[Music] hello everybody I'm Hara gavati I'm a senior customer experience at data strategies in AWS and here with me today I have fabis Kolar from sries director of design and product development and Dwayne Brown from NWS principal customer experience and data strategist we are here to talk about the customer experience landscape in retail and how Cloud Technologies in particular data and IML shaping the that landscape fabis Dwayne welcome welcome to Amazon Studios um fabis I would like to start with you and if you could please tell us a little bit about your role at selfes yeah sure hi um thanks for thanks for having me um yes so I'm uh I look after uh everything at selfes that is product management um ux and design we work very closely with um Tech teams to kind of develop um our customer experience we do a lot of things um ourselves with engineering teams um just to kind of Drive um that customer experience um and Dwayne could you please share about your role at AWS sure um so Dwayne I lead our CX practice here AWS data strategy and I help customers to innovate and also deliver change many in the areas of marketing automation digital experience and so on um pleasure to be here thank you for inviting me great so I would like to talk about the relationship between uh consumers customers and the retailers obviously that relation relationship has been going through big transformation the last years I will say it's undergoing a profound shift due to several factors advancements in technology of course generative AI but social media Mo like the adoption of mobile phones um the change of consumer behaviors there is more awareness of uh social environmental issues uh the impact of um Global events covid-19 pandemic wasn't too long ago and um also the widespread adoption of digital Technologies and Ecommerce so uh customers are looking for more personalized seamless experience with uh their retailers no matter where they are in their journey and no matter what genner they're using right so Omni Channel I will say it becomes a non-negotiable um opportunity um so fabis what are your thoughts of um how Cloud technology and data and a IML reshaping the experience of customers when they interact both with digital and physical channels yeah sure I think there's probably a couple of things to to think about right so I think firstly I feel that it's not just about technology disrupting retail or other organizations I think the consumer is actually disrupting it because they have access to this technology and there's an expectation now that you know all these channels are connected all the things you can do with your phone right are going to be relevant um regardless of how you choose to interact with the brand and I think that's been going on for for quite some time and it's taken I think some retail organizations a while get used to the fact that you know for example in its most basic form I guess we know that customers are browsing our websites or searching or doing things before they even get to our stores right so it's really important to sort of create those connections I think on the business side what technology and new technologies are enabling is it's just making it easier to stitch those things together um for us so being able to access large data sets from different channels um being able to spin up things very quickly environments to be able to test these things in the cloud etc those are obviously benefits to organizations that I think otherwise might have found it harder to be playing around with with this sort of of tech to enable different experiences for our customers yeah I I agree with Fab I think is is I think customer consumer behavior is really driving the change and called as an enabler um if you if you cash if you rewi maybe 10 12 years ago where you had um marketing departments really TR blazing with you know the first introduction of personalized experiences and product suggestions and everything those are based on you know SAS solutions that were Bas in the clothes right um and I think what has happened now is as is the broader organizations other departments have adopted the cloth that wealth has been shared more broadly um I think it's I really like the way you framed it in that it's really made the bigger smaller it's broken down the complexity into smaller bits so now you can do things like you know spin up a small service I integrate different systems so you can get real time inventory so now you can have a digital kiosk in the store and actually get the item in in the store while you're in the store right you couldn't that wouldn't have been easy before if you see my point right or you can spin up services based on demand so you can know do things like have a Time limited offer and a mobile app on social media platform and then actually get the order delivered to you or you can go pick it up so the the relationship and the interconnectivity between the different channels is much easier and I think the code isn't enabl for that great thank you and you touched you talk about um excuse me a few things so you talk about customer experience that may Encompass more than customer acquisition more than customer engagement it's also about customer service you talk about inventory right Inventory management uh maybe order fulfillment a Inns um so I would like to start with customer engagement and fabis could you just share your thoughts discuss again the role of data and AIML artificial intelligence and machine learning in reshaping the customer engagement so yeah I think I think the use of of certainly data um and then how we how we kind of access those those um pools of information that we have on our customers how they choose to you know whether it's navigate our stores or browse our websites or the things they purchase um I think all of that helps us create much more relevant experiences and relevant um sort of you know ways to navigate our um our Stores um and what that does effectively is is starts to play into how we ensure that customers are engaging with us more regularly um you know or um just becoming Advocates of our brand and and and sort of almost moving to being fans of our brand which I think is becoming incredibly important and some of that you know as well I think for us has enabled us to do things like build um a membership program which allows us to you know understand even better how our customers are engaging with us what they care about which in turn then allows us to kind of tailor the experience to drive that engagement so it becomes this kind of you know um cycle that that it allows us to to sort of um create so I I really like for's point the way you framed it I think this there's something to be said about how Brands retailers even across different sectors they've got the opportunity now to use anml further Upstream to get a better understanding of the way customers um use or engage with Brands and purchasing behaviors and what they're saying what they're actually doing and then feed That Into You Know developing better propositions that have a positive impact on engagement right so the cycle to your point um is refined you know as a result of embedding inl into mix I see I see so what you're telling me is how you can create a customer base so devoted to your brand right that they are willing to do repeated business uh with brand right and um with better understanding using data like creating better insights understanding more the behaviors and framing better propositions better messaging um you create this personalized experience that Brands retailers can use to drive up loyalty in the top line I think fa you talk about the uh membership uh program that you have so I would like to double click on this one and I think it's called SE unlocked um could you share some insights on um the strategies for enhancing uh Customer Loyalty yeah I mean I think look um the other thing I guess we we've talked about a little bit so far is we talk about sort of data AI ml I think they are slightly different things and having access to data and doing clever things with that data I think ML and AI are moving us towards the kinds of things we do with it to get to an outcome But ultimately you know we've been collecting this data on our customers for years understanding through our insights teams Etc you know how they're transacting the seasonality sometimes in some cases how International might be different to domestic all those different data points that and insights that have allowed us to realize that really to drive that engagement um we wanted to create a cohort of customers that we would just um kind of have a better understanding of and so that we could drive that loyalty Drive the engagement by creating specific tailored experiences for them so we launched selfes unlocked um um last year we're sort of about to um you know obviously it's it's an ongoing program and we will be launching uh more features and and more benefits um over the next year but really the idea was to start to create this feeling of you know you belong to um you're a member of selfes and through that you are unlocking um different benefits different experiences things that we can do to reward you for engaging with us and in turn um as long as the data that we're collecting is relevant and we spend a lot of time making sure that we're getting um the right data sets from our customers we can use that data to then in turn do better things for you uh and and have you really be part of this this community that we're creating um through selfes unlocked you made me think about something you know so you you remember back in the day when you had your your panels and your focus groups and and so so they very much determined the products that you would build the campaigns that you would build the trends that you would double down in you know and focus on but they would large based on what customers said they would do and the reality was different right um I think now you've got an opportunity to take a subset of users um um your actual customers from that panel run an ethnographic study observe them out in the well in their own environment see them you know engaging with the brand and the things that they do to the left and right of that right and you you pick up Miss opportunities right and you you you determine like unders serve audiences of people that you aren't actually providing to that well um and then merge that to be the data that you Des talked about right so so you've got quantitative data you've got purchasing Trends you've got ways that they engage with you and you've got a nice richer picture of you know of this small group The Magic is though you can now take that and now project that outward to a broader base so now that your product team merchandisers you know they've got a a much better a bigger space that that they can play with and they can experiment with the test out propositions and they could get a much better understand of you know the customers that haven't been in the surveys and they are in the focus groups so you made the 20,000 20 20 people here the 20,000 that you've got as customers right you got a much better out understanding more broadly yeah and I think you're also reducing the risk of getting it wrong like in the old the old way if we call it that it wasn't that long ago right but there's always that risk of getting it wrong because a through a focus group through a survey you're asking the questions customers are going to tell you maybe what they want to tell you but it doesn't necessar tell you how they're really going to behave and it's the old you know it's the old Ford example if if Ford had asked people what they wanted he to built a horse right it's kind of like that I think data allows us to move away from what's being said or what's being intended and actually what's really happening and it's not to say you don't still do those things to get a sense or to understand if your ideas have any value but I think it's now you can augment that with real data real transactional or behavioral data that allows you to yeah absolutely okay great so let's go to the hard stuff now because we we talk about customer engagement we talk about Customer Loyalty but in order to do these things we need first to acquire and retain customers right so I would like to talk about uh customer acquisition and retention and I think the retail environment at the moment uh is challenging from almost every perspective so there is disruption from online uh players there is price pressure from the Discounters um there are so many choices for Shoppers and I think also on top of this there is PR price transparency for the Shoppers right and the traditional approaches of um you know pricing and uh promotions is less effective now it's not working because it's very easy for the competitors to imitate this right so Dwayne um what are some of the main challenges uh that retailers face in acquiring new customers but also retaining the existing ones if you could please share some of uh like Solutions some suggestions of how we can overcome these challenges yeah no no worries I mean I don't know how how you feel but I I feel it's never been harder for Brands to break through I think there's so many things you can see in a 24-hour D um it's like you know it's just a plethora of things and it's fully saturated so it's hard there's no reason that's the reason why acquisition cost is high across different sectors I mean you know some sectors are easy than others but in general the trend is upward right um I feel like there's a elephant in the room now for brands in general so not just retailers as so you know do you develop your base so do you nurture your base to build your base right um and so let's double click into that um so for made a point earlier around using insites to develop more tailor propositions that creates more love more love products and people engage with you more right um so then that allows you then to create a community that's an interesting proposition right but then once you do that customers those customers are going to they're going to speak on your behalf right they're going to be advocates for your brand right this the nice little byproduct of that though is that you can use their profiles and and to create local likes to attract more people like them right so you got that nice twofold benefit you know and and you're right and you know you mentioned the acquisition cost earlier I think the last that I saw was something like 12 or 15% uplift year on year yeah I'd agree with with with all of that I mean I think um ultimately retention is probably where increasingly Brands need to focus because you know there are there is so much Choice out there and I think it's it's sort of moving away from traditional thinking on this where actually you know when we talk about customer experience it's a pretty broad topic to me ultimately you know customer experience is about how a customer ends up feeling how you make them feel um so you know there's different different points in that Journey for sure but how they will remember you is probably you know a a combination of all those things things and how they had that journey and that will then determine whether they decide to come back to you or not and I think that's where retailers need to focus and I think taking a leaf out of maybe adjacent Industries like if you think about things that are happening in the fitness space or in music where it's about creating fans and communities to your point um and and sort of thinking of our customers in those ways like how do you create these very engaged very loyal fans that will value The Experience overall with you versus just acquiring a product you know and again also recognizing that there'll be different times and different use cases and different Journeys for those customers sometimes you will be driven by Price you might be buying something that's more of a commodity that you will go from a search into finding the best price for it sometimes you will want to you know get the full experience because it's I don't know you might be sending someone a gift and you want that to be pretty special so you're going to go to the brand that you trust to do that so I think again it's becom increasingly important to think about our customers as fans that we will retain and will keep engaging with us you just made me think about something you know I saw this article the other day around how gen Z consumers have broken the funnel right um and I think it goes inspiration into exploration into Community into loyalty that's different right um so it made me think like the challenge for brands well it'll be interesting to see how that plays as that cohort grows older right I still think it's an interesting challenge for brands in that well what it means that well you probably need to create more engaging stories further up right and there acquisition costs and implications and cost on that front but there's probably a totally different way of working to create a community right more broadly for for different product groups that you've got so I think I I think it's an interesting more Dynamic space you know so what you're highlighting is that um differentiation um Can Be Still achievable through personalized approaches because retail ERS Brands organizations Can Craft um unique experiences that are relevant to the customers that they are relevant to their needs to their preferences and this way retailers make the customer part of the dialogue so they have they create these personalized products offers um that are uniquely relevant to them so uh fabis how um organizations can leverage technology data in IM IML uh to create more personalized and simless experiences across various platforms yeah I mean it's it's incredibly um important and I I guess some of this isn't you know new I think we're just getting better at it because we're getting better data um and then obviously through technology we're finding easier ways to leverage that data to to do that and I suppose um we run a trial recently um actually working with AWS um using kind of data that we had on our logged in customers to tailor the experience that they got um on our app so we took a single Carousel which used to be um like a static Carousel where we were positioning certain products certain brands we turned that around to be relevant to that customer so in that Journey you're going to see either brands or adjacent brands or things that are relevant to either things you've browsed or things you've bought before um and it was incredible to see how we ran this test for a couple of months we saw like 130% increasing clickthrough on those carousels and and again I think that's because we've done a lot I think as retailers and other Industries in terms of on the acquisition side you know making sure that messaging is very relevant for example in personalization kind of on that side of the fence but I think it's also customers are expecting that level of you know personalization and for things to be relevant to kind of carry through the entire experience so when they then land on your app or website or whatever um you're still kind of engaging in that dialogue to your point and then you know when they come into store again I think there'd be an expectation that the things they're being talked to about maybe by a member of the team that might be using a client telling app or something again that you've persisted that personalization and that understanding of the customer and ultimately it's about creating that two-way conversation we talk a lot about growing customer relationships because I think that's what it's about it's about creating those relationships and that's what personalization allows you to do you you just you just triggered a memory uh for remember remember the days when a large percentage of like online transactions were like Anonymous and like Browns were funny with that and I think slowly you have to create value propositions to encourage people to sign on and that kind of thing I think now to to see where we at now you know on the and the value that that creates both for Brands but also for consumers um I think the important thing for for for businesses to remember though um is that you it's it's more important for you to go beyond the you know the data Mars and the AML environments okay I think it's more important for you to extend those into services that allow you to create consistency across channels right and that way you can move away from you know think about strategy over here and then each department develops their own capability is synchronously right because you're B to get disparities and you know you deliver it when you do when you do it that way I really like what your team is doing not just because I'm next to you right um I think the the this this whole idea of that you got a cross functional team that's a line to Journeys I think that that's a really powerful way to do it right and so but that nothing to do with technology if you really think about it you you just organized yourself in a different way you've changed your operating model right and then the services support that so you know if you're in a contact center or if you're in web you're developing an app or whatever you've got consistency in data you're seeing the same things you got the same propensity scores right I see I see um fait you talk about you know the trials that experim experiments that you are doing and I would like to double click on this one because experimentation and Innovation um actually can create a competitive advantage to create that uh enhanced customer experiences right and as well experimentation Innovation is are ingrained in our AWS approach centered um on working backwards and we use the working backwards mechanisms um in uh blended with service design what you mentioned to in in our customer experience Innovation workshops and the idea there is we start from the customer problems uh and uh we focus on the customer needs rather than organ organizational goals um and we start small but uh thinking what we can create that first invention that we can create using data using Technologies get alignment from people like the different teams and um we build upon it we iterate we test we learn and we fail fast as well which is very important um we call this flywheel and the idea is to keep spinning that fly wheels um so fab what is that process for you and how important is that culture of experimentation on innovation in creating that competitive Advantage um yeah I mean there's there's a couple of things I guess to to think about there I mean firstly um absolutely agree with kind of everything you've said and we've done some work with you guys so aware of some of the the Frameworks and the things that you you you use within kind of your your organizations some of that's hugely um inspirational and we've definitely taken some of that back from from the workshops we've had um to apply in our own business um I I think over overarchingly what I've seen in different retailers is there's a real need to experiment and innovate I absolutely agree I think a lot of retailers struggle with that because retail can can be a bit shortterm in terms of you know you're you're always focused on kind of the current trading period the next couple of months the next quarter and you're not always allowing yourself to invest and think further out um but increasingly that's becoming hugely important because I think to your point to me it's like what we get from our teams we have a couple of small teams that are able to sort of run ahead of the rest of the road map I suppose i' put it that way um and try things out maybe before we realize that it's something that works and we might want to put into production and then we'll we'll kind of throw back into the squad that's kind of working on on releasing more regular features as an example um but what's really hard with that is is getting retailers to understand that part of that is also failing fast is really key so if if we've tried an experiment and it didn't work not seeing that as a failure and we've wasted a month but actually you know in the old world we probably would have wasted six months on a project and then landed something that wouldn't have done what we thought it was going to do either for the customer or for the business so increasingly I think retailers need to look at this as like an opportunity cost instead of an actual cost which is well actually we spent a month trying this thing it didn't work we're now going to Pivot and do something else that's a lot more valuable because you'll still end up getting to something Works sooner um and again when you're using data sets when you're using kind of hypotheses that you might have come up with with your insights teams or your business teams it's really important to be able to go and test those things out because it also will inform what you do next with that thing that you've developed so we've been over the last 18 months I'd say we've we've been doing a lot more of that and it's been really helpful whether it's through you know AB testing techniques um or actually having squads that can go and test out brand new tech that we might not be sure there's a a use case for yet but we introduce a use case to see if that can solve the problem I think all of these things have really helped us um kind of get there in a in a less risky way I'd say I I um there a number of things I I want to touch on that you just mentioned you got me thinking so all right so first thing remember that the digital native Brands exper experimentation is probably understood concept but for a more established brands with you know with some Legacy is an important pipeline to scale so so remember we talked earlier about you got a much better Innovation cycle now right and so therefore as part of how you take those things to production and the skill them all experimentation and being able to P it in key so definitely agree uh with forb and not friend I think that um these are the things you you probably need to think about right so do you have the framework so things like budget cycles for example right can you how easy is it for you to identify a backlog of Innovations and then get the funding for it to scale it out can you dedicate resources to it both like the technology resources but also the people right um You Because if you if you don't then a lot of those things are going to stay as back log items they're never going to go anywhere right so I just think you know it's it's it's okay for us to give us the tag line of experimentation but I think I think there's important things that like Brands beond retail to be fair need to think about in terms of how they actually enable that experimentation and Final one embracing failure in general I think failure is implicit in experimentation the thing you may put out to to this point it might not go anywhere but it saves you though it helps you to mitigate the risk so I think it's an important thing to think about and you learn from it right you learn and you sa maybe the six months that you have invested before not only that right it's a good input for your your business cases as well it helps the inform costs right you get a better idea benefit right so it's it it definitely helps so it's no wasted work right I like that to embrace failure um okay so we highlighted a few things in terms of businesses Brands retailers that they're turning to data to AI ml uh Technologies to shape customer experiences in customer engagement in loyalty in retention acquisition personalization and harnessing the power of data so Brands retailers can create more personalized um uh offers positions but also they have these insights right they understand better their customers um D I would like to look into the future now um and I would like to understand a little bit how are advancements in technology in data inl and now of course we cannot skip you know generative AI out of our discussion how these Advance advancements are shaping um the customer experience in the retail sector okay so um let's break it down so let's do let's do back office first and then we do front office so I think backup office you're seeing a number of productivity gains already right so you know you're getting a significant uplift in terms of the quality of of of content that you create for Brands I think initially there were questions around the scalability of that and we're addressing those things um I think you know then you got like the support teams the people who handle and fulfill orders in the back office and you know who handle contact center calls they're getting much better insights on customers and how to help customers better um so that's fantastic back of office great um front of office um and this could be perceived as quite controversial right so so what generative AI has is captured our imagination the imagination of investers we're all in on it I think that you know there's there's more there's more that could be done right let's put it this way if if we were to fast forward if we had a time machine we went two three years out into the future and look back at now we probably go yeah you're about right man right um I think that's largely because you know we've got we've got established conventions the ways that users and customers engage with Brands and they buy things and it's all tablet based and it's visual right I think that until we find more ways to take generative specs and embed them into those interfaces I think it will you know I think that's when you will see it unlocked and scale up see so you are in AI that's right you were I like it I like it so then you know let me give you an example right so if you think about the you know the virtual Tron services that you've got right they're real Mutual beneficial um you know features right in that you know for customers you get to see yourself in the outfit right and you get to buy it first time right big barrier for many people adopting and buying things online is oh might need to return it so they buy two and three items when they really want one right and then on the retail site for for brands for retailers they get to reduce the motor returns so it's good for me and it's good for them right so I think that's a good example of how you can embed it into something that already exists the you know the PDP the product Details page looks the same you know nothing's really changed for the customer but you've enhanced it reg featur yeah I would definitely like I'd agree with that and I think just building on it I think also to the point we were discussing earlier you know customer experience is is the the kind of the end to end right that's how you've got to think about it so actually sometimes those back office things are actually really crucial when you get to the the actual thing the customer experiences so I think until now a lot of the use cases um and I think it's important to think about it that way because I think you know everyone's experiencing the hype right now of gen and you know I'm sure in lots of businesses people are tapping people on the shoulder going hey what are we doing with AI what's our next AI project and I think you've got to be careful you got to bring it back to like is there a use case is there a genuine problem that we could solve with these Technologies and I think there are plenty right and at the moment I agree with you a lot of those feel more back office like how do you augment I don't know a lot of retailers probably struggle with getting accurate data out of the thousands of suppliers they work with you know there's probably tools out there that could help you augment that data set so that what you're presenting back to the customer is more consistent there's clearly going to be use cases and call centers and things like that that will make you know will drive productivity gains I think on the front end it's a little harder because I think again you know retail for the large part is still a very human thing it's about human Connection in a store so again you know is it more about how gen might help to augment and you know help our Workforce serve the customer better I think there's going to be those kinds of use cases that we need to consider not just the the things we've seen today which are like you know I guess a lot of chat Bots that might help you triage where a claim or a resolution goes right is this something that the robot can solve or is this something that needs to go to an actual human being to to help with right so I think those those things are actually happening now I think what we will see is how over time we will find those use cases where it does make sense as that that sort of front of office as you call it but but this is where it's not one siiz fits all in detail I think sometimes it can be we'll need to recognize that there are different experiences different Journeys where this stuff will make sense so maybe there'll be the high touch Elements which you'll still want to do in a store that you'll still want to be served by a human there might be things that actually take you away from I like the UI AI thing maybe the the UI becomes Irrelevant in some use cases where actually you know you can you can talk to a a clever speaker or your mobile phone and ask questions and you'll be kind of served the next kind of collection that you want to wear or whatever that is right there'll be those kinds of use cases that I think as retailers we just have to be ready for it not being one siiz fits all and and where do we where do we use these Technologies and where do we continue to maybe think about the human connection more we talk about lot of stuff we talk about use cases start with that priority or the problem for your customers right um You just mentioned prioritization I think what you're talking is about prioritization how data AIML the Technologies can help solving and bring you more insights and information that you can create these personalized experiences um so I would like to finish our chat with some advice to your peers peers from technology and business in retail but also in the other Industries because I think everybody can can learn from from this that they are looking to embark on this data and AI driven uh transformation to enable better customer experiences so D um some thoughts from your side what would you advise uh people that are looking um to start to embark on this journey okay so for me two things come to mind um I think any mechanism that allows businesses to bring different groups of people together on a common vision for what the right thing to do for customers like what they allow this stuff that you that you've done um I think that's a good thing ultimately right I think design thinking in general obviously we got our working backwards that you mentioned um I think adopting and extending that through service design is even more important it allows you to go deeper right um allows you to get into the Integrity of how teams hand off between one another and there systems hand off between you know between each other um which are important to really ingest change you want to adopt these Advanced Technologies you need to think about how you integrate back into the business right and realize the benefit um and then the second one would be how you then link the CX the value um you know I think you know far too often we focus on the technology right so I really love the point that you raised it earlier because the technology is cool or because it's exciting that's not the reason to move right so the reason to move is that you've framed hard benefit for the business and a hard benefit for customers right um and you've created a blend a blended package or word that allows you to then fix the basics and then deliver that benefit together as one thing so I think that you need to be thinking in in in with that frame in my view yeah I'd add like um a couple of things I think for for retailers you've got to actually make sure you're getting the right data to begin with none of these things are going to be meaningful unless you can trust the data that you've either collected or transformed on your customers um you know in our case we definitely saw a lot of problems um internally with some of the things we were we were doing and collecting and I think before you can apply the algorithms and the Machine learning and all of those things to that you really want to be confident that you have that that proper view of what your customers are up to and what they're doing so that you trust that data and I think it's just not being afraid to invest in getting that right to get kind of the next step right um I think the other point that we've already sort of touched on but you've got to find those problems to solve I think it's really important not to just use tech for the sake of using Tech um and then the other is like think about you know this will also create pretty transformative things within your business you're going to have to create new teams bring in different skill sets that understand these topics maybe from other industries that will help you shape it within your retail business and I think again don't underestimate um kind of having to go into that and what what a big change it might be eventually but you know start small pick a a couple of things where you can apply this to that point it doesn't have to be one siiz fits all right find a couple of use cases maybe spin up a small team start experimenting I think that's how you you get through it I love this so yeah focus on your use cases start small for the most important one get your teams together your small teams together you don't need all the data but you need good data to start iterating testing learning if you fail embrace it and then yeah link it to Value right link it to Value okay well thank you very much both really enjoyed today and hope to see you soon thank you and thank you very much for watching