 'em a bit of a plug here.
And that purple jacket you're
looking for is out of stock.
How do you feel?
- Awful.
- Who feels even worse than you?
- The sales guy.
- Exactly.
- And so being able to
mitigate out of stocks...
I mean, there's a trillion dollars
in out of stocks that happen.
- That's great.
That's great feedback.
Let's change gears a little bit.
So that's the power of doing this.
Some people have criticized AI
and said you know the problem is that
it actually takes on some of the biases
that the programmers have.
How do you make sure
that that doesn't happen
to something like Watson.
Or how do you react to
that simple statement?
- So, it's a great question.
And I kind of would like to go back
and give a couple more use case examples.
But let me go address the question
because that would be fair.
So first of all, AI,
it's a great topic.
It's a buzzword.
It's Kool-Aid right.
But what it fundamentally is
is it's neural network technology.
And who out there?
Wow, we got an audience, cool.
I thought we were just
talking to ourselves here.
Which of you all have...
Who of you have studied
neural network programming?
- No, just kidding.
- I have.
- So what you're ultimately doing is
is you're training a learning system.
And the greatest example
I find of understanding AI
is when I teach my two year old.
My two year old's a sponge.
And you're teaching him how to think.
You're feeding him data sets
and you're telling him, you know,
if you say one plus one is
three, well that's wrong.
They're system learns one plus one is two.
The system gets it.
You put images in front, you tell him...
Let's say Watson Content Hub,
which is our tagging system for images.
It's a content management system.
You infuse in images.
And you're teaching it to say
this is a red hat,
this is a blue hat,
this is a green hat.
Okay, so the concept of red,
blue, and green is coming in.
And then you say hat.
Okay, this is what a hat looks like.
And it starts learning context.
To answer your question directly,
it's impossible.
I mean getting past the buzzwords,
it's impossible to get rid of bias.
Bias is a fact of life.
But what you can do,
and this is one of the
things that IT departments
and businesses will struggle
with for quite some time,
is you have to surround
the AI learning process
with different points of references,
different cultural points of reference.
And that's just as much a factor for me
making sure that my kid goes to school.
I put him in a diverse,
multicultural environment.
So his learning is not filled with bias.
With the same thing as a learning system.
You can't get rid of
bias because it learns.
A neural network,
it learns the same exact
way the human brain learns.
- That's a great answer, thank you.
And I think again,
to try and bring this into how this works,
one of the benefits of
having a system like this
is you can also correct.
So just like with a two year
old that you talked about,
while they learn bad things,
you can also teach them
how to correct off of that.
- Correct.
- And this is where I think
the industry will go.
Because in many ways,
merchandising is an A/B test game.
And with the kinds of technologies
you guys are bringing to market,
you can start to A/B test
and learn correct versus
incorrect at hyper speeds,
versus the way humans would do it.
So it's a very exciting space.
You know the other thing you did
maybe a couple weeks ago
is you tweeted that we
got to have retailers
start fighting against
the digital disruption.
What did you mean by that?
And how is AI going to help them do that?
- It's a great question.
So the question,
I'll rephrase it.
It's what do we mean by
retailers need to go on the offensive
against digital disruption?
Any retailers out there?
Well for those...
I imagine somewhere at
NRF exists a retailer.
And if you're not feeling
the strain of Amazon
you're in trouble.
I'll give you an example.
So I used to lead the sales organization.
We had one multi billion dollar retailer
dropping 20% of stores
but they're shifting the
dollars to e-commerce.
And we're talking about what's the future.
Where are you gonna go?
And as we're getting to know
each other better personally,
you know it gets to 12:00 a.m.,
1:00 a.m.,
we're out to drinks,
he's like dude what are we supposed to do?
Get in the fetal position and die?
We're gonna have to fight back.
And a little bit farther in
the conversation it's like
what am I supposed to do?
And this is an office supply company.
My wife buys frickin' pens from Amazon.
What are we supposed to do?
So there's a general sense from retailers
within specific segments
that there's an existential crisis.
And it's not caused by Amazon.
It's caused by not driving
intimacy with customers.
It's not creating the experience needed.
It's not giving the price needed.
So let me answer your question directly.
Because I'm just rambling
as opposed to answering your question.
Going on the offensive means
what I have experienced
in my customer base is
most retailers,
their DNA is being a retailer.
Amazon is a technology company
that understands retail
better than most retailers
because their data gives them
better customer insight.
And to go on the offensive,
it means companies who
are not digital natives,
it's not in their DNA,
they need to fight Amazon
and go on the offensive.
Any my take on this is this.
For years,
the Walmart’s, the Staples,
all the brick and mortar retailers
have been playing catch-up.
Because Amazon,
as you know from your background,
has been a step ahead.
And going on the offensive
means innovating.
And by innovating means
building bridges between
their product markets
and building better
intimacy with customers
and creating either better experiences,
better prices,
or better means to get the
product to the customer,
or better services that
differentiate the offerings.
- That's great.
That's great, thank you.
All right, last question.
And then we'll wrap it up.
And I'll have you close.
When you think about the future of retail
and you think about this offense,
what do you think the next
few trends are gonna be?
And where should retailers be looking
to be able to go drive the
next generation experiences?
- Yeah, can I take a couple
minutes to answer that question?
- I got all the time in the world.
- All right.
So a couple places we could go with that.
First of all,
I think the future is in the past.
I see we still got this audience here.
So how many of you out
there know FAO Schwarz?
Awesome, we got a bunch of
people who know FAO Schwarz.
Who was shopping there back in the '90s?
Who saw the movie Big?
Awesome.
So Peter Harris is a guy
I was lucky enough to meet
and has become a mentor.
Peter Harris was the old guy in Big
who danced on the piano.
And that character was modeled
after the former CEO of FAO Schwarz.
And so I remember as I
got to know him better
I said dude,
how did you make money?
Because everybody knows that FAO Schwarz,
you wander around their store.
You got 40 foot high stuffed animals.
And you have the massive piano.
And you have all sorts of stuff
that no one in their right
minds would ever buy.
And so how do you make money?
And so Peter explained
that they build this magnificent maze.
You have these exclusives
with Milton Bradley,
and Parker Brothers,
and all this stuff no one's gonna buy.
And you walk around the store and you say
mommy can I buy, no.
Mommy can I have that, no.
Mommy can I get that, no.
And by the time you get
to the end of the store,
the mom is feeling like garbage
'cause they said no 20 times.
The kid is wiry.
He wants something.
And there are these clowns
at the end of the store
who are playing with these
goofy light up yo-yos.
And there's a unit cost
of $1.99 on these yo-yos.
And they're marked up to $25.
FAO Schwarz made all their money
with their primary segment
on that $23 markup
by creating an experience.
And getting back to
answering your question.
What's the future of retail?
It's understanding your segment
and creating an experience
that tailors to them.
But there's a caveat there.
Segment...
Segment one in Peter
Harris' business strategy
was with families.
Destination visits,
going to New York city
to see a retail outlet.
That is a massive segment.
In the future,
it's segments of one,
hyper personalization.
Understanding that I'm J Jill
and I'm marketing to Jane Smith.
And Jane Smith is three months
away from being a grandma
for the first time.
And there are events in that person's life
that's gonna drive decisions.
And understanding in
what medium to get to her
and what message to get to her
and what's the content and
the offer at the right time
that's going to drive a conversion
at the same time that drives loyalty.
And there's other pieces.
I'm gonna keep going here.
It's doing all that profitably.
I bet if I wander around this crazy place,
I'm gonna see 20% of the vendors...
It's a rule.
You have to say omnichannel
somewhere in your booth.
Buy online, pick...
Owning Sterling Order Management,
when Best Buy does buy
online, pick up in store,
it's my technology driving it.
So doing that profitably
is a different story.
I'll give you an example.
There is one $20 billion retailer
that during the holiday season knows
that their store inventory is a weapon.
Ship from store.
Doing it profitably is a different story.
So Watson Order Optimizer...
And again,
I see the future retail,
Watson helping create
personalized experience.
Here it's Watson driving
order optimization.
If I have a multi line order,
what's the most profitable way to ship it
to break down the individual line items
and ship it?
But that's not the easiest
question in the world
because what if one of
the items I'm ordering
is about to go on markdown?
- Perfect.
- Those sorts of things.
- That's perfect.
Thank you very much.
That was a great session.
If I just wrap this up
for you in this way.
If you think about some of the data
and some of the services like Watson
that we're talking about
and then you overlay Verifone Connect
that allows you to take
merchant experiences,
personalization experiences for consumers,
and bring those together to
create an end to end experience
where the merchants are growing,
the consumers are having a
better personalized experience,
that is exactly what
we're showing here today.
So if you haven't had a chance,
please take a look at some of the booths.
We have exactly what we've
talked about online here
for everybody from a small coffee shop
all the way to the tier
one largest retailers
that are out there in the world.
Thank you very much everybody
and enjoy the show.
- Thank you.
