Our guide in this episode is retail technology publisher, author and consultant Miya Knights. She talks to Gordon and Ger about how the use of cutting-edge technology can put the retail experience in service of the customer.
Miya discusses three vital customer considerations that retailers (and retail tech) need to address in order to be successful.
But that's only the half of it. She also talks about how technology is helping retailers answer key questions about their customers and their products.This is literally the hottest episode so far—there was no air conditioning in the studio. Listen to find out whether Ger or Gordon succumbs to the heat first.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:01):
This is Functional & Fabulous, the omnichannel podcast where we unbox tales of online retail and digital transformation.
In this episode, Ger goes in search of questions...
Great, we have all the big data, but what questions are we trying to answer?
Our guest has the questions...
What do they look like?
Where do they live?
(00:21):
How often do they shop with me?
What is it that they like?
And then I'm going to use that information to give them more of what they want.
The Functional & Fabulous soapbox racing team is born...
Can we, for a second, just talk about Dash Carts?
You're thinking about getting into one and being pushed down a hill.
Gordon describes Dash Cart propulsion...
(00:42):
Massive shoulders and big arms.
Ger questions his hearing...
What is a body buddy?
Did I hear that correctly?
And the real threat of AI is exposed...
You feel all of a sudden kind of, like, shamed by an AI because you've no idea what it's talking about.
This episode of Functional & Fabulous is brought to you with pride by StudioForty9, retail ecommerce experts, omni-channel growth consultants and cut-through performance marketing specialists.
(01:12):
StudioForty9, where your digital retail success is built.
Hello and welcome to Functional & Fabulous, the omnichannel ecommerce podcast.
We're delighted to welcome our guest today, Miya Knights.
Miya is a retail tech publisher, an occasional author, and a consultant and advisor.
She has over 25 years' experience specialising in enterprise technology use in retail.
(01:35):
And she spent this time covering and analysing the demands and challenges faced by retailers to identify the technologies that best support their needs as consumer expectations and behaviours become ever more complex.
It's always good to speak to someone who has written the book on a topic.
And in this case, Miya has co-authored two books that are extremely relevant to our subject matter.
(01:58):
Omnichannel Retail, How to Build Winning Stores In A Digital World with Tim Mason, the CEO of Eagle Eye and former Deputy CEO of Tesco PLC.
And Amazon (02:06):
How The World's Most Relentless Retailer Will Continue To Revolutionize Commerce, co-authored with Natalie Berg.
Miya, it's so lovely to have you here with us today.
Lovely to be here, Ger.
Lovely to be here.
Thank you so much for having me.
Welcome to the podcast.
It's great to be able to talk to you today.
We're really looking forward to it.
(02:28):
Likewise, Gordon.
Thank you so much, both of you, for having me.
So Miya, as someone who has written a book on Amazon, I guess you hear people make much ado about the potential end of Amazon whenever they have a stutter or a misstep.
And I've heard you say, you know, it's not the end, but only the beginning of the end of day one.
(02:48):
Would you elaborate a little bit on what you mean by that?
Oh gosh, that's a great question, but to unpack it and answer it, I have to probably give a bit of context, don't I, for your listeners?
So Jeff Bezos famously wrote in a shareholder's letter that in order to be disruptive, to maintain the position in the industry that they have attained and be as disruptive as they have been in the past, and also remain nimble and agile enough to be disruptive and innovative, that they must treat every day that they come into work as though it was day one, the first day in the company.
(03:28):
And so it's become kind of a bit of a term for referring to them as being disruptors and innovators.
And I think, you know, we've seen just, you know, on one half, Amazon is a tech firm.
On another, on the other hand, it's a retailer.
And we've seen both sectors fare differently through the last three or four years, through the pandemic.
(03:54):
We've seen big tech squeezed quite heavily as we've sort of come out of the pandemic and they perhaps, you know, overhired a little bit, and their ranks swelled and their spending swelled through the pandemic to meet demand for everything going online and our appetites growing for digital.
(04:15):
But at the same time, you know, it's being a tech company first, as I'm always saying, a retailer second, it's also really been able to use that tech savvy digital know-how to turbocharge its retail business and do really, really well as a retailer.
So we've seen traditional bits of its business that have been growth engines like its cloud services business, AWS, continue to grow, although growth is now slowing as adoption grows worldwide and competition increases.
(04:46):
And on the retail side, we've seen them grow their advertising business hugely from a profit perspective.
It's got massive margins.
So it's done really, really well there, but it's also been caught out with too much warehouse space, too many staff.
It's having to kill off areas like Alexa or at least slim them down, trim them down.
(05:08):
Maybe it's not learning as fast as it used to or failing as fast as it used to.
The experience, even though, you know, the ads business is great for shareholder news and investor coverage, but, you know, it doesn't actually make the experience a lot better for our consumers.
I think the jury is out on whether or not these ads are actually going to add value.
(05:31):
So in terms of Amazon being able to pivot, be an innovator, be a disruptor, really tune into what the customer wants and reflect it really quickly in their front end, you know, marketplace, Amazon.com and prime businesses.
They're starting to slow down a little bit.
I think the last couple of things that sort of are challenges and have been perennial ongoing challenges have been getting into food and getting into fashion.
(05:55):
I mean, they're still a massive apparel retailer, particularly in the States, they're the number one.
But luxury fashion, they're still trying to, you know, struggling to penetrate.
The likes of Shein, for example, you know, adjacent, so they're not necessarily competing against each other.
But when you think about that fast-fashion side, you can buy a t-shirt from Amazon, buy some jogging bottoms from Amazon, but you wouldn't necessarily go out and buy a party dress or dress shirt from Amazon necessarily, unless the brand already sells.
(06:27):
So there are all these headwinds, as well as the policy and regulation one, which we should always mention, that means that it might not quite be end of day one for Amazon, but I believe it's sun setting and we're starting to see Amazon, the mature retailer and tech company, head into its day two phase.
Such a clear answer to my question, actually.
(06:49):
You know, we've thought about this idea of how a large innovative company, how do you manage to generate or continuously generate that innovation on an ongoing basis, in particular from within the company?
And obviously there comes a point where things start to slow down a little bit, or there's a reinvigoration or maybe a sunset of some portions of it for a sunrise the next day.
(07:10):
They made a lot, like they made much ado about going into grocery in the States and in the UK, and obviously in the States, Whole Foods was a very strategic purchase.
But the business there seems to have abated quite a bit as well.
They were quite bullish going into it.
In some cases, they probably wrote the PR before they actually succeeded in the area.
(07:33):
How do you find that?
Do you think that that's a true statement?
Yeah, that's a fair, that's a fair estimation of where they are.
I mean, again, let's set some context, you know, Amazon's a massive retailer in everything that's non-food, but we spend 40% of all retail spend is food.
It's the biggest category and they want to see what we buy food.
(07:57):
I mean, when you think about the advantages that grocers have from the perspective of that digital pandemic, turbocharged pandemic, digital demand, they have frequency.
You know, they see who's a young family, who's grandparents, who likes to buy Babycham at Christmas, all of these kinds of nuances of our shopping habits.
(08:19):
And I think Amazon has the ability to see everything else apart from that.
And it's a missing piece when you talk about omnichannel, for example, getting that 360 degree view of the customer is not just where they shop with you, but also what they shop with you.
I mean, it doesn't necessarily mean that as a shirt retailer, you're going to want to know my inside leg measurement, but at the same time, it pays to have that, you know, I suppose as detailed a view of who is buying from you so that you can give them more of what they want, you know, infer what they want before they want.
(08:51):
So Amazon's ambitions in grocery are clear in terms of the benefits that they're looking to gain, 40% of our spend and 40% of everything we buy knowing how we do that.
The acquisition of Whole Foods has been seen as a bit of a damp squib.
I do believe Amazon, being a tech company first and a retailer second, has had to learn how to retail along the way.
(09:14):
And grocery is one of those, it's probably the hardest, the hardest sector to get into.
America, it's very fragmented.
You've got a lot of regional banners.
In Britain, it's one of the most fiercely competitive and consolidated markets.
Were they overconfident in their ability?
You know, I mean, Amazon, obviously, they've been enormously successful.
(09:37):
But as you say, grocery is really challenging.
Yeah, I'd like, it would be great to get your opinion, Miya, on whether you think that that's because they didn't have the technology right or what is the reason that this has underdelivered?
And is it, as you say, down to their retail skill set?
(10:01):
I think that's largely got, that's got a lot to do with it.
I mean, when you're talking about the retail skill set, let's deal with that first.
You know, they don't have a brand that's known and trusted for food.
I don't think the proposition, you know, they didn't necessarily... Whole Foods wasn't the best one, the grocer in the world.
They inherited some inventory systems that weren't great.
(10:23):
So retrofitting core retail systems, which they didn't really have to build in for a store environment into Whole Foods, was, I think, from a due diligence perspective, something they potentially overlooked.
And I think what a good way of thinking about it perhaps is that Amazon sees stores the way that traditional store-based retailers sees online, saw online 10 to 15 years ago.
(10:50):
You know, it's something over there, we can operate it as a different, in terms of the integration of Whole Foods, the spinning out of innovation into Whole Foods and retail skills and savvy back into Amazon.
I don't think that integration happened as quickly or as well as it should, as quickly as it should have, as well as it should have.
And they underestimated how much retrofitting they would need to do to Whole Foods to get it up to the same kind of spec and standards as Amazon was running its own retail businesses.
(11:20):
And then on the other hand, the things that they wanted to do from a test-and-learn perspective with Whole Foods that we now see in their Just Walk Out technology in their Amazon Go format stores is the price point.
It's just, it's one of those things where I hesitate to say it's technology waiting for a problem to solve.
(11:42):
It really isn't.
But it's like, I was having this conversation earlier and saying to somebody else, it's like where RFID was seven to 10 years ago in terms of business case ROI.
And that's got a lot to do with just the cost of the tech.
So they were very innovative, very disruptive.
I think the technology has absolute application legs beyond, you know, this is the way forward for shopping in stores.
(12:06):
We don't need tills anymore.
They've proven it.
It eliminates shrink.
You know who's coming into your store.
You can match the digital identity to the human physical shopping trip, for example.
But the cost of doing it has really limited them.
So that's why we see it only rolled out to local and convenience-type formats with smaller footprints.
(12:27):
You know, they're experimenting with I'm answering your question about food, but, you know, they've started to think about how to do this in department store environments as well, how to modernise, disrupt, remove friction from the store-buying experience.
But the technology that they've come up with is proving really, really difficult to scale quickly.
(12:49):
But the final thing I'll say on grocery is I would say instead of watching what has happened with Whole Foods, watch what they're doing with their own banners, and the Amazon grocery stores that they are now rolling out in America have the new redesigned Dash Cart, which allows for one bigger buy.
So bigger format stores, bigger ranges, which allows them to start to build that brand cachet around the actual shopping experience.
(13:17):
What brands do you have?
Do you have what I'm looking for?
You know, it's not just like a UK Morrison's groceries.
I have a choice.
I have local brands and I have Amazon own brands and I have other premium brands as well.
That's what customers are used to.
That's what they're looking for.
So you need the bigger format stores to do that.
Dash Cart's getting them there, although I am seeing some interesting competitors coming out with systems that you retrofit to shopping trolleys that could compete head-to-head with them.
(13:47):
It's not buying tech from Amazon, which means necessarily giving away all your data as well, sharing all your data as well.
Miya, for those people who are listening that aren't familiar, could you just give us a headline of what a Dash Cart is?
Oh, so the Dash Cart is, so the Just Walk Out technology that's in Go stores uses computer vision and shelf-sensing technology to basically track you in an anonymised way around the store.
(14:14):
And when you pick something off the shelf and put it in your bag and walk out with it, you're automatically charged.
The Dash Cart does exactly that, but in a shopping trolley form.
So it's like all the cameras and all the sensors are in the trolley.
So as you drop something in the trolley, that's the cue for the artificial intelligence systems to log it as something that's gone into your basket.
(14:34):
And as you leave the store, that's the cue for it to charge your payment instrument that you've registered to the app.
Got it.
So in convenience, it's looking at the shelves, in the larger formats, it's in the trolley.
Well, I think, you know, they'll certainly have the computer vision and sensing technology in the bigger format stores as well, because you've got bigger basket shops, you know, just belt and braces, I think.
(14:59):
But the Dash Cart is the point at which all that stuff's tallied.
And because it's a bigger shop, it allows them to give you a screen that gives you a running total, which you're more familiar with the scanning guns in supermarkets now as well.
It gives them that sort of digital media capability as well because you're pushing the cart rather than just, you know, putting stuff in a bag and walking out from a convenience perspective.
(15:22):
And tot up your multi-buy discounts as we all like to do as we're running around certain supermarkets with our Scan & Go guns.
With online, the lower the touch, the more tools you need to try and bridge the gap digitally.
And I've certainly seen situations where retailers are trying to deliver totally seamless and frictionless services, or at least that's the aim.
(15:43):
But then they're surprised by the planning effort and technology involved.
And it's almost, you know, when you were talking about Amazon and its experience in retail and retrofitting to Whole Foods and all of that, it was almost like the reverse version of it in a way.
But looking to online, you know, do you find that that's the case?
(16:03):
The more that people are trying to make these things seamless, you know, the more surprised sometimes they are by how complex that can be, you know, and how difficult sometimes it is to keep things simple.
Yes, I would say to answer your question twofold, let's break down what people are looking for from the online experience.
We've been doing it long enough now to kind of start boiling it down to some essential tenets, and then how retailers can deliver on that.
(16:29):
I think the essential tenets are, particularly now, from a give-to-get dynamic perspective when we're talking about digital and the footprint that we leave, and the click streams that we create, and the data that we therefore share, and the information we infer through that data that we then share with the retailer.
There is, I think, the overarching thing now, particularly from an omnichannel perspective, is recognise and reward me for my continued custom.
(16:54):
Don't treat me like I'm a one-time anonymous customer.
So make it worth my while to log in, make it worth my while to identify myself when I'm in store.
When I'm there, even if I'm not a regular customer of yours and I'm not on your loyalty scheme like that, I'm not logged in, but I'm just browsing, the search, browse and discovery phases of a shopping journey now have to be get me to what I'm looking for as quickly as possible.
(17:17):
Don't make it difficult for me to find what I'm looking for.
And then the final third tenet has to be, once I've found it, give me the confidence to buy something that I know is going to be what I want.
And that there becomes again, where the data can really help infer what is the mission?
What's the real value?
Is it speed?
Is it quality?
Is it quantity?
(17:38):
What is it about this person that I already know from their shopping habits, known or unknown that they've shared with me that can help me get to that, bridge that conversion gap.
You know, we can talk about fashion, we can talk about returns.
You know, why are people buying three sizes of something when if you could show them that it would fit them, give them the confidence that it would fit them, they'd buy one size?
(18:01):
So it's that, it's that I try and that's what people come to me for.
They try, for me to boil these things down and it is recognise and reward me, help me find what I'm looking for as quickly as possible and give me the confidence to buy it, knowing that it has the value that you tell me it has.
And that then you get into a whole sort of discussion about brand value and purpose and sustainability and fast versus slow deliveries.
(18:22):
But there are so many different ways that you can do that, meet those three demands that I think the last 15 years have been characterised by retailers going, well, I'll just buy an ecommerce platform, slap that in and it should do it all.
But when you are now talking about recognise and reward me, you're talking about loyalty, linked to, you know, maybe payment system, payment delivery, location, inferences from data points from customers.
(18:54):
When you're talking about search, browse, discovery, you really are talking about shop attainment, you're talking about video, you're talking about embedding video.
Are you making your video on your mobile app shoppable?
Are you using something like the Zara store app where I can nominate my favourite three shops where you'll make the inventory available to me if I could collect in an hour?
(19:14):
And that then bleeds into, you know, at the end, am I using something like AfterShip or Quiver to make sure I'm offering you a slow delivery or make sure that I'm giving you step-by-step your product is five steps away, much as less as just before that we talked about, you know, am I using an AR fitting tool?
Am I using, you know, body buddies?
(19:36):
Am I using video?
Am I using live streaming from the conversion consideration set perspective?
So all of these little but significant components need to be bolted onto these systems.
And I think I see what's happening to sort of round up what's probably a really long response to your question again, but is that these amorphous e-com platforms can't quite keep up.
(20:01):
And we're seeing that that's, you know, it's platform play versus best of breed, right?
It's always been the way.
And right now, platform is holding a lot of retailers.
For me, this is super interesting because on the one hand, you have this tech giant, Amazon, building its own tech and implementing that from, into physical environments.
(20:24):
And some retailers may look overwhelmed.
And I noticed from your Twitter feed, there was a great quote from Régis Schultz, the CEO of JD Sports saying, don't do code.
We do stores and customer experience.
Let the tech companies do the code.
(20:47):
And you gave that one a high five.
And that resonated with me when I saw it, because this is an overwhelming level of capability for a retailer to try and take on and build.
And I think, I can't remember how many applications you just referenced in that couple of minutes, but there's a lot in that stack.
(21:11):
And it kind of leads me in to ask you a little bit more about that of, how do you build that kind of best of breed versus flexible components?
How do retailers even start thinking about this?
Well, I mean, I've been doing this, I hate to admit it, over 25 years.
And just at the time when sort of POS was moving from clients or moving to client server, and then subsequently we've moved, sort of moved it up to the cloud.
(21:40):
If you're at the bleeding edge, there are some retailers that have 37-year-old POSs, shall remain unnamed.
And they are really proving huge barriers to innovation.
So we're talking the e-com platform now kind of taking the place of the POS platform in stores and becoming the barrier to innovation.
And back then it was all best-of-breed.
(22:01):
I want best-of-breed everything.
And then they realised they couldn't sew it all together.
And then you had Oracle, SAP, Microsoft, Salesforce, come in and say, well, you're buying the databases off of us.
You're buying your IBM X, whatever it might be.
Why not?
I've got some applications.
We've got all the money to throw at verticalising this, buying up all of these vertical applications and locking you in.
(22:25):
And so retailers at that time, I think, through the 90s and the early noughties, were like, yeah, all right, I have a bit of SAP.
I'll have a bit of, you know.
And they were quite happy at that time because I think the pace of innovation, the pace of changing consumer demand hadn't become turbocharged by digital quite as much then.
And so they were in a position where they could say, yeah, three to five years for ROI.
(22:47):
That's fine.
I'll take that.
And it's just sped up.
So what I'm seeing now is a little bit of a hybrid where they have got these systems of record that are owned by the big platform, big tech players.
And I always say omnichannel should be three systems of main record.
And that should be as near real-time for all of them.
Your, where's your stock?
(23:08):
And you don't necessarily need to know where it is at that moment, just when it moves.
I want to know when it moves.
If it's gone from a warehouse to a store or it's on a truck or I've handed it to a customer.
Those are the main points that you need to know where it is.
So that's stock/inventory.
Then you need to know who your customers are.
However you do that, you might need a loyalty scheme, might not.
(23:31):
And three, you need to know what you're selling.
And that might be sales and orders.
And so we've seen, again, you know, one of the big ones, people sorted out their POS systems.
Then they put an e-con systems.
They were doing telematics in the background, maybe 10, 15 years ago.
Order management.
When I was at IDC, it was an order management system.
I need to do click and collect.
I need to put my store systems onto my e-con systems.
(23:53):
And now you're trying to get retailers kind of going for, you know, sales and orders coming from one stock pool and dynamic orchestration and predictive analytics, where to keep my stock, for example.
So they still need those three systems of record, right?
But what's emerging on top from a best-of-breed perspective, I would say maybe, oh I'm going to sound like I've drunk the Kool-Aid, but the best iteration of this I've seen so far is composable commerce.
(24:20):
Throw a few buzzwords at you there.
And, you know, I think it's typified by the work that's being done by the Mac Alliance.
So I work quite closely with a mobile app, native mobile app firm called PopCommerce.
They would hate me if I didn't actually name them, who onboarded to the MACH Alliance in 2021.
So I got to look under the covers and see what the MACH Alliance needed for this vendor to join this members of members association.
(24:43):
And they literally have to show their code.
They have to work on blueprints integration.
And the MACH Alliance essentially stands for, and then I'll sort of hopefully finish answering your question in terms of having that platform systems of record, but hot swappable composable components on the top from the customer-facing perspective that gives you that agility, is that they are all microservices written in microservices with API first cloud native and headless capabilities.
(25:13):
So that's what the MACH stands for.
And I ded appreciate that the MACH Alliance doesn't just go, yeah, give us your subscription money.
We'll slap your logo on stuff.
You have to go through quite a rigorous assessment process with the existing members on their technical council.
And Google's only just been on boarded.
For example, Google has only just joined the MACH Alliance.
(25:35):
I think companies like Salesforce and Oracle will struggle to prove that they can join the MACH Alliance.
And that's a good test.
So whether something is MACH-enabled and allows that level of composability on the front end, while you manage the systems of record on the back end, I think is the happy medium that we're converging towards now.
(25:55):
Okay, so I suppose you could kind of, I've got to simplify it for my own understanding a bit here.
So it's kind of, like, those systems of record, they're our foundations and they're the bits that stay constant.
And then you can use, or retailers can then build experiences using composable elements to bring that experience to life for the customer.
(26:24):
And that's how they can they can access the technology and also differentiate through the mix of technology.
That's, that's right for them and their customer.
If I've understood what you're saying correctly.
Yeah, exactly that.
Thank you for simplifying it for me.
Absolutely.
No, no, no.
You're absolutely right.
That's exactly how it should work, I think.
I think, you know, it was interesting, that Régis Schultz quote, he actually started off by saying, you know, it took them back and forth with their e-con provider about whether or not they needed a persistent basket.
(26:54):
Yeah, it's questions.
It's questions like that that take too long to answer.
Whereas if you're evaluating a new e-com platform, you can ask that question of three or four different MACH-enabled providers and get the answer, you know, and choose the answer that best suits you because you're the retailer.
You don't necessarily necessarily know what persistent basket means, but if they can explain to you what it means and you know your customer and you know the way they shop and you know what kind of business model, operating model you want to create online, then you can meet in the middle.
(27:26):
So it makes those kinds of conversations a little bit clearer, a little bit easier.
You know, all of the big-platform guys will make sure that they have an API layer that you can use and hook these things into.
But it's, it's, it's things like dynamic search.
It's things like, you know, if I want to just swap out, so an unnamed retailer is currently migrating from ATG, which was bought by IBM years ago and is unsupported.
(27:50):
It's no longer supported.
They're running their entire e-com business and they're a former catalogue business.
They don't actually have that many stores on something that's end-of-life, something that's no longer supported simply because the operational risk of swapping that out right now is too big.
So the idea is that
they could move to,
you know, I'll try and be fair,
(28:11):
you know, you've got Shopify,
BigCommerce, Fluent Commerce,
all of these other e-commerce,
MACH-enabled systems
of ecommerce systems
more, more quickly,
more easily without disrupting
necessarily the plumbing underneath
the systems of record underneath
and having more business-focused
and outcome-focused conversations
(28:31):
rather than, you know,
getting mired in technical diagrams
and, you know, months,
let alone years to,
to seeing returns and some value
working that incremental
sort of way of getting quick...
I have a question in that area, Miya, the, you know, I've often heard people speak of the desire to make data-driven decisions based on the 360-degree view of the customer.
(28:54):
And you've mentioned that earlier.
Do you feel like the knowledge and education is in the industry to leverage the potential of the tech that is available?
And if not, what would you do about it or what do you think can be done about it?
That's a really good question, Ger.
One large UK department store has only just taken on a head of customer data.
(29:17):
Only just.
Has only just launched a loyalty factor scheme, you can probably infer which one it is...
So, you know, strategically, are they ready?
Some not.
I think those that have had loyalty schemes, we've seen them double down on them and also maybe flatten them out a little bit in terms of their value, just from the cost-of-living crisis perspective.
(29:44):
And I think they're probably, you know, they've got first-move advantage.
They kind of, they already understand the power of customer data.
And so they are, you know, the grocers, they're launching retail media networks.
You know, they're miles ahead.
I think the non-food guys are kind of just looking at marketplaces, that kind of thing, trying to get, they know they've got the eyeballs.
(30:05):
How can I make my site more sticky?
How can I start to join up my store, my view of customers in stores and my view of what they do online?
I would say the big buzzword in regards to customer data is CDPs, customer data platforms.
Do I need one?
(30:26):
Well, do I know what I'm going to do with it if I had one?
If I had one, what would I do?
Well, if you had one, what would you do with it?
Well, I think sometimes that question, there's a question of almost diving to the selection of a CDP ahead of the strategy around what would we do with it.
(30:48):
It's kind of like the famous thing with big data.
Great, we have all the big data, but what questions are we trying to answer?
Exactly.
So we talked about big data, now we're talking about AI, aren't we, from that perspective?
And I hear retailers all the time say that they're drowning in data.
So you raise a very, very good point there.
And I would suggest that you're drowning in data because you don't know what to ask of it.
(31:11):
Again, I would say, only ask what you need to know.
The most fundamental thing retailers need to know from their customer data is who is my best customer?
What do they look like?
Where do they live?
How often do they shop with me?
What is it that they like?
And then I'm going to use that information to give them more of what they want.
And I'm going to also use that information to run my business better.
(31:34):
As a retail tech expert, couldn't possibly let you go without hearing your take on the future of retail in the world of artificial intelligence, which you've just mentioned.
I saw a wonderful report recently on River Island's introduction of the smart fitting rooms, which could identify the products a customer brought with them to try on and would suggest via AI alternate sizing, colorways, recommended products that style with the items and so on.
(31:57):
What have you seen in the uses of AI that have really piqued your interest recently?
Oh dear.
Sorry, that's not a good start to my response, is it?
I'm not seeing anything particularly innovative.
I'm seeing behind, not customer-facing, I'm seeing there's stuff that customers didn't necessarily see.
(32:19):
But I heard a really good case study of AI being used to dynamically put clothing on models.
So photography, so through the pandemic, samples wouldn't come through quickly and, quickly enough, or they might have an outfit might come through, you know, the top comes through two weeks after the clothing.
So if the supplier is sending you photography and you green screen photograph your models, companies like Looklet, they can dynamically put the photography onto the models and make it look like they're actually wearing it and replicate the drape and so on.
(32:52):
So generative AI, we've seen all the deep fakes from a photographic perspective, you know, that's being used in quite a clever way to merchandise to users.
I think, I know we're coming up to time, so my vision would be, depending on how much of that, you know, on that spectrum of give-to-get you are, walking into your local supermarket and then going, hey Miya, by the app, because I've got my phone out now, right?
(33:16):
The whole point about the book I wrote with Tim Mason of Tesco's was, I can search for the nearest eggs, Google can take me turn-by-turn to the shop that sells the nearest eggs, but when I get to the shop, I put my phone on.
The pandemic's put paid to that.
We all are quite happy to snap QR codes and have our phones out in stores.
And that's across sectors.
What are we doing with it when we've got the phones out now?
(33:39):
What are retailers going to do?
And I think, you know, applying that reward and recognise, help me find what I'm looking for, make sure it's the thing that I want.
You know, it's walk into a supermarket,
Hi Miya, great to see you again.
Are you here for a weekly shop?
Are you here for, and then I maybe have troubles, you know, don't show me offers.
Don't interrupt me.
Do show me way-finding capabilities.
(34:00):
But you know, I'm at the shelf edge and it says the scanning guns already do that.
Are you sure you've got buy two, get one free?
You've not put two in your, you've only got two in your basket, but AI could go so far as to say, it looks like you're making spaghetti bolognese.
Do you know that the Tesco's own brand of Parmesan is half price versus the, you know, the premium brand that you usually buy?
(34:20):
And it's when you start to show value to consumers like that, you're saving me money.
You're getting me in and out quickly.
You could even say I'm in browsing mode.
I'm not in convenience mode.
You know, as many questions as you want to ask for the customer to help them guide you into the kind of shopping experience you offer, AI can then dynamically match that from a promotions and personalisation perspective, and really start to make the mobile a real shopping assistant, both online and in store as far as the shopping experience is concerned.
(34:50):
All of that is predicated on some pretty well joined up and AI turbocharged systems.
Yeah, that's a really, really nice use case kind of imagination or suggestion there.
It sounds like a really well put together kind of an idea for what could be done with AI in the future.
Yeah, it really does.
Yeah, and I think final thing I'd say is, do you want to add an AR filter to that?
(35:13):
Do you want them to give you turn-by-turn where you see the arrows as you walk around the shop?
And then, my God, you point your phone at a shelf edge and you're seeing promotions pop up and stickers and banners.
And again, I don't want to scare anybody because I know there's going to be people listening to this thinking that's my idea of fresh hell.
But when you think about the fact
that we do share so much data
(35:33):
with retailers nowadays
and most of us do want to be treated better
than a one-time cash paying anonymous customer
and we have our mobiles out,
depending on the use case,
the mission and the type of retailer
you are and your brand value,
all of these technology components
can be used both in-store and online
to both give customers what they want
(35:54):
and to run your business better.
So more of what they want, better run businesses.
I kind of wish we booked the studio for a few hours this afternoon to talk to you.
Thank you so much for sharing, just like scraping the surface of some of the insight.
(36:16):
And for those of you who are listening, you can buy Miya's books on Amazon and I would say absolutely give her a follow on Twitter for some great insight into retail tech.
And of course, there's your publication, Retail Technology News.
Yeah, thank you so much, guys.
(36:36):
No, I've thoroughly enjoyed it.
As you said, we only scraped the surface and we're only at the beginning.
I think I've been doing it for a long time.
Things move slowly, but it's exciting times that we're in now.
Definitely.
That's great.
Thank you so much.
Thanks, Ger.
Thanks, Gordon.
Thanks, Miya.
It's very hot, isn't it, Gordon?
Honestly, to quote Zoolander, I'm so hot right now.
(36:58):
It's very hot in the studio.
Wasn't that great though?
That was worth sitting in the un-air conditioned studio for because Miya was fabulous.
Some just brilliant insight across the board, from the inner workings of Amazon right the way through to some of the developments around tech, and really hitting on some of the brilliant basics that we've talked about throughout the season.
(37:25):
One of the things that I found interesting is the three tenets that she took us through.
So the recognise and reward your customer, help them find what they're looking for, and then assure them that it is the right thing.
Those three tenets, the way she talked about them, she talked about them as if they were table stakes for online as things currently stand.
(37:51):
But it's still, I think, a challenge for retailers to get to that level.
You know, I certainly think there are retailers that, you know, let's say in the Irish context, we're trying to get the loyalty going.
It would be such a differentiator for them.
And in Miya's mind, you know, these are basically just, like, hygiene factors.
(38:13):
And it's definitely, there's still quite a lot to be done in the world of tech for online.
Oh, completely.
Inventory, customers, sales and orders.
And then on top of that, once that's built and you've got that solid foundation, the brilliant basics, then you can start to build really exciting experiences.
(38:39):
But only when you've got those basics locked in.
And I suppose the other point is being really clear then on once you've got that, and once you are able to go and build an experience, what's that experience going to be?
What are you asking that technology to do before you pick the technology and layer it out?
Yeah, exactly.
(38:59):
So you're not going through a me too moment because I suppose, you know, it would be easy to look at a range of tech and say, well, look, we've got all of these solutions.
We're not quite sure what our problem is.
We'll just layer one of these solutions on top of it because we're sure that there's a problem somewhere, you know, rather than, let's say, running to the solution, trying to figure out what you're trying to do in the first instance.
(39:21):
And that can apply on so many levels.
I had a really funny conversation this week with somebody and they were like, they were comparing two email platforms.
And one of them is very, very common.
I'm not going to name any vendors, but one of them is really common in a specific tech stack.
And the other one is less so.
And he said to me, I'm not going to switch platforms here.
(39:46):
And I was like, why not?
And he was like, well, the price is pretty much of a muchness, but my team just prefer the UX of platform B over platform A.
And I think that's a perfectly valid reason to choose a specific piece of technology if the capabilities are broadly the same, but your team find one easier to use to create better experiences for customers, then pick the one that the team like to use because they're going to be sitting in front of it all day.
(40:17):
They have to make it happen.
Exactly.
Now, can we, for a second, just talk about Dash Carts?
You thinking about getting into one and being pushed down the hill?
I just want a go.
I just want to have a go of a Dash Cart.
Because I actually said, for the benefit of our listeners, secretly for the benefit of myself, I had no idea what one was.
(40:41):
And now I'm like, I've been putting stuff in, taking stuff out.
Give me the two-for-ones.
Hiding it beside it.
Oh, I would love to have a go of a Dash Cart.
I didn't want to mention it, but what is a body buddy?
Did I hear that correctly?
I think that might be a software application.
Body Buddy?
It could be like a, I'm guessing it's going to be like a True Fit or a Fit Analytics?
(41:05):
That kind of thing, but a bit more AR-y?
We were talking about that experience of... what I would love it to be...
And if anybody from Body Buddy is listening, you maybe want to give us a call.
But in my head, what I would love it to be is an AR application that replicates the experience of when you go into a store...
And for me, when I go into a menswear store and the salesperson looks at me and goes, ah, yeah, this is your size and this is what's going to suit you.
(41:32):
Notice how I admitted, how I omitted what my actual size was.
Medium, I'm assuming.
32 waist.
Extra small.
Extra small, 28 waist.
Massive shoulders and big arms.
And that goes back to what Matthew Brown was talking about on the, let's say, the intimate personal profile, you know, or even this idea of, let's say, you know, maybe even a digital kind of persona that you can go from store to store and say, okay, well, look, here are my sizes, this is my detail, filter for me and find only the product that's going to suit me.
(42:12):
Or the product that fits.
Yeah, I think that we can imagine that that's the use case.
Now let's go and find the technology.
But I really like the idea that Miya had around the use of AI because it was really, it's a really nice, simple, but incredibly useful thing based on what's in your cart.
It looks like you're making spaghetti bolognese.
(42:33):
Would you like our half-price Parmesan?
You know, I mean, like AI can sound so massively frightening for people.
And yes, you know, those are the sorts of leaps that generative AI is going to be able to make.
I love that use case.
But then I was kind of then thinking how exciting to have, based on what's in your shopping trolley...
(42:55):
And if you think about back to episode one, what Dean said about using loyalty to reward the behaviour that you want.
And actually, if you've got AR plus AI, you can start upselling.
So I don't know.
It looks like you're making spaghetti bolognese.
You've got these tomatoes.
(43:16):
But how about these organic Italian fabulous tomatoes that are going to make it taste, like, so much better?
Mmm, chef's kiss.
Yes.
That would be a great use case.
Or maybe you land in a situation where, you know, the AI says, oh, it looks like you're making cacio e pepe.
And you feel all of a sudden kind of, like, shamed by an AI because you've no idea what it's talking about.
(43:44):
I don't know.
I was going to make like, you know, pepper and cheese pasta.
So what are you talking about, AI?
Stop showing off.
Stop showing off or giving me the correct terms.
I love the notions of that.
The Amazon side of things, I don't think we quite, like there was so much to unpack from the conversation that we had.
(44:06):
There was so much detail in there and so much, so many, let's say, areas that we covered.
But one of the areas I would have liked to get into was the Amazon brand and whether or not the Amazon brand will carry Amazon into some of the areas it wants to go. You know, can Amazon food...
Do you want Amazon pasta?
(44:29):
Yeah.
Is the question...
And not pasta from the Amazon.
Or Amazon occasion wear?
Definitely don't want Amazon occasion wear.
Yeah.
I can't imagine that.
But I wonder, like Amazon own brand groceries.
So if you think about the supermarkets that we have, like a Dunne's own brand.
I'm thinking of yellow pack.
I don't know if you had yellow pack in the UK, did you?
(44:51):
I guess Tesco Value would have been the equivalent.
Maybe.
So we had yellow pack and Maurice what-was-his-name?
It was a grocery store, Quinnsworth, it's gone now.
But we had this guy and he'd come, you know, you'd have like the good firelighters and then you'd have the yellow pack and it was just boxed in a yellow box.
(45:14):
That was a Quinnsworth thing?
It was a Quinnsworth thing, yeah.
Lifestyle Sports used to be a Quinnsworth thing.
Oh, really?
Didn't know that.
Long history there.
It was probably one for another episode.
But yes, Lifestyle Sports, originally part of Quinnsworth.
But that would be, so this would be the, well, we're really doing a disservice to Amazon here now, but what you're suggesting is...
Comparing Amazon to Quinnsworth...
(45:36):
Potentially, allegedly. Okay, moving along.
But I do feel like if you had a magic wand, sometimes you might say, okay, well, what else could we do with the brand maybe in terms of, you know, getting into those other areas?
I suppose then, if you think about what Rich was talking about and actually being, having that kind of like that razor-thin targeting, Amazon is the, from a product perspective, is the, is as far away from the opposite in terms of its proposition, because obviously Amazon is the everything store and it's everything for everyone.
(46:13):
I do wonder how far can you stretch the product adjacency for the Amazon brand?
I get it for biscuits.
I get it for mice, as in a computer mouse... not as in, like, a pet mouse.
But does it extend into fresh food?
(46:35):
Would you trust it?
I'd definitely trust it.
I'm just wondering would I shop there?
So the other area that we kind of touched on was just the knowledge in the retail sector in terms of leveraging this tech.
I feel like, I think, you know, some of the tech is a good distance further along than I think the ability to use it is.
(47:00):
And maybe, Miya mentioned a couple of times, for example, it took Covid before people would pull out their mobile phones and, you know, scan QR codes and that sort of thing.
And obviously we saw an enormous step change during Covid in the use of tech and the speed at which businesses were making decisions and, you know, to get on board with new delivery models or new fulfillment models that, you know, let's say even a month previously, they would have put a six-month plan together in order to do click-and-collect.
(47:29):
All of a sudden, overnight, they were pushing it out.
Yeah, and making it work and making it work at Black Friday levels.
But like, you know, we're not going to have a Black Swan event.
Hopefully not a Black Swan event every two years to start seeing step changes in the adoption of technology.
Yeah, I'm kind of done with Black Swan events.
I'm good to not have so many of them.
(47:51):
One of the things I think is really interesting that Miya referenced is auto-management systems and some of the sophistication that can be built into auto-management systems to allow retailers to get the most value out of their inventory.
Love that.
And I like that there's applications that can be swapped in and out to enable that for retailers.
(48:16):
I think that's a brilliant piece of capability that I would like to see more of in use.
I like that.
I like that framing of, you know, how do you get, how do you extract value from your inventory?
Because really, while it's on the shelves of your warehouse, you know, you have no value.
You're not, you've extracted nothing from it.
You've put money into it.
(48:36):
It's an investment waiting to be realised.
And how, you know, the more ways that you're able to unlock access in terms of fulfillment and things like that, the quicker you'll get the full, full value of that investment.
The faster that you can turn that stock, the more you can get onto either replenishing it or moving on to the next season, depending on whatever business that you're in.
(49:01):
And the more fun that's going to be for the buying team.
Well, I have to say that was a fascinating half an hour.
I am absolutely, I'm overheated entirely at this point.
Somewhere in the studio.
Thanks so much.
It's positively tropical.
Yeah, thanks to our listeners.
It's been lovely to have you again for another episode.
(49:22):
And thanks, Gordon.
Thanks, Ger.
Bye.
You've been listening to Functional & Fabulous with Ger Keohane and Gordon Newman.
If you'd like to know more about the podcast, or about StudioForty9 and Omnichannel Stories, please go to functionalandfabulous.ie. Our sound engineer was Elaine Smith. and the show was produced by Roger Overall.
This is Functional & Fabulous, the omnichannel podcast where we unbox tales of online retail and digital transformation.
In this episode, Ger goes in search of questions...
Great, we have all the big data, but what questions are we trying to answer?
Our guest has the questions...
What do they look like?
Where do they live?
(00:21):
How often do they shop with me?
What is it that they like?
And then I'm going to use that information to give them more of what they want.
The Functional & Fabulous soapbox racing team is born...
Can we, for a second, just talk about Dash Carts?
You're thinking about getting into one and being pushed down a hill.
Gordon describes Dash Cart propulsion...
(00:42):
Massive shoulders and big arms.
Ger questions his hearing...
What is a body buddy?
Did I hear that correctly?
And the real threat of AI is exposed...
You feel all of a sudden kind of, like, shamed by an AI because you've no idea what it's talking about.
This episode of Functional & Fabulous is brought to you with pride by StudioForty9, retail ecommerce experts, omni-channel growth consultants and cut-through performance marketing specialists.
(01:12):
StudioForty9, where your digital retail success is built.
Hello and welcome to Functional & Fabulous, the omnichannel ecommerce podcast.
We're delighted to welcome our guest today, Miya Knights.
Miya is a retail tech publisher, an occasional author, and a consultant and advisor.
She has over 25 years' experience specialising in enterprise technology use in retail.
(01:35):
And she spent this time covering and analysing the demands and challenges faced by retailers to identify the technologies that best support their needs as consumer expectations and behaviours become ever more complex.
It's always good to speak to someone who has written the book on a topic.
And in this case, Miya has co-authored two books that are extremely relevant to our subject matter.
(01:58):
Omnichannel Retail, How to Build Winning Stores In A Digital World with Tim Mason, the CEO of Eagle Eye and former Deputy CEO of Tesco PLC.
And Amazon (02:06):
How The World's Most Relentless Retailer Will Continue To Revolutionize Commerce, co-authored with Natalie Berg.
Miya, it's so lovely to have you here with us today.
Lovely to be here, Ger.
Lovely to be here.
Thank you so much for having me.
Welcome to the podcast.
It's great to be able to talk to you today.
We're really looking forward to it.
(02:28):
Likewise, Gordon.
Thank you so much, both of you, for having me.
So Miya, as someone who has written a book on Amazon, I guess you hear people make much ado about the potential end of Amazon whenever they have a stutter or a misstep.
And I've heard you say, you know, it's not the end, but only the beginning of the end of day one.
(02:48):
Would you elaborate a little bit on what you mean by that?
Oh gosh, that's a great question, but to unpack it and answer it, I have to probably give a bit of context, don't I, for your listeners?
So Jeff Bezos famously wrote in a shareholder's letter that in order to be disruptive, to maintain the position in the industry that they have attained and be as disruptive as they have been in the past, and also remain nimble and agile enough to be disruptive and innovative, that they must treat every day that they come into work as though it was day one, the first day in the company.
(03:28):
And so it's become kind of a bit of a term for referring to them as being disruptors and innovators.
And I think, you know, we've seen just, you know, on one half, Amazon is a tech firm.
On another, on the other hand, it's a retailer.
And we've seen both sectors fare differently through the last three or four years, through the pandemic.
(03:54):
We've seen big tech squeezed quite heavily as we've sort of come out of the pandemic and they perhaps, you know, overhired a little bit, and their ranks swelled and their spending swelled through the pandemic to meet demand for everything going online and our appetites growing for digital.
(04:15):
But at the same time, you know, it's being a tech company first, as I'm always saying, a retailer second, it's also really been able to use that tech savvy digital know-how to turbocharge its retail business and do really, really well as a retailer.
So we've seen traditional bits of its business that have been growth engines like its cloud services business, AWS, continue to grow, although growth is now slowing as adoption grows worldwide and competition increases.
(04:46):
And on the retail side, we've seen them grow their advertising business hugely from a profit perspective.
It's got massive margins.
So it's done really, really well there, but it's also been caught out with too much warehouse space, too many staff.
It's having to kill off areas like Alexa or at least slim them down, trim them down.
(05:08):
Maybe it's not learning as fast as it used to or failing as fast as it used to.
The experience, even though, you know, the ads business is great for shareholder news and investor coverage, but, you know, it doesn't actually make the experience a lot better for our consumers.
I think the jury is out on whether or not these ads are actually going to add value.
(05:31):
So in terms of Amazon being able to pivot, be an innovator, be a disruptor, really tune into what the customer wants and reflect it really quickly in their front end, you know, marketplace, Amazon.com and prime businesses.
They're starting to slow down a little bit.
I think the last couple of things that sort of are challenges and have been perennial ongoing challenges have been getting into food and getting into fashion.
(05:55):
I mean, they're still a massive apparel retailer, particularly in the States, they're the number one.
But luxury fashion, they're still trying to, you know, struggling to penetrate.
The likes of Shein, for example, you know, adjacent, so they're not necessarily competing against each other.
But when you think about that fast-fashion side, you can buy a t-shirt from Amazon, buy some jogging bottoms from Amazon, but you wouldn't necessarily go out and buy a party dress or dress shirt from Amazon necessarily, unless the brand already sells.
(06:27):
So there are all these headwinds, as well as the policy and regulation one, which we should always mention, that means that it might not quite be end of day one for Amazon, but I believe it's sun setting and we're starting to see Amazon, the mature retailer and tech company, head into its day two phase.
Such a clear answer to my question, actually.
(06:49):
You know, we've thought about this idea of how a large innovative company, how do you manage to generate or continuously generate that innovation on an ongoing basis, in particular from within the company?
And obviously there comes a point where things start to slow down a little bit, or there's a reinvigoration or maybe a sunset of some portions of it for a sunrise the next day.
(07:10):
They made a lot, like they made much ado about going into grocery in the States and in the UK, and obviously in the States, Whole Foods was a very strategic purchase.
But the business there seems to have abated quite a bit as well.
They were quite bullish going into it.
In some cases, they probably wrote the PR before they actually succeeded in the area.
(07:33):
How do you find that?
Do you think that that's a true statement?
Yeah, that's a fair, that's a fair estimation of where they are.
I mean, again, let's set some context, you know, Amazon's a massive retailer in everything that's non-food, but we spend 40% of all retail spend is food.
It's the biggest category and they want to see what we buy food.
(07:57):
I mean, when you think about the advantages that grocers have from the perspective of that digital pandemic, turbocharged pandemic, digital demand, they have frequency.
You know, they see who's a young family, who's grandparents, who likes to buy Babycham at Christmas, all of these kinds of nuances of our shopping habits.
(08:19):
And I think Amazon has the ability to see everything else apart from that.
And it's a missing piece when you talk about omnichannel, for example, getting that 360 degree view of the customer is not just where they shop with you, but also what they shop with you.
I mean, it doesn't necessarily mean that as a shirt retailer, you're going to want to know my inside leg measurement, but at the same time, it pays to have that, you know, I suppose as detailed a view of who is buying from you so that you can give them more of what they want, you know, infer what they want before they want.
(08:51):
So Amazon's ambitions in grocery are clear in terms of the benefits that they're looking to gain, 40% of our spend and 40% of everything we buy knowing how we do that.
The acquisition of Whole Foods has been seen as a bit of a damp squib.
I do believe Amazon, being a tech company first and a retailer second, has had to learn how to retail along the way.
(09:14):
And grocery is one of those, it's probably the hardest, the hardest sector to get into.
America, it's very fragmented.
You've got a lot of regional banners.
In Britain, it's one of the most fiercely competitive and consolidated markets.
Were they overconfident in their ability?
You know, I mean, Amazon, obviously, they've been enormously successful.
(09:37):
But as you say, grocery is really challenging.
Yeah, I'd like, it would be great to get your opinion, Miya, on whether you think that that's because they didn't have the technology right or what is the reason that this has underdelivered?
And is it, as you say, down to their retail skill set?
(10:01):
I think that's largely got, that's got a lot to do with it.
I mean, when you're talking about the retail skill set, let's deal with that first.
You know, they don't have a brand that's known and trusted for food.
I don't think the proposition, you know, they didn't necessarily... Whole Foods wasn't the best one, the grocer in the world.
They inherited some inventory systems that weren't great.
(10:23):
So retrofitting core retail systems, which they didn't really have to build in for a store environment into Whole Foods, was, I think, from a due diligence perspective, something they potentially overlooked.
And I think what a good way of thinking about it perhaps is that Amazon sees stores the way that traditional store-based retailers sees online, saw online 10 to 15 years ago.
(10:50):
You know, it's something over there, we can operate it as a different, in terms of the integration of Whole Foods, the spinning out of innovation into Whole Foods and retail skills and savvy back into Amazon.
I don't think that integration happened as quickly or as well as it should, as quickly as it should have, as well as it should have.
And they underestimated how much retrofitting they would need to do to Whole Foods to get it up to the same kind of spec and standards as Amazon was running its own retail businesses.
(11:20):
And then on the other hand, the things that they wanted to do from a test-and-learn perspective with Whole Foods that we now see in their Just Walk Out technology in their Amazon Go format stores is the price point.
It's just, it's one of those things where I hesitate to say it's technology waiting for a problem to solve.
(11:42):
It really isn't.
But it's like, I was having this conversation earlier and saying to somebody else, it's like where RFID was seven to 10 years ago in terms of business case ROI.
And that's got a lot to do with just the cost of the tech.
So they were very innovative, very disruptive.
I think the technology has absolute application legs beyond, you know, this is the way forward for shopping in stores.
(12:06):
We don't need tills anymore.
They've proven it.
It eliminates shrink.
You know who's coming into your store.
You can match the digital identity to the human physical shopping trip, for example.
But the cost of doing it has really limited them.
So that's why we see it only rolled out to local and convenience-type formats with smaller footprints.
(12:27):
You know, they're experimenting with I'm answering your question about food, but, you know, they've started to think about how to do this in department store environments as well, how to modernise, disrupt, remove friction from the store-buying experience.
But the technology that they've come up with is proving really, really difficult to scale quickly.
(12:49):
But the final thing I'll say on grocery is I would say instead of watching what has happened with Whole Foods, watch what they're doing with their own banners, and the Amazon grocery stores that they are now rolling out in America have the new redesigned Dash Cart, which allows for one bigger buy.
So bigger format stores, bigger ranges, which allows them to start to build that brand cachet around the actual shopping experience.
(13:17):
What brands do you have?
Do you have what I'm looking for?
You know, it's not just like a UK Morrison's groceries.
I have a choice.
I have local brands and I have Amazon own brands and I have other premium brands as well.
That's what customers are used to.
That's what they're looking for.
So you need the bigger format stores to do that.
Dash Cart's getting them there, although I am seeing some interesting competitors coming out with systems that you retrofit to shopping trolleys that could compete head-to-head with them.
(13:47):
It's not buying tech from Amazon, which means necessarily giving away all your data as well, sharing all your data as well.
Miya, for those people who are listening that aren't familiar, could you just give us a headline of what a Dash Cart is?
Oh, so the Dash Cart is, so the Just Walk Out technology that's in Go stores uses computer vision and shelf-sensing technology to basically track you in an anonymised way around the store.
(14:14):
And when you pick something off the shelf and put it in your bag and walk out with it, you're automatically charged.
The Dash Cart does exactly that, but in a shopping trolley form.
So it's like all the cameras and all the sensors are in the trolley.
So as you drop something in the trolley, that's the cue for the artificial intelligence systems to log it as something that's gone into your basket.
(14:34):
And as you leave the store, that's the cue for it to charge your payment instrument that you've registered to the app.
Got it.
So in convenience, it's looking at the shelves, in the larger formats, it's in the trolley.
Well, I think, you know, they'll certainly have the computer vision and sensing technology in the bigger format stores as well, because you've got bigger basket shops, you know, just belt and braces, I think.
(14:59):
But the Dash Cart is the point at which all that stuff's tallied.
And because it's a bigger shop, it allows them to give you a screen that gives you a running total, which you're more familiar with the scanning guns in supermarkets now as well.
It gives them that sort of digital media capability as well because you're pushing the cart rather than just, you know, putting stuff in a bag and walking out from a convenience perspective.
(15:22):
And tot up your multi-buy discounts as we all like to do as we're running around certain supermarkets with our Scan & Go guns.
With online, the lower the touch, the more tools you need to try and bridge the gap digitally.
And I've certainly seen situations where retailers are trying to deliver totally seamless and frictionless services, or at least that's the aim.
(15:43):
But then they're surprised by the planning effort and technology involved.
And it's almost, you know, when you were talking about Amazon and its experience in retail and retrofitting to Whole Foods and all of that, it was almost like the reverse version of it in a way.
But looking to online, you know, do you find that that's the case?
(16:03):
The more that people are trying to make these things seamless, you know, the more surprised sometimes they are by how complex that can be, you know, and how difficult sometimes it is to keep things simple.
Yes, I would say to answer your question twofold, let's break down what people are looking for from the online experience.
We've been doing it long enough now to kind of start boiling it down to some essential tenets, and then how retailers can deliver on that.
(16:29):
I think the essential tenets are, particularly now, from a give-to-get dynamic perspective when we're talking about digital and the footprint that we leave, and the click streams that we create, and the data that we therefore share, and the information we infer through that data that we then share with the retailer.
There is, I think, the overarching thing now, particularly from an omnichannel perspective, is recognise and reward me for my continued custom.
(16:54):
Don't treat me like I'm a one-time anonymous customer.
So make it worth my while to log in, make it worth my while to identify myself when I'm in store.
When I'm there, even if I'm not a regular customer of yours and I'm not on your loyalty scheme like that, I'm not logged in, but I'm just browsing, the search, browse and discovery phases of a shopping journey now have to be get me to what I'm looking for as quickly as possible.
(17:17):
Don't make it difficult for me to find what I'm looking for.
And then the final third tenet has to be, once I've found it, give me the confidence to buy something that I know is going to be what I want.
And that there becomes again, where the data can really help infer what is the mission?
What's the real value?
Is it speed?
Is it quality?
Is it quantity?
(17:38):
What is it about this person that I already know from their shopping habits, known or unknown that they've shared with me that can help me get to that, bridge that conversion gap.
You know, we can talk about fashion, we can talk about returns.
You know, why are people buying three sizes of something when if you could show them that it would fit them, give them the confidence that it would fit them, they'd buy one size?
(18:01):
So it's that, it's that I try and that's what people come to me for.
They try, for me to boil these things down and it is recognise and reward me, help me find what I'm looking for as quickly as possible and give me the confidence to buy it, knowing that it has the value that you tell me it has.
And that then you get into a whole sort of discussion about brand value and purpose and sustainability and fast versus slow deliveries.
(18:22):
But there are so many different ways that you can do that, meet those three demands that I think the last 15 years have been characterised by retailers going, well, I'll just buy an ecommerce platform, slap that in and it should do it all.
But when you are now talking about recognise and reward me, you're talking about loyalty, linked to, you know, maybe payment system, payment delivery, location, inferences from data points from customers.
(18:54):
When you're talking about search, browse, discovery, you really are talking about shop attainment, you're talking about video, you're talking about embedding video.
Are you making your video on your mobile app shoppable?
Are you using something like the Zara store app where I can nominate my favourite three shops where you'll make the inventory available to me if I could collect in an hour?
(19:14):
And that then bleeds into, you know, at the end, am I using something like AfterShip or Quiver to make sure I'm offering you a slow delivery or make sure that I'm giving you step-by-step your product is five steps away, much as less as just before that we talked about, you know, am I using an AR fitting tool?
Am I using, you know, body buddies?
(19:36):
Am I using video?
Am I using live streaming from the conversion consideration set perspective?
So all of these little but significant components need to be bolted onto these systems.
And I think I see what's happening to sort of round up what's probably a really long response to your question again, but is that these amorphous e-com platforms can't quite keep up.
(20:01):
And we're seeing that that's, you know, it's platform play versus best of breed, right?
It's always been the way.
And right now, platform is holding a lot of retailers.
For me, this is super interesting because on the one hand, you have this tech giant, Amazon, building its own tech and implementing that from, into physical environments.
(20:24):
And some retailers may look overwhelmed.
And I noticed from your Twitter feed, there was a great quote from Régis Schultz, the CEO of JD Sports saying, don't do code.
We do stores and customer experience.
Let the tech companies do the code.
(20:47):
And you gave that one a high five.
And that resonated with me when I saw it, because this is an overwhelming level of capability for a retailer to try and take on and build.
And I think, I can't remember how many applications you just referenced in that couple of minutes, but there's a lot in that stack.
(21:11):
And it kind of leads me in to ask you a little bit more about that of, how do you build that kind of best of breed versus flexible components?
How do retailers even start thinking about this?
Well, I mean, I've been doing this, I hate to admit it, over 25 years.
And just at the time when sort of POS was moving from clients or moving to client server, and then subsequently we've moved, sort of moved it up to the cloud.
(21:40):
If you're at the bleeding edge, there are some retailers that have 37-year-old POSs, shall remain unnamed.
And they are really proving huge barriers to innovation.
So we're talking the e-com platform now kind of taking the place of the POS platform in stores and becoming the barrier to innovation.
And back then it was all best-of-breed.
(22:01):
I want best-of-breed everything.
And then they realised they couldn't sew it all together.
And then you had Oracle, SAP, Microsoft, Salesforce, come in and say, well, you're buying the databases off of us.
You're buying your IBM X, whatever it might be.
Why not?
I've got some applications.
We've got all the money to throw at verticalising this, buying up all of these vertical applications and locking you in.
(22:25):
And so retailers at that time, I think, through the 90s and the early noughties, were like, yeah, all right, I have a bit of SAP.
I'll have a bit of, you know.
And they were quite happy at that time because I think the pace of innovation, the pace of changing consumer demand hadn't become turbocharged by digital quite as much then.
And so they were in a position where they could say, yeah, three to five years for ROI.
(22:47):
That's fine.
I'll take that.
And it's just sped up.
So what I'm seeing now is a little bit of a hybrid where they have got these systems of record that are owned by the big platform, big tech players.
And I always say omnichannel should be three systems of main record.
And that should be as near real-time for all of them.
Your, where's your stock?
(23:08):
And you don't necessarily need to know where it is at that moment, just when it moves.
I want to know when it moves.
If it's gone from a warehouse to a store or it's on a truck or I've handed it to a customer.
Those are the main points that you need to know where it is.
So that's stock/inventory.
Then you need to know who your customers are.
However you do that, you might need a loyalty scheme, might not.
(23:31):
And three, you need to know what you're selling.
And that might be sales and orders.
And so we've seen, again, you know, one of the big ones, people sorted out their POS systems.
Then they put an e-con systems.
They were doing telematics in the background, maybe 10, 15 years ago.
Order management.
When I was at IDC, it was an order management system.
I need to do click and collect.
I need to put my store systems onto my e-con systems.
(23:53):
And now you're trying to get retailers kind of going for, you know, sales and orders coming from one stock pool and dynamic orchestration and predictive analytics, where to keep my stock, for example.
So they still need those three systems of record, right?
But what's emerging on top from a best-of-breed perspective, I would say maybe, oh I'm going to sound like I've drunk the Kool-Aid, but the best iteration of this I've seen so far is composable commerce.
(24:20):
Throw a few buzzwords at you there.
And, you know, I think it's typified by the work that's being done by the Mac Alliance.
So I work quite closely with a mobile app, native mobile app firm called PopCommerce.
They would hate me if I didn't actually name them, who onboarded to the MACH Alliance in 2021.
So I got to look under the covers and see what the MACH Alliance needed for this vendor to join this members of members association.
(24:43):
And they literally have to show their code.
They have to work on blueprints integration.
And the MACH Alliance essentially stands for, and then I'll sort of hopefully finish answering your question in terms of having that platform systems of record, but hot swappable composable components on the top from the customer-facing perspective that gives you that agility, is that they are all microservices written in microservices with API first cloud native and headless capabilities.
(25:13):
So that's what the MACH stands for.
And I ded appreciate that the MACH Alliance doesn't just go, yeah, give us your subscription money.
We'll slap your logo on stuff.
You have to go through quite a rigorous assessment process with the existing members on their technical council.
And Google's only just been on boarded.
For example, Google has only just joined the MACH Alliance.
(25:35):
I think companies like Salesforce and Oracle will struggle to prove that they can join the MACH Alliance.
And that's a good test.
So whether something is MACH-enabled and allows that level of composability on the front end, while you manage the systems of record on the back end, I think is the happy medium that we're converging towards now.
(25:55):
Okay, so I suppose you could kind of, I've got to simplify it for my own understanding a bit here.
So it's kind of, like, those systems of record, they're our foundations and they're the bits that stay constant.
And then you can use, or retailers can then build experiences using composable elements to bring that experience to life for the customer.
(26:24):
And that's how they can they can access the technology and also differentiate through the mix of technology.
That's, that's right for them and their customer.
If I've understood what you're saying correctly.
Yeah, exactly that.
Thank you for simplifying it for me.
Absolutely.
No, no, no.
You're absolutely right.
That's exactly how it should work, I think.
I think, you know, it was interesting, that Régis Schultz quote, he actually started off by saying, you know, it took them back and forth with their e-con provider about whether or not they needed a persistent basket.
(26:54):
Yeah, it's questions.
It's questions like that that take too long to answer.
Whereas if you're evaluating a new e-com platform, you can ask that question of three or four different MACH-enabled providers and get the answer, you know, and choose the answer that best suits you because you're the retailer.
You don't necessarily necessarily know what persistent basket means, but if they can explain to you what it means and you know your customer and you know the way they shop and you know what kind of business model, operating model you want to create online, then you can meet in the middle.
(27:26):
So it makes those kinds of conversations a little bit clearer, a little bit easier.
You know, all of the big-platform guys will make sure that they have an API layer that you can use and hook these things into.
But it's, it's, it's things like dynamic search.
It's things like, you know, if I want to just swap out, so an unnamed retailer is currently migrating from ATG, which was bought by IBM years ago and is unsupported.
(27:50):
It's no longer supported.
They're running their entire e-com business and they're a former catalogue business.
They don't actually have that many stores on something that's end-of-life, something that's no longer supported simply because the operational risk of swapping that out right now is too big.
So the idea is that
they could move to,
you know, I'll try and be fair,
(28:11):
you know, you've got Shopify,
BigCommerce, Fluent Commerce,
all of these other e-commerce,
MACH-enabled systems
of ecommerce systems
more, more quickly,
more easily without disrupting
necessarily the plumbing underneath
the systems of record underneath
and having more business-focused
and outcome-focused conversations
(28:31):
rather than, you know,
getting mired in technical diagrams
and, you know, months,
let alone years to,
to seeing returns and some value
working that incremental
sort of way of getting quick...
I have a question in that area, Miya, the, you know, I've often heard people speak of the desire to make data-driven decisions based on the 360-degree view of the customer.
(28:54):
And you've mentioned that earlier.
Do you feel like the knowledge and education is in the industry to leverage the potential of the tech that is available?
And if not, what would you do about it or what do you think can be done about it?
That's a really good question, Ger.
One large UK department store has only just taken on a head of customer data.
(29:17):
Only just.
Has only just launched a loyalty factor scheme, you can probably infer which one it is...
So, you know, strategically, are they ready?
Some not.
I think those that have had loyalty schemes, we've seen them double down on them and also maybe flatten them out a little bit in terms of their value, just from the cost-of-living crisis perspective.
(29:44):
And I think they're probably, you know, they've got first-move advantage.
They kind of, they already understand the power of customer data.
And so they are, you know, the grocers, they're launching retail media networks.
You know, they're miles ahead.
I think the non-food guys are kind of just looking at marketplaces, that kind of thing, trying to get, they know they've got the eyeballs.
(30:05):
How can I make my site more sticky?
How can I start to join up my store, my view of customers in stores and my view of what they do online?
I would say the big buzzword in regards to customer data is CDPs, customer data platforms.
Do I need one?
(30:26):
Well, do I know what I'm going to do with it if I had one?
If I had one, what would I do?
Well, if you had one, what would you do with it?
Well, I think sometimes that question, there's a question of almost diving to the selection of a CDP ahead of the strategy around what would we do with it.
(30:48):
It's kind of like the famous thing with big data.
Great, we have all the big data, but what questions are we trying to answer?
Exactly.
So we talked about big data, now we're talking about AI, aren't we, from that perspective?
And I hear retailers all the time say that they're drowning in data.
So you raise a very, very good point there.
And I would suggest that you're drowning in data because you don't know what to ask of it.
(31:11):
Again, I would say, only ask what you need to know.
The most fundamental thing retailers need to know from their customer data is who is my best customer?
What do they look like?
Where do they live?
How often do they shop with me?
What is it that they like?
And then I'm going to use that information to give them more of what they want.
And I'm going to also use that information to run my business better.
(31:34):
As a retail tech expert, couldn't possibly let you go without hearing your take on the future of retail in the world of artificial intelligence, which you've just mentioned.
I saw a wonderful report recently on River Island's introduction of the smart fitting rooms, which could identify the products a customer brought with them to try on and would suggest via AI alternate sizing, colorways, recommended products that style with the items and so on.
(31:57):
What have you seen in the uses of AI that have really piqued your interest recently?
Oh dear.
Sorry, that's not a good start to my response, is it?
I'm not seeing anything particularly innovative.
I'm seeing behind, not customer-facing, I'm seeing there's stuff that customers didn't necessarily see.
(32:19):
But I heard a really good case study of AI being used to dynamically put clothing on models.
So photography, so through the pandemic, samples wouldn't come through quickly and, quickly enough, or they might have an outfit might come through, you know, the top comes through two weeks after the clothing.
So if the supplier is sending you photography and you green screen photograph your models, companies like Looklet, they can dynamically put the photography onto the models and make it look like they're actually wearing it and replicate the drape and so on.
(32:52):
So generative AI, we've seen all the deep fakes from a photographic perspective, you know, that's being used in quite a clever way to merchandise to users.
I think, I know we're coming up to time, so my vision would be, depending on how much of that, you know, on that spectrum of give-to-get you are, walking into your local supermarket and then going, hey Miya, by the app, because I've got my phone out now, right?
(33:16):
The whole point about the book I wrote with Tim Mason of Tesco's was, I can search for the nearest eggs, Google can take me turn-by-turn to the shop that sells the nearest eggs, but when I get to the shop, I put my phone on.
The pandemic's put paid to that.
We all are quite happy to snap QR codes and have our phones out in stores.
And that's across sectors.
What are we doing with it when we've got the phones out now?
(33:39):
What are retailers going to do?
And I think, you know, applying that reward and recognise, help me find what I'm looking for, make sure it's the thing that I want.
You know, it's walk into a supermarket,
Hi Miya, great to see you again.
Are you here for a weekly shop?
Are you here for, and then I maybe have troubles, you know, don't show me offers.
Don't interrupt me.
Do show me way-finding capabilities.
(34:00):
But you know, I'm at the shelf edge and it says the scanning guns already do that.
Are you sure you've got buy two, get one free?
You've not put two in your, you've only got two in your basket, but AI could go so far as to say, it looks like you're making spaghetti bolognese.
Do you know that the Tesco's own brand of Parmesan is half price versus the, you know, the premium brand that you usually buy?
(34:20):
And it's when you start to show value to consumers like that, you're saving me money.
You're getting me in and out quickly.
You could even say I'm in browsing mode.
I'm not in convenience mode.
You know, as many questions as you want to ask for the customer to help them guide you into the kind of shopping experience you offer, AI can then dynamically match that from a promotions and personalisation perspective, and really start to make the mobile a real shopping assistant, both online and in store as far as the shopping experience is concerned.
(34:50):
All of that is predicated on some pretty well joined up and AI turbocharged systems.
Yeah, that's a really, really nice use case kind of imagination or suggestion there.
It sounds like a really well put together kind of an idea for what could be done with AI in the future.
Yeah, it really does.
Yeah, and I think final thing I'd say is, do you want to add an AR filter to that?
(35:13):
Do you want them to give you turn-by-turn where you see the arrows as you walk around the shop?
And then, my God, you point your phone at a shelf edge and you're seeing promotions pop up and stickers and banners.
And again, I don't want to scare anybody because I know there's going to be people listening to this thinking that's my idea of fresh hell.
But when you think about the fact
that we do share so much data
(35:33):
with retailers nowadays
and most of us do want to be treated better
than a one-time cash paying anonymous customer
and we have our mobiles out,
depending on the use case,
the mission and the type of retailer
you are and your brand value,
all of these technology components
can be used both in-store and online
to both give customers what they want
(35:54):
and to run your business better.
So more of what they want, better run businesses.
I kind of wish we booked the studio for a few hours this afternoon to talk to you.
Thank you so much for sharing, just like scraping the surface of some of the insight.
(36:16):
And for those of you who are listening, you can buy Miya's books on Amazon and I would say absolutely give her a follow on Twitter for some great insight into retail tech.
And of course, there's your publication, Retail Technology News.
Yeah, thank you so much, guys.
(36:36):
No, I've thoroughly enjoyed it.
As you said, we only scraped the surface and we're only at the beginning.
I think I've been doing it for a long time.
Things move slowly, but it's exciting times that we're in now.
Definitely.
That's great.
Thank you so much.
Thanks, Ger.
Thanks, Gordon.
Thanks, Miya.
It's very hot, isn't it, Gordon?
Honestly, to quote Zoolander, I'm so hot right now.
(36:58):
It's very hot in the studio.
Wasn't that great though?
That was worth sitting in the un-air conditioned studio for because Miya was fabulous.
Some just brilliant insight across the board, from the inner workings of Amazon right the way through to some of the developments around tech, and really hitting on some of the brilliant basics that we've talked about throughout the season.
(37:25):
One of the things that I found interesting is the three tenets that she took us through.
So the recognise and reward your customer, help them find what they're looking for, and then assure them that it is the right thing.
Those three tenets, the way she talked about them, she talked about them as if they were table stakes for online as things currently stand.
(37:51):
But it's still, I think, a challenge for retailers to get to that level.
You know, I certainly think there are retailers that, you know, let's say in the Irish context, we're trying to get the loyalty going.
It would be such a differentiator for them.
And in Miya's mind, you know, these are basically just, like, hygiene factors.
(38:13):
And it's definitely, there's still quite a lot to be done in the world of tech for online.
Oh, completely.
Inventory, customers, sales and orders.
And then on top of that, once that's built and you've got that solid foundation, the brilliant basics, then you can start to build really exciting experiences.
(38:39):
But only when you've got those basics locked in.
And I suppose the other point is being really clear then on once you've got that, and once you are able to go and build an experience, what's that experience going to be?
What are you asking that technology to do before you pick the technology and layer it out?
Yeah, exactly.
(38:59):
So you're not going through a me too moment because I suppose, you know, it would be easy to look at a range of tech and say, well, look, we've got all of these solutions.
We're not quite sure what our problem is.
We'll just layer one of these solutions on top of it because we're sure that there's a problem somewhere, you know, rather than, let's say, running to the solution, trying to figure out what you're trying to do in the first instance.
(39:21):
And that can apply on so many levels.
I had a really funny conversation this week with somebody and they were like, they were comparing two email platforms.
And one of them is very, very common.
I'm not going to name any vendors, but one of them is really common in a specific tech stack.
And the other one is less so.
And he said to me, I'm not going to switch platforms here.
(39:46):
And I was like, why not?
And he was like, well, the price is pretty much of a muchness, but my team just prefer the UX of platform B over platform A.
And I think that's a perfectly valid reason to choose a specific piece of technology if the capabilities are broadly the same, but your team find one easier to use to create better experiences for customers, then pick the one that the team like to use because they're going to be sitting in front of it all day.
(40:17):
They have to make it happen.
Exactly.
Now, can we, for a second, just talk about Dash Carts?
You thinking about getting into one and being pushed down the hill?
I just want a go.
I just want to have a go of a Dash Cart.
Because I actually said, for the benefit of our listeners, secretly for the benefit of myself, I had no idea what one was.
(40:41):
And now I'm like, I've been putting stuff in, taking stuff out.
Give me the two-for-ones.
Hiding it beside it.
Oh, I would love to have a go of a Dash Cart.
I didn't want to mention it, but what is a body buddy?
Did I hear that correctly?
I think that might be a software application.
Body Buddy?
It could be like a, I'm guessing it's going to be like a True Fit or a Fit Analytics?
(41:05):
That kind of thing, but a bit more AR-y?
We were talking about that experience of... what I would love it to be...
And if anybody from Body Buddy is listening, you maybe want to give us a call.
But in my head, what I would love it to be is an AR application that replicates the experience of when you go into a store...
And for me, when I go into a menswear store and the salesperson looks at me and goes, ah, yeah, this is your size and this is what's going to suit you.
(41:32):
Notice how I admitted, how I omitted what my actual size was.
Medium, I'm assuming.
32 waist.
Extra small.
Extra small, 28 waist.
Massive shoulders and big arms.
And that goes back to what Matthew Brown was talking about on the, let's say, the intimate personal profile, you know, or even this idea of, let's say, you know, maybe even a digital kind of persona that you can go from store to store and say, okay, well, look, here are my sizes, this is my detail, filter for me and find only the product that's going to suit me.
(42:12):
Or the product that fits.
Yeah, I think that we can imagine that that's the use case.
Now let's go and find the technology.
But I really like the idea that Miya had around the use of AI because it was really, it's a really nice, simple, but incredibly useful thing based on what's in your cart.
It looks like you're making spaghetti bolognese.
(42:33):
Would you like our half-price Parmesan?
You know, I mean, like AI can sound so massively frightening for people.
And yes, you know, those are the sorts of leaps that generative AI is going to be able to make.
I love that use case.
But then I was kind of then thinking how exciting to have, based on what's in your shopping trolley...
(42:55):
And if you think about back to episode one, what Dean said about using loyalty to reward the behaviour that you want.
And actually, if you've got AR plus AI, you can start upselling.
So I don't know.
It looks like you're making spaghetti bolognese.
You've got these tomatoes.
(43:16):
But how about these organic Italian fabulous tomatoes that are going to make it taste, like, so much better?
Mmm, chef's kiss.
Yes.
That would be a great use case.
Or maybe you land in a situation where, you know, the AI says, oh, it looks like you're making cacio e pepe.
And you feel all of a sudden kind of, like, shamed by an AI because you've no idea what it's talking about.
(43:44):
I don't know.
I was going to make like, you know, pepper and cheese pasta.
So what are you talking about, AI?
Stop showing off.
Stop showing off or giving me the correct terms.
I love the notions of that.
The Amazon side of things, I don't think we quite, like there was so much to unpack from the conversation that we had.
(44:06):
There was so much detail in there and so much, so many, let's say, areas that we covered.
But one of the areas I would have liked to get into was the Amazon brand and whether or not the Amazon brand will carry Amazon into some of the areas it wants to go. You know, can Amazon food...
Do you want Amazon pasta?
(44:29):
Yeah.
Is the question...
And not pasta from the Amazon.
Or Amazon occasion wear?
Definitely don't want Amazon occasion wear.
Yeah.
I can't imagine that.
But I wonder, like Amazon own brand groceries.
So if you think about the supermarkets that we have, like a Dunne's own brand.
I'm thinking of yellow pack.
I don't know if you had yellow pack in the UK, did you?
(44:51):
I guess Tesco Value would have been the equivalent.
Maybe.
So we had yellow pack and Maurice what-was-his-name?
It was a grocery store, Quinnsworth, it's gone now.
But we had this guy and he'd come, you know, you'd have like the good firelighters and then you'd have the yellow pack and it was just boxed in a yellow box.
(45:14):
That was a Quinnsworth thing?
It was a Quinnsworth thing, yeah.
Lifestyle Sports used to be a Quinnsworth thing.
Oh, really?
Didn't know that.
Long history there.
It was probably one for another episode.
But yes, Lifestyle Sports, originally part of Quinnsworth.
But that would be, so this would be the, well, we're really doing a disservice to Amazon here now, but what you're suggesting is...
Comparing Amazon to Quinnsworth...
(45:36):
Potentially, allegedly. Okay, moving along.
But I do feel like if you had a magic wand, sometimes you might say, okay, well, what else could we do with the brand maybe in terms of, you know, getting into those other areas?
I suppose then, if you think about what Rich was talking about and actually being, having that kind of like that razor-thin targeting, Amazon is the, from a product perspective, is the, is as far away from the opposite in terms of its proposition, because obviously Amazon is the everything store and it's everything for everyone.
(46:13):
I do wonder how far can you stretch the product adjacency for the Amazon brand?
I get it for biscuits.
I get it for mice, as in a computer mouse... not as in, like, a pet mouse.
But does it extend into fresh food?
(46:35):
Would you trust it?
I'd definitely trust it.
I'm just wondering would I shop there?
So the other area that we kind of touched on was just the knowledge in the retail sector in terms of leveraging this tech.
I feel like, I think, you know, some of the tech is a good distance further along than I think the ability to use it is.
(47:00):
And maybe, Miya mentioned a couple of times, for example, it took Covid before people would pull out their mobile phones and, you know, scan QR codes and that sort of thing.
And obviously we saw an enormous step change during Covid in the use of tech and the speed at which businesses were making decisions and, you know, to get on board with new delivery models or new fulfillment models that, you know, let's say even a month previously, they would have put a six-month plan together in order to do click-and-collect.
(47:29):
All of a sudden, overnight, they were pushing it out.
Yeah, and making it work and making it work at Black Friday levels.
But like, you know, we're not going to have a Black Swan event.
Hopefully not a Black Swan event every two years to start seeing step changes in the adoption of technology.
Yeah, I'm kind of done with Black Swan events.
I'm good to not have so many of them.
(47:51):
One of the things I think is really interesting that Miya referenced is auto-management systems and some of the sophistication that can be built into auto-management systems to allow retailers to get the most value out of their inventory.
Love that.
And I like that there's applications that can be swapped in and out to enable that for retailers.
(48:16):
I think that's a brilliant piece of capability that I would like to see more of in use.
I like that.
I like that framing of, you know, how do you get, how do you extract value from your inventory?
Because really, while it's on the shelves of your warehouse, you know, you have no value.
You're not, you've extracted nothing from it.
You've put money into it.
(48:36):
It's an investment waiting to be realised.
And how, you know, the more ways that you're able to unlock access in terms of fulfillment and things like that, the quicker you'll get the full, full value of that investment.
The faster that you can turn that stock, the more you can get onto either replenishing it or moving on to the next season, depending on whatever business that you're in.
(49:01):
And the more fun that's going to be for the buying team.
Well, I have to say that was a fascinating half an hour.
I am absolutely, I'm overheated entirely at this point.
Somewhere in the studio.
Thanks so much.
It's positively tropical.
Yeah, thanks to our listeners.
It's been lovely to have you again for another episode.
(49:22):
And thanks, Gordon.
Thanks, Ger.
Bye.
You've been listening to Functional & Fabulous with Ger Keohane and Gordon Newman.
If you'd like to know more about the podcast, or about StudioForty9 and Omnichannel Stories, please go to functionalandfabulous.ie. Our sound engineer was Elaine Smith. and the show was produced by Roger Overall.
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