February 6, 2025 • 22 mins
Smart retail has been a buzzword for years, but we’re now at a critical inflection point. The industry grapples with rapid innovation, shifting customer expectations and mounting operational pressures. Retailers don’t look just for incremental upgrades—they need a complete digital transformation that integrates automation, AI-driven insights, and real-time data to stay competitive.
In this podcast episode, we explore the future of smart retail and how emerging technologies drive the industry forward. From AI-powered customer behavior analytics and personalized digital signage to voice AI for seamless wayfinding and transactions, we examine how innovation reshapes both the store and the customer experience.
Join us as we explore these ideas with:
Silvia Kuo, Director of Business Development and Partnerships, ASUS
Christina Cardoza, Editorial Director, insight.tech
Silvia answers our questions about:
- Challenges smart retail still has to overcome
- Enhancing employee experience with AI
- Using technology to make smart retail a reality
- Integrating technology into existing infrastructure
- Real-world use cases and lessons learned
- Leveraging industry expertise
- Smart retail’s ongoing evolution
Related Content
To learn more about the evolution of retail, read POC Shows What’s In Store for Retail Analytics. For the latest innovations from ASUS, follow them on Twitter/X at @asus and LinkedIn.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
(upbeat music)
- Hello and welcome to"insight.tech Talk,"
where we explore the latest IoT, AI, edge
and network technologytrends and innovations.
As always, I'm yourhost, Christina Cardoza,
(00:22):
Editorial Director of insight.tech,
and today we're exploringthe world of smart retail
with Silvia Kuo from ASUS.
Hey Silvia, thanks for joining us.
- Hello. Nice to be here.
Thank you, Christina.
- Before we jump into the conversation,
what can you tell us aboutyourself and what you do at ASUS?
- Yeah, so I'm the BusinessDevelopment Director at ASUS
for the EMEA region,
(00:42):
and I basically, myjob, what I do is I look
for new projects to engage in.
I also look into what technology we should
include in those projects.
And the other thing I do isalso I run the partner program,
which is essentially lookingfor different partners
to create solutions togetherand offer them to the market.
- Great. Excited todive into some of that.
(01:03):
I know ASUS has a lot of solutions
and a lot of ways you can help retailers
or partners in this space.
But I wanted to start off the conversation
because we're talking about smart retail
and I feel like this is a keyword that has been floating
around for a couple of years now.
So when we say smart retail
and when we talk about smartretail, what do we mean?
Are retailers there yet,
or what are the challengesthat they're still facing
(01:25):
to get to smart retail?
- I think that smart retailhas been around for a while
and everyone's talking about it,
but I think that there is this, of course,
as any change, right?
There's a bit of resistance,
but there is also this imminentchange that you can feel.
And I think that the industryhas been probably trying
to look for a direction,that's my feeling,
(01:48):
but there is a lot ofinnovation that we see
and they are adopting it.
And I think that a few years from now,
retail might look a bitdifferent from what we know it,
how we know it today.
- One thing I've noticedwith smart retail,
and I've noticed ASUS standsout a little bit in this space,
is that when retailersdo their transformation,
it often happens insilos or one at a time.
(02:10):
They do self-checkoutor they do inventory.
What I love about ASUS isthe company has a range
of products from end-to-endto really go from inventory
to behavioral analyticsto space optimization.
So what can you tell us about some
of the smart retail solutions out there
and how that can help reallytransform a business from front
end to backend rather thanjust one area at a time?
(02:32):
- Right, and I think that's, you know,
the reason why we have, wehave this more comprehensive,
if you may, or holistictype of approach, is really
because of the nature ofcomputer company, right?
So we are the brain, let'ssay, behind all of this
innovation is where we, it runs.
So because of that, we have had
to look into the differentsolution as a whole.
(02:53):
So when we offer something,it's more of an end-to-end.
It's we are looking into a problem
and then seeing whatcomponents put into a solution
to solve this problem.
And that is why it'sthis holistic approach.
And I think that inretail, some of the things
that we are doing today is fall,
I think it always fallsinto two categories.
Either it is gatheringdata in order to allow
(03:17):
to analyze this data and furthermake data-driven decisions,
or is automating process.
And I think that inretail is very important
because we're seeing thatone of the main challenges is
that there's a lack of personnel
all around the world, right?
And people not wanting to do this kind
of operational routine type of jobs.
So what was happening is that
the retailers are quitedesperate in trying
(03:39):
to find a solution tomake this less costly
and also to make people be able to do job
that is more meaningful for them.
So for example, instead of, you know,
filling up the shelves, they'llbe managing systems that'll
fill up the shelves for them
or in instead of, you know, looking
and completing Excel forms tosay, "Okay, what I need to buy
for the next quarter?" it'llbe, you know, analyzing this
(04:01):
through a computer andmaking a sort of a decision,
a final decision, or reviewing that.
So this kind of managementof systems is how we see
where the industry is going.
- And I love how you put that
because I feel like a lot
of times when technology likethis comes into play, a lot
of people are worried that it'sgoing to replace their jobs
(04:22):
or what the technology is going to do,
but it sounds like it's reallytaking away the mundane tasks
and making their role more valuable
and making their position within a
retail store more valuable.
- Of course, of course.
And I, and we see that overall.
Like we see that now we wantpeople to be more engaged
and to have more meaningful,
because I think it comesalong with the introspection
(04:43):
that we as human beingshave, are becoming more
and more aware of our psychology
and you know, thingsmeaningfulness in life.
And I think the technologyallows us to explore
that side even more.
So, like you say, it's,a lot of people feel
that it's a threat,especially AI, it's going
to be a threat, replaceall of all of our jobs.
I think that it's a shift.
It is like everything, right?
(05:03):
In technology and even, you know,
the industrial revolutiontime a long time ago,
people were scared, butactually what happened is
that it improved production,it improved people's lives.
So for example, when I seelogistics, there's a lot
that we can do still in logistics.
Sometimes it's still todaythe process is very manual.
So things like trackingthe stock when it comes in:
How much do I have? Instead ofsending someone to count it,
(05:24):
then I have a systemthat can just naturally
do it quickly for me.
And then I can alsohave an alerting system
that lets me restock
the shop very quickly withoutme having to send someone
to see if the shop is empty.
So that's just for logistics.
If we go into, for example,the space optimization,
now with computer vision, wecan look at the whole store
(05:45):
and we can have a heat mapof what, which are the areas
that people visit the mostbecause of the layout or maybe
because of the type ofbrand that I put there.
And with all this knowledgethen I can, for example,
during Q4, when it's the highseason, for certain stores,
I can put the best brands, right?
Or I can a adjust the rent,let's say as a retailer,
the rent or the, you know, the fees
(06:06):
or what I offer to myvendor according to this.
So there's lots of things, or for example
in when we see queues, long queues,
and that is really somethingthat we want to avoid, right?
We can look at this and instead
of having three checkoutpoints, we can say, "Okay,
now there's more people,so let's open three more."
So these kind of solutionsis what we are trying
to help out with.
(06:28):
- Absolutely.
And I just think about some
of the more advanced technology
or solutions in my everydaylife, it just becomes norm.
I don't even think aboutthings that I'm using.
So I can't wait to see untilthat becomes more mainstream
and more adoptive across retail stores.
I don't think workers willreally even think of it.
It is just going to becomea new way of working.
But of course there's alot of complex technology
(06:50):
and things that go intomaking that happen.
Some of the other keywords out there, AI
computer vision and edge computing.
You touched on computervision a little bit,
but I'm curious, what are the roles
of these advanced technologies?
How are they playing in these solutions
and making retail really smart retail?
- Yeah, I think theseare all technologies,
so AI, computer vision, edge computing,
(07:11):
they're all technologies behind something.
So it's more of a horizontal.
So when I say this is for example,
AI can help the engagement of customers
because nowadays we see
that stores right are notreally a place just to purchase,
but more of a customer experience,a brand experience space.
So in that aspect, we have seenthings like digital signage
that is targeting the audience.
(07:32):
When I see that, for example,there's a group of people
that is around this age, they're male
or female, I can instantlyshow them something
that is targeted to them
or even do interactive,kind of ask them questions.
So this is what AI is doing now,
is analyzing the situationreal time and giving feedback
and interacting with customers.
As something more behindthe scenes that AI is doing,
it's for example, analyzing data.
(07:53):
So when we, AI works based on data, so
as if we have more data,sometimes in the past we had data
but we didn't know what to do with it.
Now what AI is doing isanalyzing this so that over time,
over years and months, I canunderstand what the behavior
of my audience is in this area as opposed
to another district in the country.
(08:14):
So, and adjust the say thestock according to this.
Computer vision is very interesting
because also it's a horizontal
technology where I can applyit for example, for recycling.
Now we see a lot
of retail grocery stores thathave the recycling machines
and they're determining what kind of
empty product we areputting into the machine
(08:35):
and giving, for example,in some cases in Europe,
they give you money back, right?
So you can spend it in thestore. Other things is security.
We're doing security with this
or doing checkout,
a checkout when someonedoesn't have a barcode
or is a product withoutbarcode is not walking back
to the produce sectionor having to weigh it.
It can use that, use computer vision
and recognize what the product is.
(08:57):
And each computer Ithink is, it's something
that allows the all thistechnology to have less latency
because if we had to moveall of this analysis back
to the cloud or back toa data center, first,
it'll take a long time and consumes a lot
of power and also data.
So what without having to goback to the central network,
(09:20):
we are doing this computein a distributed way,
even when there's no internetfor example, it's down
for a few hours, I can evendo this, I continue to use it
and then when I'm back on thenetwork I can also update new
features, et cetera.
- It's amazing when youthink about the data aspect
that you just mentioned, I feellike a couple of years ago,
all that data that wasbeing collected, you'd have
(09:41):
to wait every quarter
or every, at the end of theyear to really analyze that data
and to be able to make changes.
And by that point a lot ofopportunity came and went.
And so with this technology,AI helping with the data,
computer vision, edgecomputing, you're able
to now make these changes in real time
when it actually matters.
And that has just been improvingthe business even more.
(10:01):
So that's great to see.
But I'm curious, how canbusinesses successfully integrate
some of these technologieswe've been talking about into
their infrastructure whenwe're talking about inventory
and end-to-end, self-checkouts,smart queues, what type
of infrastructure orinvestments are necessary
to start implementingsome of this technology
(10:22):
and these solutions?
- Right, of course thereis some investment involved
because it's a technologythat wasn't there before.
But as much as we can, wealways try to use what is there.
So for example, when youmentioned the cameras, right?
Computer vision uses cameras a lot.
We always try to use the cameras
that they already have doing security,
but we adjust them to, at the same time
(10:44):
that they're doing security,we're using the same
video stream to analyze itbehind on the on edge computer
for example, and do someanalysis afterwards.
So we are trying to reuse
what whatever infrastructureis there already.
The compute usually there is,if it's a new technology such
(11:05):
as AI or computer vision,it needs a lot of computers.
So there might be a needof putting a computer.
But many times,
many stores have their ownlittle data center if you may.
And what we can do is collectthe data in on the edge,
let's say on in the stores,pull it back into the,
these little data centers.
So all of the, the big dataanalysis is happening there
(11:27):
or is happening, whateveris decision making
or statistics is happeningafterwards there.
So we reuse these kind of things.
We don't really haveto, you know, put a lot
of hardware into it.
But yes, a lot of the newertechnology needs, for example,
some sensors or some, you know, cameras
that have certain anglesthat were not there, these,
(11:48):
or some signage for example, in order
to communicate with the customer.
So these are investments thatare, that has to be done,
but as much as we can,we try to reuse, yeah.
- That's great.
I always love the camera example
because so many businesses,
they want to make sure they're
future proofing any investments
that they do make.
And when they were purchasingthese security cameras decades
(12:10):
ago, I don't know if they imagined
that they would be beingused in these capacities.
So it's amazing to see just howmuch technology has involved
and how much we can leverage some of
that existing infrastructure
to really make thesechanges across the store.
I wanted to shift over now,
we've been talking a lotabout retail stores in general
and different solutionsthat can be applied,
(12:32):
but do you have any customer examples
or use cases you can share of businesses
that have actuallyleveraged these solutions
we've been talking about?
You know, what problemsthey were experiencing
and how the companycame in and helped them.
- Yes, yes.
I think there's one that is more
of a problem solving like you mentioned,
and the other one ismore of an enhancement.
(12:53):
I have two examples.
So the first one was a,or the, this retailer,
this grocery retailer waslooking for an automated way
to alert them of empty shelves,
especially in fresh produce area.
And because it was very manual
and they also wanted tocombine that with the pricing.
So they wanted to adjust thepricing throughout the day,
(13:13):
depending on the performanceof that product that day.
So what we did was we usedcomputer vision to first identify
what produce was on the shelf
and throughout the daywould take different images
and analysis at acertain interval in order
to determine if the level of stock.
So this would be,
you'll create an alert intheir system, central system,
(13:35):
but also for all of the operators.
So they will see, "Oh okay,I have to refill the apples
and the oranges now."
And it, without having todo this walk walking by.
And another thing that wedid based on the same AI
technology of recognition of the product,
we also automated their pricing.
So now for example, the appleswere not selling very well
(13:55):
that day and we at four o'clock we wanted
to start clearing them.
So we would automaticallychange the e-tags
on belong the apples
and change the information and the price.
So, and this the, we didthis already in several
of their stores and theyare planning to roll it out.
And so that's a good example.
(14:15):
The second example more about enhancement
and improving understandingof the customer.
This was a technologythat we developed together
with a software vendor of ours in France.
What they did is they put a sensor
and a camera in order to understand
how people interact with the products.
So a lot of brands wereinterested in this.
They also featured in oneof the biggest trade shows
(14:37):
for retail in NRF New York.
So what they were doingis they were looking at
how long do customers stand in front
of the brand, which product they pick up,
whether they look at it,how long they interact
with the product, whetherthey take, did they buy it
or whether they put it back.
So there was a lot of datathat was accumulated there
and a lot of, they got a lot
(14:57):
of interest from brands themselves
because brands want tounderstand when we launch a new
product, how does that, do people like it
or it's not such a big deal, right?
So the brands themselves weretrying to contact these people
to use the technology
but also the furnituremakers for retail stores
were very interested inoffering this to the brands.
- I love those examples,
(15:18):
especially the one aboutthe fresh produce and apples
because it showcases
how this is not onlyhappen helping businesses
and their efficiency and their operations,
but then also the customerexperience is improving as well.
They're making sure thattheir produce is always fresh
and that items are always there
when they're going to look for it.
So that's great to see.
(15:39):
You mentioned in the beginninghow ASUS works as a brain
and works with partners to get some
of these solutions in stores
and to make some of these happen.
So I'm curious about thosetypes of partnerships,
especially I should mention insight.tech
and the "insight.tech Talk"are sponsored by Intel.
But I'm curious what the valueof your Intel partnership
(16:01):
and technology is inmaking some of this happen
and additionally any otherpartners that you're working
with to make this happen.
- Right.
I think that Intel has been a
long-term partner to ASUS, right?
Even right at the beginningwhen we were just doing
consumer computers, right,laptops and because of this
long-term relationship it has really been
crucial when we, this department,
(16:22):
the IoT department was created
because I think one of theadvantages that ASUS has
and even throughoutdifficult periods where stock
or you know, supply chain wasan issue for ASUS, it wasn't
so much an of an issue
because of this relationshipand partnership.
In many cases we areone of the first people
that try out the newtechnology from Intel.
(16:43):
So we're able to implement them in a lot
of the new products that we launch.
But at the same time, I think
that Intel is a verygood partner in terms of
when they're developing something like AI,
they are doing OpenVINO™ trying
to implement these new features.
They ask ASUS to be sortof the testers of this.
And we also market it out there,
(17:05):
not just because of the partnership.
I think it's because we seeacross the board there's lots
of choices of technology andwe offer different kinds,
but we are also able to,
when we see something likeIntel coming into this space
and trying to optimize and democratize it
because it's not just aboutselling more computes,
it's about how do you makethis accessible to people.
(17:26):
We see Intel doing that a lot
and they're also verysupportive to partners.
They will for example, engageus with the end customers.
Many of the examples I gaveyou just now were actually
people from Intel that, that introduced us
and say, "Look, they tried this out,
why don't you see if that works for you?"
So there's a lot of rapportwith Intel in this aspect
(17:47):
and I think that's whatmakes a good relationship.
And I think regarding theother question, the other part
of the question that you maderegarding the partner program
that we run, I, I always saythat in IoT it's very difficult
to do something on your own
because it's, how you haveso many components, right?
Even with the cameramakers, we see camera makers
there are optimizingtheir software in order
(18:09):
to make AI more possible, you know,
or trying to put thechip on their camera so
that it's easier for the edgecomputer to analyze more data.
So we're seeing that there'sa very good collaboration
and everybody understands this,
that without a partnership it'shard to do everything alone.
So we are, we created thispartner core program as a way to,
we do a lot of marketingand a lot of validation,
(18:31):
but apart from this it really is a space
where you can exchange projects
and you introduce each other
to different customers and projects.
- Yeah, that's great.
That's an ongoing theme at insight.tech.
This idea of better together
and working with other partners
that no one company cando it all themselves.
I think that would be very difficult
and the solutions that retailers
(18:51):
or end users would get wouldbe very expensive, you know,
and take a lot long time toupdate or to really work through
or do more advancements.
So it's great to hear companies like Intel
and ASUS working togetherwith other partners
to make this possible.
You know, this sounds likeeven though we've been talking
about smart retail fora couple of years now,
we still have a long way to go
and we're only at the beginning of it
(19:13):
and not all of these thingsare being implemented yet.
So I'm curious, how doyou anticipate this space
to continue to evolve?
Technology gets more advanced,you make more partnerships.
Where do you think smart retail's going?
- Right, it's a broad questionand yeah, I wish I knew more,
but I will try to guess.
I think that one of the thing is
(19:33):
that we will see a lot moreautomation of the operations.
Like we mentioned first when we started.
Second is that,
as I said, we will see peoplehaving more meaningful roles,
more, more interesting jobs.
Let's say that it will bemanaging systems, right?
And also I think that a lot of the brands
(19:53):
and a lot of the retail spaces will be
become showrooms really.
It won't be just for,you know, to buy things.
And I would even dare to saythat to that some of the spaces
you would just place ordersand it'll ship to your home.
You don't even have towait for the clerk to go
and get this right size foryou to, you know, it'll be more
(20:13):
of a showroom, a tryout room.
Other things is we are seeinga lot of interactive devices
and kiosks and AI will help with this.
So it will help with theproblem of having enough staff
to attend to all of the guests.
So you will be able tointeract with the screens,
with devices in a easier way.
(20:35):
We are seeing a lot ofvoice AI for example
that is very accurate,even has accents and slang.
So a lot of that coming up.
Also I think the,
what you see it sometimesin for Asia there's a,
this obsession for makingthings faster and more seamless.
Right?
And I think that will be something
that will expand across the world.
(20:56):
It will be making theexperience more seamless
and waiting for less time
and having a nice experienceinstead of this, you know,
waiting times, yeah.
- Yeah, that's one thing thatthat customers with technology
is implemented don't take welltoo is when the technology
doesn't work or when they haveto wait for the technology.
- Yeah.- But we'll have to come
(21:17):
back in a couple of years
and re-listen to thispodcast to see if any
of these predictions were right.
But I can definitely,
definitely guarantee more meaningful roles
for workers is definitely going to be
something that comes out
of this and more meaningfulcustomer interactions
and customer experiences because of this.
So that's great to hear.We are running out of time.
(21:38):
So before we go, I justwanted to throw it back
to you one last time.
If there's any key takeaways
or final thoughts you want to
leave our listeners with today?
- Yeah, I think I want to doa sort of a call to anyone
that is a solution provider, right?
That think that they would benefit from
partnering with a ASUS,feel free to reach out.
- Absolutely.
(21:59):
And for those who want to learn more about
what ASUS is doing in this space
or how smart retail isgoing to continue to evolve,
I encourage you to visit insight.tech
where we continue
to cover ASUS and otherpartners in this space.
So thank you Silvia for joining.
It's been a great conversation.
Thanks to our listenersfor tuning in today.
Until next time, this hasbeen "insight.tech Talk".
(22:21):
(upbeat music)
(upbeat music)
- Hello and welcome to"insight.tech Talk,"
where we explore the latest IoT, AI, edge
and network technologytrends and innovations.
As always, I'm yourhost, Christina Cardoza,
(00:22):
Editorial Director of insight.tech,
and today we're exploringthe world of smart retail
with Silvia Kuo from ASUS.
Hey Silvia, thanks for joining us.
- Hello. Nice to be here.
Thank you, Christina.
- Before we jump into the conversation,
what can you tell us aboutyourself and what you do at ASUS?
- Yeah, so I'm the BusinessDevelopment Director at ASUS
for the EMEA region,
(00:42):
and I basically, myjob, what I do is I look
for new projects to engage in.
I also look into what technology we should
include in those projects.
And the other thing I do isalso I run the partner program,
which is essentially lookingfor different partners
to create solutions togetherand offer them to the market.
- Great. Excited todive into some of that.
(01:03):
I know ASUS has a lot of solutions
and a lot of ways you can help retailers
or partners in this space.
But I wanted to start off the conversation
because we're talking about smart retail
and I feel like this is a keyword that has been floating
around for a couple of years now.
So when we say smart retail
and when we talk about smartretail, what do we mean?
Are retailers there yet,
or what are the challengesthat they're still facing
(01:25):
to get to smart retail?
- I think that smart retailhas been around for a while
and everyone's talking about it,
but I think that there is this, of course,
as any change, right?
There's a bit of resistance,
but there is also this imminentchange that you can feel.
And I think that the industryhas been probably trying
to look for a direction,that's my feeling,
(01:48):
but there is a lot ofinnovation that we see
and they are adopting it.
And I think that a few years from now,
retail might look a bitdifferent from what we know it,
how we know it today.
- One thing I've noticedwith smart retail,
and I've noticed ASUS standsout a little bit in this space,
is that when retailersdo their transformation,
it often happens insilos or one at a time.
(02:10):
They do self-checkoutor they do inventory.
What I love about ASUS isthe company has a range
of products from end-to-endto really go from inventory
to behavioral analyticsto space optimization.
So what can you tell us about some
of the smart retail solutions out there
and how that can help reallytransform a business from front
end to backend rather thanjust one area at a time?
(02:32):
- Right, and I think that's, you know,
the reason why we have, wehave this more comprehensive,
if you may, or holistictype of approach, is really
because of the nature ofcomputer company, right?
So we are the brain, let'ssay, behind all of this
innovation is where we, it runs.
So because of that, we have had
to look into the differentsolution as a whole.
(02:53):
So when we offer something,it's more of an end-to-end.
It's we are looking into a problem
and then seeing whatcomponents put into a solution
to solve this problem.
And that is why it'sthis holistic approach.
And I think that inretail, some of the things
that we are doing today is fall,
I think it always fallsinto two categories.
Either it is gatheringdata in order to allow
(03:17):
to analyze this data and furthermake data-driven decisions,
or is automating process.
And I think that inretail is very important
because we're seeing thatone of the main challenges is
that there's a lack of personnel
all around the world, right?
And people not wanting to do this kind
of operational routine type of jobs.
So what was happening is that
the retailers are quitedesperate in trying
(03:39):
to find a solution tomake this less costly
and also to make people be able to do job
that is more meaningful for them.
So for example, instead of, you know,
filling up the shelves, they'llbe managing systems that'll
fill up the shelves for them
or in instead of, you know, looking
and completing Excel forms tosay, "Okay, what I need to buy
for the next quarter?" it'llbe, you know, analyzing this
(04:01):
through a computer andmaking a sort of a decision,
a final decision, or reviewing that.
So this kind of managementof systems is how we see
where the industry is going.
- And I love how you put that
because I feel like a lot
of times when technology likethis comes into play, a lot
of people are worried that it'sgoing to replace their jobs
(04:22):
or what the technology is going to do,
but it sounds like it's reallytaking away the mundane tasks
and making their role more valuable
and making their position within a
retail store more valuable.
- Of course, of course.
And I, and we see that overall.
Like we see that now we wantpeople to be more engaged
and to have more meaningful,
because I think it comesalong with the introspection
(04:43):
that we as human beingshave, are becoming more
and more aware of our psychology
and you know, thingsmeaningfulness in life.
And I think the technologyallows us to explore
that side even more.
So, like you say, it's,a lot of people feel
that it's a threat,especially AI, it's going
to be a threat, replaceall of all of our jobs.
I think that it's a shift.
It is like everything, right?
(05:03):
In technology and even, you know,
the industrial revolutiontime a long time ago,
people were scared, butactually what happened is
that it improved production,it improved people's lives.
So for example, when I seelogistics, there's a lot
that we can do still in logistics.
Sometimes it's still todaythe process is very manual.
So things like trackingthe stock when it comes in:
How much do I have? Instead ofsending someone to count it,
(05:24):
then I have a systemthat can just naturally
do it quickly for me.
And then I can alsohave an alerting system
that lets me restock
the shop very quickly withoutme having to send someone
to see if the shop is empty.
So that's just for logistics.
If we go into, for example,the space optimization,
now with computer vision, wecan look at the whole store
(05:45):
and we can have a heat mapof what, which are the areas
that people visit the mostbecause of the layout or maybe
because of the type ofbrand that I put there.
And with all this knowledgethen I can, for example,
during Q4, when it's the highseason, for certain stores,
I can put the best brands, right?
Or I can a adjust the rent,let's say as a retailer,
the rent or the, you know, the fees
(06:06):
or what I offer to myvendor according to this.
So there's lots of things, or for example
in when we see queues, long queues,
and that is really somethingthat we want to avoid, right?
We can look at this and instead
of having three checkoutpoints, we can say, "Okay,
now there's more people,so let's open three more."
So these kind of solutionsis what we are trying
to help out with.
(06:28):
- Absolutely.
And I just think about some
of the more advanced technology
or solutions in my everydaylife, it just becomes norm.
I don't even think aboutthings that I'm using.
So I can't wait to see untilthat becomes more mainstream
and more adoptive across retail stores.
I don't think workers willreally even think of it.
It is just going to becomea new way of working.
But of course there's alot of complex technology
(06:50):
and things that go intomaking that happen.
Some of the other keywords out there, AI
computer vision and edge computing.
You touched on computervision a little bit,
but I'm curious, what are the roles
of these advanced technologies?
How are they playing in these solutions
and making retail really smart retail?
- Yeah, I think theseare all technologies,
so AI, computer vision, edge computing,
(07:11):
they're all technologies behind something.
So it's more of a horizontal.
So when I say this is for example,
AI can help the engagement of customers
because nowadays we see
that stores right are notreally a place just to purchase,
but more of a customer experience,a brand experience space.
So in that aspect, we have seenthings like digital signage
that is targeting the audience.
(07:32):
When I see that, for example,there's a group of people
that is around this age, they're male
or female, I can instantlyshow them something
that is targeted to them
or even do interactive,kind of ask them questions.
So this is what AI is doing now,
is analyzing the situationreal time and giving feedback
and interacting with customers.
As something more behindthe scenes that AI is doing,
it's for example, analyzing data.
(07:53):
So when we, AI works based on data, so
as if we have more data,sometimes in the past we had data
but we didn't know what to do with it.
Now what AI is doing isanalyzing this so that over time,
over years and months, I canunderstand what the behavior
of my audience is in this area as opposed
to another district in the country.
(08:14):
So, and adjust the say thestock according to this.
Computer vision is very interesting
because also it's a horizontal
technology where I can applyit for example, for recycling.
Now we see a lot
of retail grocery stores thathave the recycling machines
and they're determining what kind of
empty product we areputting into the machine
(08:35):
and giving, for example,in some cases in Europe,
they give you money back, right?
So you can spend it in thestore. Other things is security.
We're doing security with this
or doing checkout,
a checkout when someonedoesn't have a barcode
or is a product withoutbarcode is not walking back
to the produce sectionor having to weigh it.
It can use that, use computer vision
and recognize what the product is.
(08:57):
And each computer Ithink is, it's something
that allows the all thistechnology to have less latency
because if we had to moveall of this analysis back
to the cloud or back toa data center, first,
it'll take a long time and consumes a lot
of power and also data.
So what without having to goback to the central network,
(09:20):
we are doing this computein a distributed way,
even when there's no internetfor example, it's down
for a few hours, I can evendo this, I continue to use it
and then when I'm back on thenetwork I can also update new
features, et cetera.
- It's amazing when youthink about the data aspect
that you just mentioned, I feellike a couple of years ago,
all that data that wasbeing collected, you'd have
(09:41):
to wait every quarter
or every, at the end of theyear to really analyze that data
and to be able to make changes.
And by that point a lot ofopportunity came and went.
And so with this technology,AI helping with the data,
computer vision, edgecomputing, you're able
to now make these changes in real time
when it actually matters.
And that has just been improvingthe business even more.
(10:01):
So that's great to see.
But I'm curious, how canbusinesses successfully integrate
some of these technologieswe've been talking about into
their infrastructure whenwe're talking about inventory
and end-to-end, self-checkouts,smart queues, what type
of infrastructure orinvestments are necessary
to start implementingsome of this technology
(10:22):
and these solutions?
- Right, of course thereis some investment involved
because it's a technologythat wasn't there before.
But as much as we can, wealways try to use what is there.
So for example, when youmentioned the cameras, right?
Computer vision uses cameras a lot.
We always try to use the cameras
that they already have doing security,
but we adjust them to, at the same time
(10:44):
that they're doing security,we're using the same
video stream to analyze itbehind on the on edge computer
for example, and do someanalysis afterwards.
So we are trying to reuse
what whatever infrastructureis there already.
The compute usually there is,if it's a new technology such
(11:05):
as AI or computer vision,it needs a lot of computers.
So there might be a needof putting a computer.
But many times,
many stores have their ownlittle data center if you may.
And what we can do is collectthe data in on the edge,
let's say on in the stores,pull it back into the,
these little data centers.
So all of the, the big dataanalysis is happening there
(11:27):
or is happening, whateveris decision making
or statistics is happeningafterwards there.
So we reuse these kind of things.
We don't really haveto, you know, put a lot
of hardware into it.
But yes, a lot of the newertechnology needs, for example,
some sensors or some, you know, cameras
that have certain anglesthat were not there, these,
(11:48):
or some signage for example, in order
to communicate with the customer.
So these are investments thatare, that has to be done,
but as much as we can,we try to reuse, yeah.
- That's great.
I always love the camera example
because so many businesses,
they want to make sure they're
future proofing any investments
that they do make.
And when they were purchasingthese security cameras decades
(12:10):
ago, I don't know if they imagined
that they would be beingused in these capacities.
So it's amazing to see just howmuch technology has involved
and how much we can leverage some of
that existing infrastructure
to really make thesechanges across the store.
I wanted to shift over now,
we've been talking a lotabout retail stores in general
and different solutionsthat can be applied,
(12:32):
but do you have any customer examples
or use cases you can share of businesses
that have actuallyleveraged these solutions
we've been talking about?
You know, what problemsthey were experiencing
and how the companycame in and helped them.
- Yes, yes.
I think there's one that is more
of a problem solving like you mentioned,
and the other one ismore of an enhancement.
(12:53):
I have two examples.
So the first one was a,or the, this retailer,
this grocery retailer waslooking for an automated way
to alert them of empty shelves,
especially in fresh produce area.
And because it was very manual
and they also wanted tocombine that with the pricing.
So they wanted to adjust thepricing throughout the day,
(13:13):
depending on the performanceof that product that day.
So what we did was we usedcomputer vision to first identify
what produce was on the shelf
and throughout the daywould take different images
and analysis at acertain interval in order
to determine if the level of stock.
So this would be,
you'll create an alert intheir system, central system,
(13:35):
but also for all of the operators.
So they will see, "Oh okay,I have to refill the apples
and the oranges now."
And it, without having todo this walk walking by.
And another thing that wedid based on the same AI
technology of recognition of the product,
we also automated their pricing.
So now for example, the appleswere not selling very well
(13:55):
that day and we at four o'clock we wanted
to start clearing them.
So we would automaticallychange the e-tags
on belong the apples
and change the information and the price.
So, and this the, we didthis already in several
of their stores and theyare planning to roll it out.
And so that's a good example.
(14:15):
The second example more about enhancement
and improving understandingof the customer.
This was a technologythat we developed together
with a software vendor of ours in France.
What they did is they put a sensor
and a camera in order to understand
how people interact with the products.
So a lot of brands wereinterested in this.
They also featured in oneof the biggest trade shows
(14:37):
for retail in NRF New York.
So what they were doingis they were looking at
how long do customers stand in front
of the brand, which product they pick up,
whether they look at it,how long they interact
with the product, whetherthey take, did they buy it
or whether they put it back.
So there was a lot of datathat was accumulated there
and a lot of, they got a lot
(14:57):
of interest from brands themselves
because brands want tounderstand when we launch a new
product, how does that, do people like it
or it's not such a big deal, right?
So the brands themselves weretrying to contact these people
to use the technology
but also the furnituremakers for retail stores
were very interested inoffering this to the brands.
- I love those examples,
(15:18):
especially the one aboutthe fresh produce and apples
because it showcases
how this is not onlyhappen helping businesses
and their efficiency and their operations,
but then also the customerexperience is improving as well.
They're making sure thattheir produce is always fresh
and that items are always there
when they're going to look for it.
So that's great to see.
(15:39):
You mentioned in the beginninghow ASUS works as a brain
and works with partners to get some
of these solutions in stores
and to make some of these happen.
So I'm curious about thosetypes of partnerships,
especially I should mention insight.tech
and the "insight.tech Talk"are sponsored by Intel.
But I'm curious what the valueof your Intel partnership
(16:01):
and technology is inmaking some of this happen
and additionally any otherpartners that you're working
with to make this happen.
- Right.
I think that Intel has been a
long-term partner to ASUS, right?
Even right at the beginningwhen we were just doing
consumer computers, right,laptops and because of this
long-term relationship it has really been
crucial when we, this department,
(16:22):
the IoT department was created
because I think one of theadvantages that ASUS has
and even throughoutdifficult periods where stock
or you know, supply chain wasan issue for ASUS, it wasn't
so much an of an issue
because of this relationshipand partnership.
In many cases we areone of the first people
that try out the newtechnology from Intel.
(16:43):
So we're able to implement them in a lot
of the new products that we launch.
But at the same time, I think
that Intel is a verygood partner in terms of
when they're developing something like AI,
they are doing OpenVINO™ trying
to implement these new features.
They ask ASUS to be sortof the testers of this.
And we also market it out there,
(17:05):
not just because of the partnership.
I think it's because we seeacross the board there's lots
of choices of technology andwe offer different kinds,
but we are also able to,
when we see something likeIntel coming into this space
and trying to optimize and democratize it
because it's not just aboutselling more computes,
it's about how do you makethis accessible to people.
(17:26):
We see Intel doing that a lot
and they're also verysupportive to partners.
They will for example, engageus with the end customers.
Many of the examples I gaveyou just now were actually
people from Intel that, that introduced us
and say, "Look, they tried this out,
why don't you see if that works for you?"
So there's a lot of rapportwith Intel in this aspect
(17:47):
and I think that's whatmakes a good relationship.
And I think regarding theother question, the other part
of the question that you maderegarding the partner program
that we run, I, I always saythat in IoT it's very difficult
to do something on your own
because it's, how you haveso many components, right?
Even with the cameramakers, we see camera makers
there are optimizingtheir software in order
(18:09):
to make AI more possible, you know,
or trying to put thechip on their camera so
that it's easier for the edgecomputer to analyze more data.
So we're seeing that there'sa very good collaboration
and everybody understands this,
that without a partnership it'shard to do everything alone.
So we are, we created thispartner core program as a way to,
we do a lot of marketingand a lot of validation,
(18:31):
but apart from this it really is a space
where you can exchange projects
and you introduce each other
to different customers and projects.
- Yeah, that's great.
That's an ongoing theme at insight.tech.
This idea of better together
and working with other partners
that no one company cando it all themselves.
I think that would be very difficult
and the solutions that retailers
(18:51):
or end users would get wouldbe very expensive, you know,
and take a lot long time toupdate or to really work through
or do more advancements.
So it's great to hear companies like Intel
and ASUS working togetherwith other partners
to make this possible.
You know, this sounds likeeven though we've been talking
about smart retail fora couple of years now,
we still have a long way to go
and we're only at the beginning of it
(19:13):
and not all of these thingsare being implemented yet.
So I'm curious, how doyou anticipate this space
to continue to evolve?
Technology gets more advanced,you make more partnerships.
Where do you think smart retail's going?
- Right, it's a broad questionand yeah, I wish I knew more,
but I will try to guess.
I think that one of the thing is
(19:33):
that we will see a lot moreautomation of the operations.
Like we mentioned first when we started.
Second is that,
as I said, we will see peoplehaving more meaningful roles,
more, more interesting jobs.
Let's say that it will bemanaging systems, right?
And also I think that a lot of the brands
(19:53):
and a lot of the retail spaces will be
become showrooms really.
It won't be just for,you know, to buy things.
And I would even dare to saythat to that some of the spaces
you would just place ordersand it'll ship to your home.
You don't even have towait for the clerk to go
and get this right size foryou to, you know, it'll be more
(20:13):
of a showroom, a tryout room.
Other things is we are seeinga lot of interactive devices
and kiosks and AI will help with this.
So it will help with theproblem of having enough staff
to attend to all of the guests.
So you will be able tointeract with the screens,
with devices in a easier way.
(20:35):
We are seeing a lot ofvoice AI for example
that is very accurate,even has accents and slang.
So a lot of that coming up.
Also I think the,
what you see it sometimesin for Asia there's a,
this obsession for makingthings faster and more seamless.
Right?
And I think that will be something
that will expand across the world.
(20:56):
It will be making theexperience more seamless
and waiting for less time
and having a nice experienceinstead of this, you know,
waiting times, yeah.
- Yeah, that's one thing thatthat customers with technology
is implemented don't take welltoo is when the technology
doesn't work or when they haveto wait for the technology.
- Yeah.- But we'll have to come
(21:17):
back in a couple of years
and re-listen to thispodcast to see if any
of these predictions were right.
But I can definitely,
definitely guarantee more meaningful roles
for workers is definitely going to be
something that comes out
of this and more meaningfulcustomer interactions
and customer experiences because of this.
So that's great to hear.We are running out of time.
(21:38):
So before we go, I justwanted to throw it back
to you one last time.
If there's any key takeaways
or final thoughts you want to
leave our listeners with today?
- Yeah, I think I want to doa sort of a call to anyone
that is a solution provider, right?
That think that they would benefit from
partnering with a ASUS,feel free to reach out.
- Absolutely.
(21:59):
And for those who want to learn more about
what ASUS is doing in this space
or how smart retail isgoing to continue to evolve,
I encourage you to visit insight.tech
where we continue
to cover ASUS and otherpartners in this space.
So thank you Silvia for joining.
It's been a great conversation.
Thanks to our listenersfor tuning in today.
Until next time, this hasbeen "insight.tech Talk".
(22:21):
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