 Live from London, England, it's theCUBE, covering AWS Summit London 2019. Brought to you by Amazon Web Services. Welcome to the AWS Summit in London's Excel Center. I'm Susanna Streeter and Dave Vellante is my co-host today on theCUBE. There's been so much to talk about here at the Summit today to do with machine learning and AI. And I'm really pleased to say that we have two really key people here to discuss this. We've got Tom Summerfield, who is head of commerce at Foot Asylum, and also Richard Potter, who is the CEO of Peak. Now you guys have really formed a partnership, haven't you? Foot Asylum is a leisure where really retailer, started in bricks and mortar stores, really moved to online, and Peak is a bit of a pioneer for artificial intelligence systems, really. How did you get together, what kind of sparked really your demand really for their services, Tom? Yeah, well, so we knew that we needed to be doing something with data and AI, and we didn't really know exactly what it would be. We were interested in personalization, but then also in a bigger picture, like a wider digital transformation piece for the business where a well-established bricks and mortar business, and then a fast-growing online business, and we were interested to know how we could harness the momentum of the stores to help the digital side of the business, and also vice versa. And we thought data would be the key, and we ended up having a conversation with the guys at Peak, and that's exactly what we've been able to do, actually, on the back of that, and we're delivering a hyper-personal experience for our consumers now. I was one of the stats that I noticed when looking into what you've been doing, a 20% increase in email revenue, so that's quite remarkable, really. So, Richard, tell us how you're able to do this, what kind of services that you lean on to make those kind of results. It's a combination of a lot of things, really. You obviously need people who know what they're doing from a retail and a business perspective, married with technical experts, data science, algorithms, data. I think specifically how we've done it is Peak's built a fairly unique AI system that becomes almost like the central brain within our customers' businesses, and off that, the algorithms help automate certain business processes and deliver tangible uplifts in business performance, like the 28% uplift in sales here. In order to do it, it's quite a long journey. I suppose the outlook we took when we started collaborating was that if we could deliver that hyper-personalized shopping experience, we were always going to be able to show customers the right product at the right time, and if we were doing that, that we would lead to high brand engagement, higher loyalty, and higher lifetime values of customers, and that's what's shown to be the case in Fort Asylum's example. Yeah, definitely. To echo that, the hypothesis was if you can show the right customer, the right product at the right time, then their purchase frequency, average order value metrics all start to move positively, and ultimately then affecting their long-term engagement with our brand, which increases revenue, and also delivers a more frictionless consumer experience, hopefully, for the customer. Because as far as your experience is the same, so many companies out there, they're sitting on this huge pile of data, yet they don't know how to best optimize that data. When did you first realize, Richard, that there was this kind of gap in the market for peak to grow? Yeah, I think data and analytics has come on a bit of a journey, all the way from common sense reporting to more advanced analytics, but when you get to AI and machine learning, what you're talking about is algorithms being able to self-learn and make predictions about things, and that actually fundamentally changes the way businesses can operate. And in this case, a great example is, we're sending hyper-personalized marketing communications to every single foot to silent customer. They don't realize necessarily that they are tailored to them, but they just become more relevant, but it doesn't require a digital marketer to create every single one of those campaigns, or emails, and even trigger the sending of those materials. The brain takes care of that, it can automate it, and what the marketer needs to do is feed it, engaging content, and set up digital campaigns, and then you're left with this capability where AI is saying, you might be a marketer for this product, let's send you something that might appeal to you, and that just gives a marketing team scale, and then as we move into other use cases, like in the supply chain, fulfillment, delivery of product, the same thing, the teams just get huge scale out of letting algorithms do those things for them, and I suppose the realization for us that there was that gap in the market was just that you can see the outperformance of certain companies, you can see that Amazon attributes 35% of their sales to their machine learning recommendation systems, I think Netflix says 85% of all content is consumed because of its algorithms, and if companies like that can harness machine learning to such a great degree, how do other businesses do it who can't access that talent pool of Silicon Valley, or the global talent leaders in tech, and that's where we had the insight that as peak we could create a company that gave our customers that technology and that capability to deliver the same kind of results that Amazon and Netflix gave us. So before the internet, the brands had all the power. You could price however you wanted, if you overpriced, nobody even knew, and the internet was sort of like the revenge of the consumer. AI and data now gives the brands the ability to learn more about its customers, but you have to be somewhat careful, don't you, because your privacy concerns, obviously GDPR, et cetera, so you have to have a value proposition for the customer, as you were saying, Richard, they may not even know that the machine is providing these offers, but they get value out of it. So how do you guys think about that in terms of the experience for the customer, and how do you draw that balance? I think from my angle that Richard touched on a couple of bits there, to do it at scale first and foremost across the entire network of consumers is a killer bit element to it, but to deliver that personal experience, I think consumers nowadays are more expectant of this, really. We would have considered innovation a couple of years ago, but now actually it's expected, I think, from the consumer, so it's actually in the name of you have to move forward to stand still, so we think we're right at the front of this at the moment, and we're really looking now how we optimize the journey for the consumer, so that actually we know if we're, from some transactional data that we have and a little bit of other behavioral data that we're really conscious of the whole GDPR piece and stuff, and that's really, really relevant and super important, and I'm pleased to say that we have that, by a peak, it's completely on lockdown from that perspective as well. Where do the data sources come from? You mentioned some transaction data. Where does the other data come from? Are you using social data and behavioral data? Where does that come from? So there's elements of social data. Some of it is a little bit black box, so you can't always access it, and that's a GDPR piece there, and rightly so, actually, in some cases. We have a loyalty scheme which allows us to understand our consumers better in our bricks and mortar retail, which is really cool that we've got some of that transactional data on a customer level from the stores. We know that some people in our sector maybe don't have that, so that allows us to complete the sort of single customer view which then we can aggregate in peak's brain. Then transaction data on the website in the app and bits of browsing, just within our own network where a customer's potentially been and reacted with something, a piece of content, and journeys within the website, and that's how we build that view. Do you think this is the way that more bricks and mortar stores can survive? Because so many are closing in high streets up and down the UK and in other countries, because simply they're not really delivering what the customer wants. Yeah, I think so, Rich and I both feel quite strongly now that we're sort of onto this now a little bit. It's a really, as our relationship for the two businesses has evolved, it's become clearer and clearer that actually, we've armed with this data, our fingertips, we can actually breathe fresh life into the stores, and it's in the eye of proper true omnichannel retailing. We don't mind where the customer spends the money, we just need to be always on in a connected environment so that, as we said before, pushing the right products at the right time, and when they're in market, we turn up the message a little bit, but then understanding when they're not in market, and maybe to back off them, and maybe we warm them up with a little bit of a different type of message then. And actually, we want to challenge ourselves to send less, better marketing communications to our consumers, but absolutely that the storepiece is now, so we tail back our store, sort of opening strategy as a business to focus more on the digital side of things, but now it's possible that we might open some more stores now, but it'll be with a more informed strategy of where we need to do that. What is it this ironic? The brick and mortar marketplace is getting disrupted by online retailers, obviously, Amazon's the big whale in the marketplace, and your answer to that is to use Amazon's cloud services and artificial intelligence to pave the way for your future. I mean, that's astounding when you think about it. Coming full circle. Yeah, it's this sort of unified commerce approach to, there's a place in the world for shops, it's like it's not, the romance isn't completely dead in going shopping, it turns out, you know, so, and actually, yeah, we're using harnessing the AWS, well, via our friends at peak, yeah, it's some irony there, I think, it's really cool. And that decision that you made, obviously, wasn't made lightly, but you saw the advantages of working with the cloud outweighing the potential trade-offs of competition. Yeah, I mean, that was never really a consideration for, no, I mean, certainly not, no. I think this is something that is happening. The data and harnessing it in a safe, responsible, effective way, I believe, is the future of all commerce, so. And as far as security is concerned, because of course, we have had data breaches, customers' credit card details have been accessed, how do you ensure that it's as secure as possible in the way that you choose the services? I think that just comes down to best practice infrastructure. And the way we look at it at peak is, there's no better tools in the world to do that than the same technologies that Amazon themselves use. It's to do with how you configure those services and tools to make it secure. And if you have an unsecure open database on a public network, of course that's not secure, but you could have the same thing in your own infrastructure and it wouldn't be secure. So I think the way we look at it is exactly the same thing. And actually, being in the Amazon cloud for us gives us a greater comfort, particularly in terms of co-location of data centers and making sure that our application fails over into different locations. It gives us infrastructure we couldn't afford otherwise. And then on top of that, we get all these extra pieces of technology that can make us even more secure than we could do. Otherwise, we'd have to employ an army of infrastructure engineers and we don't have to do that because we run on AWS. Okay, so we're able to eliminate all that heavy lifting as the saying goes. You've got this corpus of data. I'm interested in how long it took to get through a POC, train the models, how much data science was involved, how much of a heavy lift was that? Yeah, well, I think for us, it's been pretty rapid actually. We started working together in January last year. So we're only just a sort of year into that. And in that entire so far length of our relationship, we've gone from hyper-personalizing digital campaigns to recommendation systems on a website to now optimizing customer acquisition on social media and then finally into the supply chain and optimizing demand and so on. And I think there's a lot of reasons why we've been able to do it quickly, but that's fundamental to the technologies that PIC has built. There's two sides to it. Our technology's cut out a lot of the friction. So we didn't run a proof of concept. We were able to just pick it up, run with it and deliver value. And that's to do with, I think, the product that PIC has built. But then you obviously need a customer who's going on a transformation journey and is hungry to make that stick and land in. And then when the two come together. I think that it's an interesting point that though, because whilst we're at foot asylum, we're always, I always say, it's the sort, we're not massive, but we're not tiny, but it's the sort of place you can turn up on a Monday and say, I've had an idea about something and we're sort of doing it by Friday. That's a nice agile culture. It can create some drama as well, possibly. But I think it's really straightforward to get straight into it. And I think this is where some of the bigger, sleepier high street retailers that are more fixed in a bricks and mortar world need to not be too afraid to come out and start embracing it because I think some of them are trying now. I think it might be a little bit late for some now, but it just wasn't that hard really to get going. And you've seen the business results. Can you share any measurements or quantification? We've got a really good one that we're just talking about at the moment, actually. We were able to use the segmentation tools within the peak brain to use them on social then to create lookalike audiences. So Facebook has some tools where it will help you create audiences that it thinks will be right via its complex algorithms itself. But we almost took a leap ahead of their algorithms via our algorithms, uploading our own segments to create a more sophisticated lookalike audience. We produced a ROAS results, a return on ad spend, people are not as familiar with that, of 8,400%, which we would normally be happy as a business with sort of 7, 800%. If you're running at that, we've say an AdWords campaign or something like that, that's quite an efficient campaign. So to add a zero, we were a bit like, it felt like it's a mistake that it's not can't be right. But no, so that's super cool. And that's really opened our eyes to the potential of harnessing our sort of the PKI brain to then bring it onto social and do more outward advertising on there, yeah. So moving the goalpost meant that you achieved a really high score. Oh, thank you very much. Thank you very much for telling us all about that. Tom Summerfield and Richard Potter, thank you for joining me and Dave Vellante here at the AWS Summit in London, much more to come on theCUBE.