Being a Digital Leader - the Good, Bad AND Ugly of Digital Transformation
Join us as we dive deep into the world of digital transformation with real-life stories of breakthroughs and challenges from the front lines. In each episode, we'll sit down with industry experts, AND Digital consultants, and other influential figures in the technology space to hear about their personal experiences of leading digital transformation initiatives.
We'll explore what worked, what didn't, and the lessons learned along the way.
Being a Digital Leader - the Good, Bad AND Ugly of Digital Transformation
The cost of getting customer experience wrong
The gap between what customers expect and what businesses actually deliver is widening, costing companies millions in lost revenue. In our recent panel, Alex Comyn (AND Digital), Catriona Morse (Royal London), Tim Mason (the pioneer of Tesco Clubcard and CEO Eagle Eye) and Rich Bovey (Chief of Data, AND Digital) explore this costly disconnect and offer practical remedies.
Over half of the 250 business leaders we surveyed say poor customer experience has already cost them millions, and a similar number admit they’ve lost customers as a result. Yet organisations still favour efficiency over experience, often choosing to appease stakeholders rather than customers.
Tim Mason insists that true customer-centricity is less about technology or data and more about understanding people’s lives. After all, data might show what customers do, but rarely explains why, leading 56 per cent of firms to make AI-driven decisions on flawed data, risking trust and reputation.
Our experts agree that the real edge lies not in AI tools, now widely available but in data quality and a culture that acts on it. The number-one risk, they warn, is doing nothing.
From restaurants changing napkin colours to spare dark trousers from lint, to travel firms easing trips with children, the smallest touches reveal genuine understanding and win loyalty.
Discover how to bridge the gap in our “Know Me or Lose Me” report download it today to learn how better data and emerging AI can forge deeper customer connections without expensive mis-steps.
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Hello everyone and welcome to our webinar on the state of customer experience, not least the cost of getting customer experience wrong. Earlier last month, ant Digital published its report Know Me or Lose Me, which delved deep into the challenges facing organizations in better understanding what their customers were looking for and, more importantly, how better management of their data and huge leaps in AI capability is opening up opportunities to be ever more knowledgeable, responsive and real-time than ever before. And yet, from the 250 business leaders that we spoke to, just over half of them said that poor CX has already cost them millions in lost revenue and operations. Over half of them believe that they've lost customers as a result of poor CX and two-thirds of them fear they'll lose even more customers this year. And with even greater pressures on the economy, over half are expected by their stakeholders to deliver improvements with no budget increase.
Speaker 1:Now I'm joined today by three people who are working at the cutting edge of this challenge. But before we start, if you have any questions, please use the Q&A function and we'll endeavor to answer as many of your questions as we can at the end of the session. And don't forget the event is being recorded and we'll share a link to the recording, along with a link to our report. Know Me or Lose Me at the end of this session. So to get things going, I'll start introducing myself. My name is Alex Common. I'm Brand Experience Principal at Anne Digital and most of my work is involved in exactly this how to make life better for our clients customers so that they do more business with them. I'll pass over to Kath to introduce herself.
Speaker 2:Hi there, thanks, alex. My name is Cath Morse. I am the head of customer digital experience at Royal London and I'm really passionate about ensuring that we really embed that thinking around customer into organisations to really create that frictionless, seamless and very easy customer experience for organisations. So really looking forward to today's discussion and conversation and hopefully some really good questions at the end. So thank you.
Speaker 1:Fantastic Tim, do you want to introduce yourself?
Speaker 3:Hi everybody, thanks for joining. My name's Tim Mason. I'm the CEO of Eagle Eye, and 30 years ago not quite today, but nearly 30 years ago today. And 30 years ago not quite today, but nearly 30 years ago today I was the guy that launched the Tesco Clubcard, so I've been in this space for quite a long time.
Speaker 1:Rich. Do you want to introduce yourself?
Speaker 4:Hi everybody and thanks for having me. Rich Bovey, chief for Data at and Digital, so I'm responsible for our data practice and leading all of our brilliant data professionals at AND.
Speaker 1:Wonderful. So I guess I'm going to start with an open question to all of you, and you know when I sort of think about this. We've all been working in the industry for some time. Tim, you just said, you know, 30 years ago you kicked off with Tesco Clubcard. Tim, you just said you know, 30 years ago you kicked off with Tesco Clubcard. Where do you think the industry is in denial and what are we still getting fundamentally wrong about customer experience today? Because this feels like it's always been here and no one ever has been able to actually solve it.
Speaker 2:Who wants to go first? Kat, I'll let you go first. Yeah, perfect. So it definitely has been, as you you say, kind of in the ether for a very long time and nobody, I think, has been able to absolutely kind of nail it.
Speaker 2:I think one of the the key aspects for me is that we're still very much focusing on on the bottom line in the wrong way. So we very much look at, often within businesses, how we can build out efficiencies rather than how we look at experience, and so we drive a lot of our business decisions through that aspect to kind of satisfy probably more of that stakeholder aspect rather than the customers. And so I think by pivoting it and thinking about actually first what the customer needs and understanding from the data that's available whether that be customer complaints, whether that be customer interaction data, you know, whatever data that you've got within your organisation to really drive that understanding of the customer needs and how they feel off the back of the journey is actually where we should be aiming it. And you know, I think there are so many reports out there that demonstrate that actually by focusing on the CX rather than the business, efficiency actually drives far more profitability across your bottom line for organisations. So I absolutely think that that should be somewhere where we should be looking.
Speaker 2:What my concern is is probably in the kind of reaction to that and the panic to that and it says this in the report that about kind of 56% of the respondents from organisations that you questioned are making decisions based on AI and data that they know is fundamentally wrong, and that's because they feel like they're in this AI race, and my real concern here is actually that we're going to go in the wrong direction and we're going to actually, as organisations, lose trust, lose reputation, lose governance.
Speaker 2:You know there's a slew of organisations that we've seen in the press that have had bad experiences when their data has not been in the right place. I'm sure everybody can associate to the Marks and Spencer's one that is currently ongoing in that space and the cost of getting it wrong, and so my biggest concern around that is like we should be using the data, but we should be using it in the right way and ensuring that it is safe in that space. So I think I think businesses need to really look at the governance that sits around. That, alex, would probably be my view at the moment excellent.
Speaker 1:I really like your comment as well about even the types of data you look at, and I think you know you mentioned customer complaints. I think is actually, you know you, great customer experience is actually largely invisible because you're in and you're out and it's just a great experience and it makes you come back. But customer complaints is where you really get some solid insight from your customers as to why things are going wrong and why they're not happy. I think that's a fantastic insight, tim. I think obviously it'd be great to hear your perspective on this, especially with your experience.
Speaker 3:Great to hear your perspective on this, especially with your experience.
Speaker 3:Yeah, I think the most important thing and Kat, I think, has sort of alluded to this the most important thing and the most difficult thing is actually having a genuinely customer-first strategy. Although people talk a good game, they don't necessarily deliver it. It's not about data and it's not about technology, and it's about thinking about the customer, putting yourselves in the shoes of the customer and having staff that are sufficiently knowledgeable and sufficiently loyal that they understand the customer's life and can respond to that. So if you can get all that right which is a herculean task, you know this is not trivial to be genuinely customer driven, then you'll buy the right systems. You'll buy the right systems, you'll have the right data strategy and you'll use the data in the right way to benefit customers.
Speaker 3:But the starting point is and wasn't it ever thus is how do we go to market? How do we approach customers? How do we manifest to market? How do we approach customers? How do we? How do they? How do we manifest ourselves in their lives, and that's so. You know that's a difficult thing to do.
Speaker 1:I think, Rich, what's your thoughts on this? I know I've got my own.
Speaker 4:Well, I know my job here, alex. Right, I'm a data guy. I'm a data guy, I'm a panelist. But before I kind of advocate for the brilliant things that we can do with data and AI and maybe talk about risk, actually it's worth just pointing out yeah, data reveals what people do, but rarely why. Okay.
Speaker 4:So to tim and cat's points there actually, um, it needs to be wrapped in a a customer first strategy for the meaningful and has a genuine understanding of what customers say. Look at, um, look at starbucks in the instance, right, they are an organization that went heavily on the digital side of things, digitizing every part of the customer experience. They're actually pulling back from that a little bit because they have realized that that's inhibited some of their engagement and loyalty and slightly damaged the brand. Right To Kat's point around ROI measurement and business case and all that sort of that has taken quite a few years to manifest and they're course correcting now. Right, so I won't take us down the data and AI rabbit hole just yet, but unless you have that clear customer first strategy, anything you're doing in data and AI may be difficult.
Speaker 1:I think these are all really really sort of salient points and what I'd like to do is really start to think about the foundations and starting with the customer and how well we know our customer. And again, the first question out to all of you is kind of what do we think it really means to know your customer in 25? And are we getting better at it? Or actually we're just talking a really good game without implementing and I say this because I write about this in the report Two companies I've worked with one, a big automotive I'm not going to name any names, of course, but big automotive company who made brilliant cars but actually suffered from a real retention problem. And in the investigations it became clear that some of the challenges were structural because everyone who worked there never actually had to buy their own car. They all got given company cars so they'd never taken the car in for a service, they'd never really done a proper sales visit with a dealer to be sold the car, and that sort of insight really, and that insight really helped shape their understanding of how do we show up for the customer and understand what their needs are.
Speaker 1:Equally, there's another company I worked with years ago, an outdoor company where everyone worked there was effectively a customer as well. They believed in the product, they wore the product, they talked about the product. The culture in there was completely different. You were walking in there talking to a bunch of experts who knew that category inside out and believed in it and wore that product as a badge of honour because they knew it was the best in the market. Two really different and, interestingly, one was a multinational and one was quite a small, albeit very globally successful business. Those shifts are sort of I find really really interesting and again sort of it really really interesting and again sort of it would be great to hear from all of you. Like what? What do you think it means now to show up for your customer in 2025? Should we go? Should?
Speaker 3:I jump in um. I don't think the company you were talking about was rei. It might have been, but rei is an American outdoor business, started in Seattle, I think. I think it's a co-op. The most amazing thing about REI is the first American to summit Everest was an REI store manager, and that you know. It says so much about the brand, I think, and so it's not really an answer to your question, but it's a story that I love about a brand that that I like um, it wasn't rei actually, I'll tell you what it was.
Speaker 1:Berghaus, uh, we sort of set up by chris bonington and yeah, yeah, fantastic example.
Speaker 3:Yeah, another one, it's interesting how businesses in in that space do seem to do that, because patagonia is another one, isn't it? I'm sure patagonia is a brand that we sort of have great affection for, and I was teasing, I was on with um, one of my brokers this morning from one of the big banks and he was wearing his company, you know gilet thing and I was laughing about the fact that patagonia refused to supply them. You know, for these, these guys all getting together in silicon valley and we'll have 50 of your gilets. Oh no, you won't, they said, which again is quite a brand building moment. I think, um, I think the most important thing that you, I was with a guy, um guy doing.
Speaker 3:The other week there was a dinner about loyalty but his business was train tickets and discounted train tickets and selling the overstock on train tickets Young business doing very well. And he said don't worry, bother me with this loyalty stuff, just put all our energy into making a better product, the best product. And you have to say you're absolutely right, mate. If you can invest to make a better product, to take friction out to make, that's absolutely what you should be doing for sure. But of course, in other industries that are more mature, points of difference may well have been competed away.
Speaker 3:You're very similar to other businesses and then you need the data, you need the insight and how you show up to start trying to differentiate yourself in smaller ways. But I do think it's a sort of a bit of a truism. I remember back in the early days of considering loyalty and loyalty schemes at Tesco. The managing director at the time said you're only talking about the icing, I'm talking about the cake. Said you're only talking about the icing, I'm talking about the cake. And I think you know the cake, the core of the business, has got to be a great cake.
Speaker 1:I want to ask you a follow-up question and then I'll pass it over to the other panellists, tim, especially with you, know, because you make a really good point right, a great product can do a lot of great things, but the product is only as good as the organization operates around it. Like one of my former clients always had a really great quote, which was it's one thing to put a buy button on your website, but the challenge is knowing what to do when someone presses it. And I think from your perspective, tim, especially with the work, the pioneering work you did with Tesco, do we know how to organize ourselves around our customers so that that product can shine in the way that it needs to?
Speaker 3:I think we can do, and actually data does become important here, because you know if you run a retail business, you know which is your best store, you know which of your fastest selling products, but you don't actually know back rich's point, the why. What's the customer doing behind that? Um, are they buying protein products because they're old and they need more protein on their diet, or because they're young and they're down the gym all the time? Understanding that difference doesn't half make a difference to how you go to market with that person. But then I think the other thing is so the data really helps in bringing to life and creating pictures of real people.
Speaker 3:But all of us have been involved in it. You know you've got a supply chain problem, you've got a systems problem. You get sucked into the guts of the business and you just forget what's in it. You know you get a supply chain problem, you get a systems problem, you get sucked into the guts of the business and you just forget what's in it for the customer. And so the leadership of the business always need to be leading the organization back to what I would say. That is the core question what's in it for the customer? And if you're not clear what's in it for the customer. And if you're not clear what's in it for the customer, don't do that do something else.
Speaker 1:Again, you make a really good point and this is something I've come across over the years. People often think data is insight and actually they're two very, very different things, and I think I'd really like to know about some of the work you've been doing at Royal London and ask you how does company culture affect how well we really understand and put customers first, beyond just having data? So making that join between the, the raw materials of what we know about them versus what that actually means, and, and almost like the, why?
Speaker 2:yeah, no, absolutely so. I think from from my perspective and certainly from our perspective at Royal London, starting at the purpose is the most important part. So we at Royal London, our purpose is completely aligned to understanding and supporting our customers and, in particular, we are really focused in terms of how we can build customers financial resilience focused in terms of how we can build customers financial resilience. So for anybody that doesn't know kind of the product we provide pensions and we provide insurance products to customers and we also have our own investment arm, which is our lamb, where we invest and to ensure that we can get growth in those products for our customers. And so, as a mutual and which means that we don't have shareholders because we return our profits to our customers, it's really important again that we invest our funds in the right way so that we can return that profit share, as we call it, to customers into customers' individual pension pots, which obviously is an absolute win from a customer perspective. But really that's our kind of loyalty aspect within our product. So, starting at that purpose aspect and being really clear about how that impacts customers and then really driving that down into our strategy outcomes and linking those strategy outcomes into the work that all the individual teams do within the business. So they've got a really clear line of sight between what they are doing and how it connects into the wider ambition for the business and then within that, within the teams, what we've we've set up is how we map those journeys end to end. So we've got full visibility of those end-to-end journeys and we can see gains that our customers experience from their perspective, not just a business process, which I think historically in organizations is what companies have done.
Speaker 2:So this is very much the customer experience and then also integrating that with customer testing.
Speaker 2:So we've got a customer panel. We've got kind of guerrilla testing that we do. We've got one-on-one customer testing and really understanding from the customer's perspective how they use those products and services and how they interact with the journeys and doing that customer-aided design, as we would call it, and having that really kind of HCD, so human-centered design, in our space. And then you know taking that and then driving that through into build and test and then, once we've delivered that, actually ensuring that we've implemented the right feedback loops and really robustly going through the feedback that we see from the journeys across the different data points that we've got and then using that data to actually then build our backlog and develop the next feature that we want to build for our customers. So so what you see within our organisation is that, right from purpose all the way down to the actual deliverable that goes into the customer hands, the customer has been considered, thought of and actually included in that decision making, which we think is absolutely key to ensuring that customers get the right support to build their financial resilience.
Speaker 1:Just I'm going to go off script a bit because there's a really interesting point you make around just how cohesive that is across royal london. Does this form part of your on-board experience when you join us working for royal royal london? How does that narrative play out?
Speaker 2:so when you say working for ireland, and you mean our employees rather than employees yeah, yeah, no, I just need to clarify because we provide workplace pensions, so I just wanted to to check. So so, for our employees, absolutely so. We have done a lot of work, actually, on our colleague onboarding journey in recent years, and what I've been really, really keen to do is ensure that they have that real kind of streamlined and easy approach, but also that that customer aspect is included in it. So when, um, our employees come in or and are on boarded, they get a whole half day session around the importance of customer, how it's embedded into the business and what the expectation is that for them around customer.
Speaker 2:On top of that, though and tim touched on this earlier about using and understanding the product we are all enrolled in the Royal London Pension, because that's obviously something we need to do across organisations in the UK now in terms of auto enrolment, so they also get a chance to onboard onto the Royal London Pension and experience what it's like to go through that process. It's like to go through that process, and we actually collect feedback from them as they do that, um, because often that's another source of understanding what works well and not so well within the journey, and we've actually made a couple of tweaks based on kind of colleague onboarding from our perspective. So yeah, it's absolutely embedded across the colleague aspect as well as as the day-to-day I think you pretty.
Speaker 1:You're answering all the questions. You go very, very conclusively rich. Do you have you got something to say about this?
Speaker 4:I can see you chomping at the bit um, look on on um, uh, on the whole loyalty and customer strategy. Um, you know, look, we'll get into the risks of data and ai, perhaps, perhaps in a bit, but um, I, I just I'm quite um interested myself in the cultural aspect of things and flow through the organization. Um, certainly, data folk really understand how culture and data culture, a culture of data led decision making, branching into all aspects of the organisation, really fuels behaviours and aligns, creates that sort of axis of alignment in how things are done, as Kat's describing.
Speaker 1:That is underpinned by, um, a strong customer focus, fema, to actually go go hand in hand um tim, I want to ask you about sort of from working on tesco club card what did you learn during that time that today's brands really could sort of remember today and sort of work with today?
Speaker 3:well, funnily enough, one of the first things that I was struck by was this thing about people making decisions on data that they know is wrong. Um, I don't know about making decisions on data that we knew was wrong. We certainly were making decisions on data that we knew was incomplete, because, if you remember, back in the day and I guess it's got worse now there used to be this thing, as it's like drinking from a fire hydrant. Do you remember that expression? And well, unfortunately, for for tesco, we couldn't afford a fire hydrant, we could only afford a tap, so we had a plastic, only afford a tap. So we had a plastic card, we had a mag strike, we had some storage, we knew your name, your address, the store you shopped in and the departments you shopped in, and that was it, and that was costing us about 100 million to get that and so, people, which was about 20% of company profits at the time, by the way.
Speaker 3:So you know, this was a significant bet, and people would come to me and say, oh, if only I knew which product. And I would say don't tell me what you're going to do with the data you haven't got. Tell me what you're going to do with the data you have got and what they learned when you looked at it. What you learned was frequency was much, much more important than you thought it was. There were loads of people coming in five times a week spending 20 quid a time. You didn't even they were invisible to you because you were obsessed with people with big, with big trolleys and families doing big shops. So you had no marketing for lower spend frequent shoppers, although they were hugely valuable, could be, amongst your most loyal.
Speaker 3:The second thing that you learn, which is a sort of a no shit Sherlock point, is your most loyal customers. If you regarded that as being a combination of how often they shopped and the amount that they spent, shopped a lot across a lot of departments. So they bought their meat, they bought their fruit and veg. They bought their health and beauty. They bought their meat, they bought their fruit and veg they bought their health and beauty.
Speaker 3:They bought their wines and spirits, bearing in mind that the history of the last 40 or 50 years has been supermarkets building capability in those categories. So there was still opportunity. And so the second thing that you learned was you know, if we've got people who are coming in like quite a lot, spending quite a lot but not buying health and beauty, can we encourage them to buy health and beauty? The third thing that you learned is you knew where people lived, and so you could work out where the battleground was around store. In those days, retailers were still opening stores, and the most important thing that you could do to protect your business was to make sure that stores that open against you didn't impact you as hard as perhaps they were going to, and so by using the data of where people lived to identify the battleground where you were going to be fighting for customers and investing in those customers not all customers you were able to significantly change the result of those of those battles those you know.
Speaker 3:You had those three things together, and there were a couple there were a few others that made a significant difference to the way in which we were able to run the business and the financial performance of the business, because of course we all love well, no, we don't all love. If you, if you're a customer serving business, you love serving customers, but you can only do the great stuff for customers while the pnl is delivering. When the pnl starts going wrong, then there's huge pressure on the business to cut corners and not to deliver as well for customers, which Kat would say is completely the opposite of what you should do.
Speaker 1:You should do exactly the reverse of that, and of course she's right, providing you're not the one who's going to get fired if you miss your quarterly figures well I think this was again I sort of mentioned this in the intro that you know the the pressure on many of our respondents to improve things without an increase in their funding to make that possible is a real worry for them, and I guess what you talk about and I think what is actually around constraint and constraint from a creative perspective actually can be a wonderful thing, and I think you've absolutely demonstrated demonstrated that, I think, in in our sort of report. 66% of our respondents said that real-time engagement is impossible without centralized data. So how do you then design around that constraint? And I'd like to actually to put that to you, kat, especially with what you were talking about before, with what you've done at Royal London yeah, no, absolutely so.
Speaker 2:You know, I definitely think that that is, and you know the report demonstrates that in the figures that you've just mentioned but that is a that's a real problem in business in terms of that real-time engagement. And I think, from our perspective, if I think about financial products, I don't think there's a huge amount of the population that wake up in the morning and think, oh my gosh, do you know what I'm going to do? I'm going to check my pension. Now some might, it depends what stage of life you're in, but without generalising.
Speaker 2:But there is a huge part of the population that won't, so how do we keep them engaged, kind of, in that process? And so from our perspective perspective, it's very much kind of looking again at how those customers are using the journey, how they're interacting with the journey and really understanding that usage and then being able to find ways to engage with them in terms of actions that they have or they have not taken on the product. So, for example, you may have come in and you may have actioned a change of address or change of name but you may not have completed it. So for us, it's about taking those journeys and setting up a kind of next best action or an MBA to then message the customer, notify them and help them that way. The other aspect is also for us in terms of launching new features.
Speaker 2:Us, in terms of launching new features, it's about being able to communicate to those customers that new features have been launched and talking about actually why it's valuable to them and why they should come in and use it. And I think that's really the key point. Like you can interact with your customer as much as you want, but if you were basically spamming them every week and asking them to come in and do something in your journey. They'll just turn you off, like they'll send your email to spam. They'll delete your notifications. So actually for me, it's around building the journeys in terms of the value and why it's worthwhile to the customers. So what's in it for them rather than what's in it for you as a business to you know, either generate some commercial return or to be able to say that you've got a higher level of engagement. So it's all about building in why it's worthwhile and valuable to the customer from my perspective, it's a crucial thing, isn't it?
Speaker 1:That contract between the brand and the customer often is forgotten, and I think that's where a lot of businesses sort of start to sort of struggle. I think, rich, I kind of want to turn to you now as well, because when we think around building off the back of real-time engagement, the role and potential challenges for ai, 63 of the people we spoke to when we're putting the report together said that there's a widening ai gap between enterprise and mid-market. The word arms race was always coming up and and sort of the fact that well, that we can be outspent by the bigger players, and so what do we do about it, what is really driving that and how do you think we can close that gap?
Speaker 4:look, there is a gap. There is a gap. No doubt there are winners and losers in the as you, as you call it arms race around ai and in a way, it's a paradox because, um ai and the tooling that's available look you kids out there can get access to the same highly tuned base model. Llms that CEOs can get access to, right, so it's democratized. Everyone has access to the same tooling. We're leveling the playing field, aren't we? Using, using ai, what will actually um? No, in fact, it amplifies the differences, because what is the marginal difference and advantage that can be gained via ai, given that everyone else has access broadly to the same commoditized tool set? It's the data that you have that is powering it, data that your organization has around its customer and around the market and around its supply chain, and so on and so forth, right? So fundamentally, um, the organizations that have historically invested in data do have a leg up in in in the arms race.
Speaker 4:And if, if you, if you're not willing to take my word for how important data is um in in in ai and customer experience, conveniently, yesterday, salesforce announced that it was buying Informatica. Now, informatica, if you haven't come across them, are a data management governance platform, allow you to track the health and trusted data, and so on and so forth $8 billion, alex, $8 billion. Allow you to track the health and trusted data, and so on and so forth. $8 billion, alex, $8 billion. Now, that's four times the investment that Salesforce has actually put into AI specifically. So we're putting more investment an organization like Salesforce, we're putting more investment into data than AI, and their expectation is that that's where customers need the greatest help and where customers can find the greatest advantage. So, yeah, I think that tells a pretty loud and clear story.
Speaker 1:So, with that in mind, and again going back to this gap and about the role of ai with data, again, over half of our respondents admitted to making ai decisions based on flawed data. And is that? I guess the question is, you know, is that them being bold? Is that bold innovation or is that actually? I know you mentioned this earlier, cat as well, and we talked about incomplete data versus bad data or is it just risky business and actually all organizations need to just knuckle down and start to sort this this out?
Speaker 4:so look, there are risks and we'll talk about a few of the risks, right, but let's be clear the number one risk is not doing anything, okay, so, um, uh, you know, actually, tim tim used a line very similar to to one that I use regularly, which you know what can you do with the 60 of data that you do have, rather than worrying about the 40 that you don't have or you think might be a bit rubbish? Okay, so do, because there's a lot of value there. There's a lot of value and actually many of the questions that we seek to answer with data, you know, frankly, you know there's the good old Pareto rules apply, whereby 80% of the value is in 20% of the data. Sometimes, certainly when you're starting out, you know things like that. A mindset like that can be very, very helpful to you.
Speaker 4:There are risks, right, you know. If someone gets wrongly sent some information or promotions that don't relate to what they have done, if they feel like there has been a breach in data, you guys can tell us more clearly than me. The cost of breaking trust is extremely high. But let's be clear this is a reasonably well trodden road now and there are tools, methods and approaches out there that allow us to very quickly navigate from the use cases and the value to the data. Using approaches like orientated around data products give us a real clear structure to doing so. There are governance models out there that are really simplistic now, that have been well tried and tested, that are more user-centric than the kind of lockdown protect everything, stop everyone from doing anything with the data type of models that you see come through in some places.
Speaker 1:So, from design through to execution, even on a more modest budget and you know results can be pretty profound um tim, I kind of want to this question because I think it's really relevant hearing what you've just been talking about, rich, and what you've been talking about Kat, going back to your roots with Tesco Clubcard again, 64% of our respondents believe that traditional loyalty is going to be replaced by AI and, almost like being a bit provocative, I want to ask you is that a sign of progress, or are we losing what made loyalty work in the first place?
Speaker 3:I mean it's difficult to quite to understand the point that they think they're making. It seems to me that you know you have. We talked at the beginning about loyalty, the way you run your business, the focus with which you run your business, the fact that you care about what customers think and you try and win their loyalty. You then may add to that some sort of a scheme that rewards loyalty, rewards people for showing up, and the reason that you would normally do that is because, at the moment, you have anonymized data and that what this does is it gives you first party data where you know what's going on. What you then have to demonstrate to the consumer is that, because you've got this first party data, you can run your business better for them than you would without it. Now, some of it will be a bit anonymous, because the fact that a product stays in a range, because you understand who's buying it and you want to look after those consumers, that's great. You don't get the problem of a product being discontinued. But what comes into your inbox in terms of promotions and communications and that should get wider and wider as personalization efforts continue that should reflect what the first party data is teaching me about you. You then then bring AI into it. My view about that is all that that is doing is enable you to use first party data better and to make better insights to do more.
Speaker 3:You know whether it's machine learning? A lot of this is machine learning. Let's be honest. You know we have a I have a business called Eagle AI which works out what you're going to spend next month, what you would like to see on promotion and how much we have to incentivize you to buy that promotion, and then it spreads it over the month. So it's a sort of continuity thing, or six years using machine learning, about eight or nine algorithms, and particularly the affinity engine, with two battling algorithms stretch and reward trying to work out the sweet spot. We've now started putting in a neural network and a transformer architecture into that and it's significantly improved the performance of the affinity engine.
Speaker 3:I can't, you know, I can't see how any of that is saying loyalty is dead. I just think it's it's. It's better tools and, of course, the. The issue is that people who are really keen on doing this and focusing, focusing on this, they have the opportunity to get better and better, which actually means that potentially, there's blue water opening up between them and you, who's not so interested? And just becomes more and more generic and more and more perceived by consumers to be more and more dumb, more and more in it for you than in it for them.
Speaker 1:So just sort of as we before we start looking at so. We've getting some really great questions coming through from from attendees. I've got one kind of final thing would be really good, because obviously you know, we're having this panel because we're here to help. We want to help people take something away from this when we think around the shift in mindset and spend that people need to make. Is it we talked about culture earlier is it culture that's the biggest barrier to transformation, or is there still work that people can do around tech or around data, like where should people start to place their priorities if they're gonna start to make meaningful steps towards delivering a better customer experience? Kat, I'll turn to you first yeah so.
Speaker 2:So yeah, it's a really good question. I think it probably depends where you are from a business perspective, and what I found quite useful historically when I've gone into new organizations is actually doing a little bit of a kind of audit in terms of understanding across key points where the maturity is in the organization. So number one, where it's kind of embedded from a cultural perspective and where it sits on that scale. Number two, how the journeys look in terms of the visibility of that end-to-end and understanding that and where the opportunity potentially is to support customers and also bringing them into the design of that. And then number three, how well actually the technology is linked into that understanding of the proposition. And I think taking a sense check across there and just taking a step back and out of that is a really good starting point.
Speaker 2:I think then the second part that I always like to do is kind of part of that view is experience the journey, and it's good to do it when you're fresh into the organisation, because then you've got very little bias in terms of how that's happened. You're fresh into the organisation because then you've got very little bias in terms of how that's happened. And I've been through journeys and you know many organisations where they said, oh, this is our best journey and it's frictionless, it's digital, and actually I've gone through and experienced it and it's not digital at all and it just. It so happens that I entered through the website but the rest of it's been very paper-based. So I think really having that visibility and then taking that understanding and stepping back and implementing those strategy points that we've talked about today and really understanding how to prioritize that in terms of what the most important is but you know, experience the journey, like ask your customers, like don't assume you are not your customer, and so ask them and understand them would be my first thing that I would do, tim.
Speaker 3:Yeah, I think you have to start with the culture of the organisation. People face uncharted territory. They know whether to turn left or right, and what you don't want is you don't want your employees turning right when they should. Of course they should turn left. Everybody knows that somebody who works for eagle eye would turn left. In these circumstances, you know.
Speaker 3:So I think it is about establishing the culture. If you establish the culture, then the use of data, the use of confidentiality, the use of the application of security, all of those things will follow that cultural north star and it's the. It is the only. It's not the only thing that matters, but it is the critical thing. It's incredibly difficult to do. It's not hugely changed by ai. You know, it's the same thing that managers were trying to do in the 1950s and the 1960s is to create a culture. That means that we reflect the things that we want to be, but you don't always get it right. It's a source of massive competitive advantage, but it is the most important thing, and then everything else can hang off that.
Speaker 1:And Rich, I guess, to you, with all the clients that you're talking to day in, day out in your role, where are you sort of advising them on sort of what the priorities are, what their first steps should be to get this right?
Speaker 4:Yeah, so typically we are supporting organisations with their data strategy or implementing a data strategy, and investment is usually a big issue, right, for all the reasons we've outlined before.
Speaker 4:The number one piece of advice we give is to treat your stakeholders in the organization like your investors, like your investors. Treat them like investors because you're asking them to invest in a belief that this is going to drive outcomes for the wider organizations. Investors make decisions based on rationale, cold hard facts of returning investment, but also reason, right, and you need to be reasonable with them in terms of the time that it will take, the cultural dependencies and the outcomes for the customer, orientated around the vision and, ultimately, treating stakeholders like investors. You also very often want to start small-ish, right. Start small and great For those organizations which perhaps are trying to build into the world. We're describing and painting a picture of Starting small, getting the flywheel turning, having success stories that you can talk to, doing the storytelling around that Refuel, having a reinvestment model that then allows you to grow from there and build on that success. That's typically the route to building a data-centered organization that is capable of being customer first.
Speaker 1:Fantastic. So I'm going to just turn to some questions from our audience. So Rachel's question is and I think this is a really pertinent question now we talked around the challenges the challenges we've all faced, but from your own perspective, sort of where have you seen good loyalty and what made it different? So what brands do you think are really nailing this and and that we can all learn from?
Speaker 3:I'll go first I mean my favorite. One of my favorite stories is sorry, did you?
Speaker 1:No, Tim, you go first. Did you say cat go? I did say cat.
Speaker 2:No, it's fine, Tim, on you go, you've started it's not a problem.
Speaker 3:Well, ok, look, I thought I was taking the pressure off rather than interrupting. I apologise. There's a restaurant in the us called ruth chris. It's a very nice upmarket steak restaurant, excellent if you go. It's the butter, the secrets, the butter on the steak gotta, gotta try it anyhow. So we're going to this restaurant, minneapolis, because we're visiting target.
Speaker 3:So we have to be over the weekend to see target on the monday morning, and so I take my colleague to this restaurant and we sit down. And as we're sitting down I look across and there's a table over there and the server is taking the napkin and placing it on the customer's lap. But what they do is they take the white napkin off the table and they put a black napkin on the customer's lap. I think that's a bit weird. So, anyhow, they come to me and they do exactly the same thing. So I said to them do you mind? Why do you do that thing with swapping the colour? They said oh sir, we find that our customers who wear black trousers quite a lot of them wear black trousers they don't like getting the white lint from the napkin on their trousers. So if you're wearing black trousers we change to a black napkin and I literally said to this server if you care that much about my trousers, I can't imagine what you're doing with my steak.
Speaker 3:And so it's really. I think back to Kat's point about walk in their shoes and do things that demonstrate that you understand what life is like that's a wonderful example, kat.
Speaker 1:Have you. Can you follow that? I can't.
Speaker 2:I'm not sure if I can quite get into that detail about steak. I really like that one, tim, I've not heard that one before. I think mine's. Mine's probably similar, but but the same in terms of knowing your customer, um. So I think for me, um, we do quite a lot of um holidays as a family and you know jet two for me is a really good experience. So I wouldn't say that I've historically been kind of pro doing the package holiday aspect. I've had some bad experiences historically.
Speaker 2:But the thing that I enjoy from a jet do perspective is from the moment that you turn up to the airport to kind of the moment you get to get home that there is a real kind of support and understanding in that space.
Speaker 2:So I think what they've really kind of clinched is that idea in terms of check-in especially with young children can be really quite stressful and painful, and what they always have on hand is they always have people that work for Jet2 to support the check-in.
Speaker 2:They're handing stickers out to the kids, they always entertain the kids and they make sure it's as fast and efficient as possible. So it's literally kind of bag drop and off you go and then once you get to the plane. It's similar there's packs given out to the kids for colouring, for drawing, for entertaining, and I think what they've really honed in on is, for those travelling with children, like that's the most stressful part, and therefore they've really understood that from from the parents perspective, and they found ways to alleviate that, to almost make it more relaxing for the parents, and so actually when people are coming to book holidays or excursions, it doesn't matter that they're maybe a bit more expensive. Actually they know that the pain will be taken away in terms of that kind of experience from travel. So that's definitely somebody that I regularly reuse, just based on the fact that they make it so much easier for traveling with wee ones.
Speaker 1:I think that's great. I've got one. We'll do one more question from the audience, though. We've had some fantastic questions and actually this one really sort of piqued my interest. One from Antonia is the role of AI in loyalty only ever to drive more revenue, and what else can it do for the customer experience? And, I think, your two anecdotes. It would be great to understand how you think AI can deliver on those sort of really nice softer experiences. Rich, do you want to answer this one?
Speaker 4:Yeah, look, agentic AI. So Tim spoke very nicely around using AI, machine learning, to optimize business problems. Obviously, we have agentic AI out there in the world now that can be relatively easy to use, transform in some respects the way that people communicate with customers, right, and there's some fabulous examples that people may have experienced. And there's probably some suboptimal examples as well, but where we've encountered a chatbot which is completely rubbish and sends us into some sort of death-loop spiral of repetitive questions. Irrespective of all of that, that wave is really taking over and, by different measures, people expect the majority of that sort of higher volume customer experience touch points to be handled by agentic ai from as early as 2026, 2027, right, so so so that is here to stay. The question is how do you? You know we've there's really bad examples where it's a massive turnoff. There's really good examples where it's seamless. Who wants what? Um, uh, which type of customers actually prefer the quicker, easier version that they can use whilst they're also making the kids dinner, or they can, or they're, you know, on the bus to work, right, uh, versus those people who want the genuine, more personal touch and actually are quite offended by talking to a robot. How do you identify those? How do you? And then, during that journey, how do you make sure, sure that the AI agent has sufficient information in order to actually satisfy requests?
Speaker 4:There's a growing risk as well and this is a bit of a random one, alex, but I'll tell you anyway there's a growing risk in the future as well, if they're deployed too broadly that AI starts to learn from what AI thinks a customer is rather than what a customer really is, as Tim and Kat are describing, right, you kind of. The classic example at the moment is if you Google what is a picture of a baby peacock, right? If you Google it, 90% of the images that Google produces are generated by ai. That means that any new images are based on ai versions. The ai is learning from the ai.
Speaker 4:So the risk of agent-based service is that we become so abstracted from the customer and what they truly want that, um, actually, we become out of touch and our vision and understanding of the customer and what they truly want, that, um, actually, we become out of touch and our vision and understanding of the customer becomes morphed. So, irrespective of these kind of big leaps forward that we're making with ai, um, the human in the loop, the wrapper. The control that the organization needs to have is absolutely fundamental and I think that you there's a really good point.
Speaker 1:I know this will be our sort of close. We'll move on to closing comments. Like you said, ai is fantastic, so it starts learning from itself. And then we have a problem when I think about some of the work we've done, and certainly in the quick serve dining space. So we've recently with wagamama, which now we've got, I think, a million active users with with zillionaires, uh, through azuri group, where we've got a million active users and we've actually just launched for ask italian as well.
Speaker 1:Those aren't currently ai driven, and what they are doing, though from you know we think, around the soft things that great loyalty and understanding your customer can bring, is they're building that genuine affinity between the customer and the brand, where they're seeing that those restaurants as like a trusted destination, where they're actually made to feel wanted, they're given reasons to return, and it's not that purely transactional, which is certainly when we think about customer experience, when we get into loyalty, those things can can become terribly transactional if you're not careful.
Speaker 1:And I think those actually listening to customers and understanding customers and given giving them those little reasons to return. To go back to your point, kat, reaffirming that contract between the customer and the brand. I think is is kind of really, really crucial. I think you know, I know I work for them but I think, anne, I have done an incredible job working with those brands to deliver that I think just in the last few moments. Just quick roundtable. It'd be great to have some sort of final thoughts. I think, starting with you, kat, any kind of closing comments you want to make.
Speaker 2:So, in summary, I think the key takeaways should be you know, know, really think about your culture and how you embed customer in this space and, in doing that, get to know your customer, understand their needs, understand why it's valuable for them and why it's worthwhile, not necessarily why it solely just drives your business efficiency. You know the two have to be considered simultaneously. You know the two have to be considered simultaneously and then, I think, ultimately, looking at ways that AI can supplement that and enhance that, rather than them being two separate things, is key. So that probably my key takeaways in summary for everybody.
Speaker 1:Fantastic Tim. How about you I?
Speaker 3:think that AI has just sort of made this a bit more fashionable again, and you know boards and shareholders are asking the question what are you doing? What's your approach? How do you? But I think, at the most fundamental level, if I know what you buy and if I can open up a direct channel to communicate with you about what you buy, surely I can do a better job. So I don't send you.
Speaker 3:If you think about paper flyers they're not as popular as they used to be, but the idea still exists. You produce a newspaper. These are my, my promotions this week. Come and shop with me. It is very easy digitally to take that and to reorder that to be what's most relevant to you in the store this week rather than what's most relevant to us in the store. But in in america they will always start with meat and soda, coca-cola type products. They will always be so. If you don't drink soda and you're a vegetarian, every supermarket in america says we're not really a shop for you, mate, whereas of course, if you personalize it, you can say yeah, we are a shop for you because we understand what you like and I think you know if you take that simple example and then people will be doing it, and they will be doing it better and better, and it's pretty self-evident that that enables a better experience. So my view is you you have to get the customer data if you want to be a customer facing and customer focused business fantastic rich.
Speaker 1:You have like five seconds?
Speaker 4:come on invest in data to reveal what people do and invest in cx to understand why they do it, and returns and returns on investment will be clear fantastic, I think.
Speaker 1:For my part, it's talk to your customers, even if you know, just watch your customers in your store and see what they're doing. Um, I want to say thank you so much to everyone on the panel. Um, it's been, you know, one really appreciate your time and, hopefully, thank well. Thank you to all our uh attendees as well for joining and and I really, really hope that you you've got something useful out of this from some incredible panelists. We will be sending out a link to the recording after this finishes and we'll also send out a link, if you've not already got it, to our report. Uh, know me or lose me. Um, so, thanks from and and uh, thank you to everyone for coming thanks very much indeed, thank you.
