IN CLEAR FOCUS: Professor Mohamed Zaki of Cambridge University discusses his new book “Data-Driven Customer Experience Transformation.” Mohamed explores the shift from product-centric to customer-centric business models, distinguishing customer satisfaction from delight, and leveraging AI and data analytics to predict customer behavior. Mohamed also shares his insights on omnichannel experiences, personalization strategies, and real-world case studies, including Caterpillar’s CX transformation.
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Episode Transcript
Adrian Tennant: Coming up in this episode of IN CLEAR FOCUS …
Professor Mohamed Zaki: One of the key things is the interpersonal relation with the customer, which is coming from where we see now a lot of the tech firms are going, it’s personalization. So we saw this with all these new tech firms, what made them successful on their platform, they understood every customer, what they really care about, what they need, what they prefer, and they offer that to them back.
Adrian Tennant: You’re listening to IN CLEAR FOCUS, fresh perspectives on marketing and advertising produced weekly by BigEye, a strategy-led full-service creative agency growing brands for clients globally. Hello, I’m your host, Adrian Tennant, BigEye’s Chief Strategy Officer. Thank you for joining us. Recent research from Kantar reveals a striking insight. Customer experiences contribute more to brand perceptions than advertising. In fact, while paid media delivers 25% of brand building impact, direct customer experience and word of mouth account for around half of all brand perceptions. Our guest today is uniquely positioned to help us understand this data point. Professor Mohamed Zaki is based at the Institute for Manufacturing in the Department of Engineering at the University of Cambridge, where he serves as Deputy Director of the Cambridge Service Alliance. This research centre brings together the world’s leading firms and academics to address digital transformation challenges. Mohamed has consulted and lectured for over 50 organizations, including Manchester United, Caterpillar, and IKEA. He’s also the course leader for the Data-Driven Design for Customer Experience online course at Cambridge University Press and Assessment, and co-founder of Customer Experience Insights Limited, which developed the 360CX AI platform for customer engagement decision-making. He serves in advisory roles for several companies, most recently as AI Innovation Advisor at Tactful AI. His new book, published by Kogan Page, is “Data-Driven Customer Experience Transformation: Optimize your omnichannel approach,” which is also our selection for the BigeyeBook Club this month. To discuss some of his book’s key ideas and frameworks, I’m delighted that Mohamed is joining us today from Northamptonshire in the UK. Mohamed, welcome to IN CLEAR FOCUS!
Professor Mohamed Zaki: Thank you so much. It’s a pleasure to be here with you, Adrian.
Adrian Tennant: What inspired you to write “Data-Driven Customer Experience Transformation”?
Professor Mohamed Zaki: So I work most of my career helping organizations around this area in particular for a while. So most of my research helping firms to understand how they can leverage data and AI to design better experience, but also as well to manage it in particular. What makes me drive to drive the book is actually the fast pace of the era that we’re living at the moment, especially the digital transformation that’s happening with many firms. When I’ve been asking a lot of practitioners, they were struggling a little bit with the right tools and frameworks that enable them to design the future of services and experience for the firms. But more important is leveraging this new emerging technology like AI and data to enable them to understand their customers better. And this is particularly problematic in enterprise firms or established firms, not the digital-born organization. You can see digital-born organizations, they’re quite starting as a startup, nimble, their tools and softwares and solutions is quite up to date. So that’s allowed them to become more data-driven, if you like, organization. Think about ChadGPT, for example. This is an example of a data-driven business organization, which has managed to do a better experience for users when we are interacting with a machine, in this case, a conversational AI. There will be a lot of attempts before, but they were the most successful one, and that came from the statistics. Many users daily joining their platform now, and this is because of the experience they had with this conversational AI capability. So I guess to answer your question in particular, there is need for a lot of practitioners now with fresh thinking, fresh tools that go beyond the traditional ones that exist for a while, like design thinking, journey mappings, and emotion mapping. So I thought, let’s leverage some of my engagements and interactions with a lot of firms, and most of the tools I’ve been developing through my research in this book to communicate and disseminate, and hopefully this is helpful for people.
Adrian Tennant: In your book’s introduction, you highlight how we’re living in an experience-driven economy, where even beloved brands risk losing market share due to a single negative customer experience. Mohamed, what’s driving this shift?
Professor Mohamed Zaki: This just came a lot as well from a lot of facts and figures that a lot of big practitioner firms, we’ve been surveying customers to understand, you know, the new generation of customers, what they think about the brand they are engaging with. And you can see the new wave of customers, let’s say this way, needs not the standard ways of services or the transactional strategy that we used to have with established firms. They need personalized experience, they need the speed, they need care about some of their issues and problems. Hence, this is a discussion in the book, to deliver a quality product or a service is not at the moment making your biggest competitive advantage. You have to have a quality product, of course, and quality service here, offer it to your customers. But what differentiate you versus your competitors is the customers really feel that they have a great experience and seamless experience with your brand. So we saw a lot of statistics, the PwC for example recently issued a report saying 32% of the customers that they surveyed, they’re saying they would switch if they have one bad incidents with the brand that they love. And that’s really a big statistics. Salesforce as well came up with a report that says 75% of the people that responded to the survey, they need consistency in the experience. And this is a big problem that I’m discussing in the book, because again, when organization building their different offers through different channels, the way I call it digital channels, that’s including apps, for example, Now we are in the era of conversational AI, so chatbots and web chats, for example, or through social media interactions as well. So all these kinds of digital channels, this is your gateway to engage with your customers better. But then you have probably some of these firms have as well physical channels, right? So this is another, if you like, complexity as well to the way you are engaging and interaction with the customers here. Then I guess the social part as well. So probably we have an employee engaging with our customers as could be through customer service or sales representative, this kind of human to human interactions as well, adding as well more complexity. So if you think about it, how can I establish firms, try to manage that consistency experience. And we’re hearing this a lot from customers complaining that we have a great experience in your physical place. For example, we enjoy shopping in your retail, but when I go to your app, it’s not good enough or cranky or it’s not that seamless. And the more difficulty as well it comes is actually when the customers go and check a product, for example, over your app or your website, and then they browse it and they like it and they want to go buy it from your physical, right? So they don’t want to buy it from your digital channel. So that makes as well the journey going as a configuration from the digital to the physical here in this case. And sometimes as well, the availability of the product, they go to the physical place, they don’t find the product. So the experience came as very negative. So that continuity and the consistency as well, that you have a great experience in the digital channel, similarly as well a great experience in the physical, make the overall experience of the customers that they have, I like this brand because whatever I’m dealing with across these different channels, they have a consistent experience it provides you. But to do this, you need different ways of thinking about what we call customer experience centricity here. So because you need to think about the holistic journey, that’s completely different than thinking about these channels in isolation. And that’s, I guess, that’s where a lot of practitioners are struggling with the traditional tools, because they don’t have ways to think about this as a holistic journey and interactions between these different channels. Hence a lot of discussions in the book about how can we think about these different engagements and interactions to help us to build a better and seamless experience to our customers.
Adrian Tennant: Well, of course, you discuss the transition from product-centric to customer-centric business models. What are the key challenges organizations face in making this transformation?
Professor Mohamed Zaki: That’s a very good question, Adrian. So I think if I would like to summarize it, there is many challenges, obviously, and contextual, but the way we found in a lot of our research with firms, it could summarize into three key pillars here. One is what we call it the attitude, right? So typically because you are established firms, some of these firms are 30 years old in general, they tend to have a strategy like was completely different than the world that we live in at the moment. This is why this nimble and agility is quite important here. But the question is, sometimes you have resistance that could be from your employees inside the firm. Once you’re starting to introduce new strategy, they don’t get it, right? And we saw a lot of firms, some of them doing very aggressively, right? So we have to change, we have to do it, they don’t break it down. and they don’t do it incrementally as an innovation level, or they’re not preparing their employees about that change, which is a lot of these kind of efforts could fail. So there is an attitude challenge, right? So how can I convince my, if you like, not only my employees, the ecosystem of actors as well, or if you like, the other organization that works with me, that this change is happening and they have to align with my strategy in this. But also as well the customers, you have to introduce this kind of engagements and interactions and attitudes to the customers as well, and how they accept and adopt the changes that you are providing here. I think the second key challenge that they face in general is the capabilities. This needs a completely different capabilities than the existing ones that they have. And if you think about data-driven or the world of generative AI, large language model, these technologies that now it’s in every board and every firm, how we can leverage it, how can we use it in our products, in our service, in our engagements with our customers, in social media, with our employees as well, how they can use this. So, it’s a big question, a big challenge how to systematically, you are introducing these capabilities and build it up to serve your employee efficiently, obviously, and secondly as well, build the right experience for your customers, which is hopefully can bring some return of investments to your firm. I think the last one is the methods. So, we used to leverage a lot of methods completely different than the digital transformation asks us to do. So before we used to have a marketing for example focus group will averaging survey like net promoters score for people that doesn’t know what the promoters survey metrics that we evaluate how customers can promote our services to their families and colleagues so it’s basically a question. And if you give a higher score, that’s mean you are quite loyal and promoter to our firm. And if you get lower, that’s mean that you’re really not satisfied for our service and organization. In the world that we’re living in the moment, these surveys doesn’t give us the complete picture about the customer evaluations about our services. And the reason is we have digital channels that we have a lot of data coming from this. This is through browsing capability, behavior of customer engaging with these digital capabilities. So this is a lot of data here that you can leverage to understand how your customers engaging with your digital capabilities. Also as well, customers interacting with you through conversation now. So chatbots and stuff like this is the wealth of data. You can understand what works well and what doesn’t work well. If you have as well the behavioral data, how many of your customers, so we’ve been talking about customer life value, how frequent your customers is buying, clustering, segmenting your customers, et cetera. So how to combine these different data and leverage this as a key inputs for capabilities like machine learning and AI to enable you really to predict whether your customer is loyal or not. And this is examples of the changes of methods from you are leveraging one metric or one way of evaluating your customers into a new ways of engaging with the data that you are capitalizing with or you are sitting in your system to help you to understand better what the customer think, feel, and actually do when engaging and interacting with your firm.
Adrian Tennant: Kind of more holistic approach than just quantitative or qualitative research.
Professor Mohamed Zaki: Exactly. And obviously that’s what comes back to your question, the challenge, because it needs skills, it needs investments, it needs structured way to capture these data together. And again, you know, breaking the silos and culture inside firms to enable this to be implemented in the right way to become a customer experience-centric firm.
Adrian Tennant: Mohamed, in chapter five of your book, you distinguish between customer satisfaction and customer delight. What key elements contribute to creating delightful experiences?
Professor Mohamed Zaki: Back to we are competing or any competitive landscape. So customer has many options to go to firm A or firm B. To make, for example, a firms to distinguish their engagements and interaction with customer and become loyal to them, they have to go extra mile with the customer. So become a business imperative now. satisfying our customers by just providing the things that they order or the product that they like us to do with the normal way of doing it, become now completely different. So I’ll give an example here. What makes a lot of people using Amazon, for example, compared to different retail, some of the services like next day delivery was very successful, which is build that seamless interaction and engagement. And the way, as well, Amazon now thinking about it, how we can do this from next day or next two days into the same day. This is how you go extra mile with the customers here, how you delight your customers because this is what they care about, this is what they need about. So we came up in our research, there is a couple of key dimensions that you need to think about. So obviously as well, when we come to delight, from the delight, it’s an emotional arouser, right? So you have to surprise your customer, you have to provide the things that they wouldn’t expect. So hence the difference between satisfaction and delight, it’s an extra effort now you go closer to the customers here. I think one of the other key things is the interpersonal relation with the customer, which is coming from where we see now a lot of the tech firms are going, it’s personalization. So we saw this with a lot of digital-born firms, so Netflix, Facebook, and all these kind of new tech firms, what made them successful on their platform, they understood every customer, what they really care about, what they need about, what they prefer, and they offer that to them back. which is a little bit not there with a lot of established firms. It’s very hard for them. And this is because they’re not capturing the right data about the customer in a systematic way and put them together to enable them to understand what is really the preference for their customer in this case. So how you personalize, how you build interpersonal relationship, this is another key factor here to enable you to come closer to your customers. I think the third element is problem solving. At the end of the day, customer, for example, when they go to customer service, this means that they have issues. There is some service failure or some problem that they had with the company. If dealing with this in a subtle and a quick way, sometimes the customers see this as a lacking that the company are lacking behind in terms of providing the right experience for them. And how many of us, if I’m asking all your audience and yourself, you have issues with customer service, many of us will say this is not working, right? And again, because firms using customer service as a cost center, it just function to be there. to respond to the customer’s inquiries, but what we call a more customer experience-centric firms is the one that understand this is a big channel or an important channel that we have to really resolve customer issues very quickly, even if some of them as well lose some money. So they’re saying, even if we lose some money as well from this kind of inquiry, but at least the customer will attach to us. We retain the customers for a long time and become loyal to us. I think one of the key things as well, we are human, we are dealing with senses. Whatever channels we are interaction or we’re offering to our customers, it has to be very delightful, right? And this is why when you’re producing an app or a website or even in a physical place, it has to be really in a very sensorial element, has sensorial elements to it to make you delightful when you are engaging with this. Also as well the sequence of events right experience here it has different stages when the customer engaging it could be a pre-purchase within the purchase and after purchase a lot of firms always thinking about the purchase and after purchase and worry less about the pre-purchase But this is really important. Recently, I’ve been talking to a lot of companies and they’ve been saying, gone these days as well, that customers now go and ask Google. Actually, now people asking to LGBT now, if I want to take this course, for example, give me the best courses now that is happening, or if I want to ask products. So how now you have to really quantify what is going on in the pre-purchase stage and become on top of this new technologies that is happening. So at least that you are trying to offer and complement the solution to build a life experience for your customers. Lastly, you should give some perceived, what we call a perceived control, a control to your customers. And this is where Apple were really successful when you go to Apple stores, for example, you find the employees are really customer experience centric because they’re not there for selling products, they’re there to be advisor, right? So they are really supporting you through the process and to enable you to take the right decision. And this is really completely different than a traditional salesman who has actually tried to really sell the product to you. So now for me as a customer is when I feel that I’m in control in the whole process, I will be delighted. I don’t feel that I’ve been ripped off or the company now try to advise me with anything to enable me to buy the product or service, but actually someone advising me. And that’s what we really, as a human, we really like. We like someone advise, take our hands and hold our hands until we take our decision by ourselves.
Adrian Tennant: Let’s take a short break. We’ll be right back after this message.
 | Adrian Tennant: In partnership with our friends at Kogan Page, June’s Bigeye Book Club selection is “Data-Driven Customer Experience Transformation: Optimize your omnichannel approach.” The book’s author, Professor Mohamed Zaki of the University of Cambridge, delivers an essential guide to creating consistent, exceptional customer experiences across digital, social, and physical channels through the power of data. “Data-Driven Customer Experience Transformation” shows you how to leverage AI and data analytics to predict engagement, understand customer loyalty, and forge stronger relationships. Through rigorous research and compelling case studies from organizations including Microsoft, KFC, and Emirates Airline, Mohamed demonstrates how to design and implement customer experiences that drive growth and build brand loyalty. As an IN CLEAR FOCUS listener, you can save 25 percent on “Data-Driven Customer Experience Transformation” when you order directly from the publisher at KoganPage.com – just enter the exclusive promo code BIGEYE25 at checkout. Shipping is always complimentary for customers in the US and the UK. In our increasingly complex omnichannel world, let “Data-Driven Customer Experience Transformation” be your guide to delivering exceptional customer experiences. |
Adrian Tennant: Welcome back. I’m talking with Professor Mohamed Zaki, author of “Data-Driven Customer Experience Transformation.” Mohamed, your book emphasises the role of AI and data analytics in understanding and predicting customer behaviour. Now, as regular listeners know, we love case studies on IN CLEAR FOCUS. So could you share a specific example of how organizations can use these technologies to enhance customer experience?
Professor Mohamed Zaki: Perfect. So this is a second section of the book, which is talking about now, we spoke about designing and how we use these digital and physical and social interaction is already experienced. Now, you need to test whether your design match the expectation of the customers and really the customer like whatever journey are offered to them. I will talk about a story and a case study and real story here. So when I starting doing some work around this, it was interaction with Caterpillar. Obviously, this is one of the leading asset heavy manufacturer organization. and as you know that Caterpillar is also as well doing sell their digger and crushers through dealers as well globally but also as well support this through a service for this like any cars as well like automotive as well so you have a car you typically as well have to service this car afterwards And one of the key things that we had as a discussion at some point when you start in this product catapult was really keen about the product again coming from a product strategy and service, how to make the best product that we can offer to our customers which is really obviously important. So they were focusing in the AI capabilities around machine data, right? So how can we predict when the machine will fail, which can advise our customers, this is the right services that we should do with it. We send the technician to fix it to you in your site, or you send it back to their workshops. And that’s going to enable them really to make the customers up and running, because obviously their customers, like in construction and mining, they need all these diggering crushers up and running most of the time. So this availability service, if you like. But with starting to say, but do you want to understand as well, what is the customer really think and feel about the services that you offer to them? So they have a traditional way of, obviously, after a service being run, they ask a list of questions, which is many firms are still following. That’s including net promoter score, for example. So how likely can recommend our services to your friend and colleague in the business, etc. Customer satisfaction score, so that’s again, it’s a rating score from 0 to 10. Interestingly, when we looked into a historical data, we found that customers sometimes give you 9 out of 10 or 10 out of 10, which is represent that you should be a loyal customers in this case. In the qualitative comment, they are heavy complainer. So they’re starting to say that we are, don’t like, for example, a technician comes to us, very not communicating well, what’s going to happen with the machine, and many other issues that is happening as well there, including some issues in the product defects and etc. But that shows there is a misalignment between a source of data here, which is the qualitative comments, in the same instrument, which is a survey, versus the quantitative numbers, which are represented by the Net Promoters call. And then we took this analysis as well, and then we complement it with the behavioral data. So this is the sales data. So actually how many of their customers, same customers that responded to these surveys with actual buying for the service or not. And when you do the traditional ways of segmenting customers, we found a big list of customer likely to chair. And if you connect this behavioral data with the attitudinal, and if you like the emotional data, the way I talk about it, you found a lot of regular complaints that is happening from the customers and the company didn’t make an attention to what is the customers was really saying in this qualitative one. And the reason for this, because if customer give us nine out of 10 and 10 out of 10, why we look into the qualitative or in the customer service or the conversation? Because they are loyal already. But this made us start thinking around, if we manage to support the company here by connecting these different data points, showing them how this can be represented as a feature to machine learning capability, they accurately can predict whether the customer is really loyal or not loyal. And this is a real case and real implementation. Obviously, they can take this approach now and starting to complement these insights and become part of the process at the moment.
Adrian Tennant: Excellent. As I mentioned in the introduction, Mohamed, you co-founded Customer Experience Insights Limited and developed the 360 CX AI platform. How does this kind of AI-powered decision-making platform help organizations manage customer experience in real time?
Professor Mohamed Zaki: So this is again come back to similar from that case study that we’ve done with Caterpillar. So a lot of organizations starting to ask the same questions. It’s like, we need to really have a 360 view about these different data points that are coming from different systems. So what we typically say to firms, don’t ditch net promoter score, it’s one data point, right? We’re coming from a data science and AI world, every data is matter. It’s you need to qualify whether really the customer is really loyal or not. And by looking into the different data streams that you have, that’s including customer service data, which is coming from call centers, conversation data that coming from chat interactions, and also these kind of textual data, if you like. So this is where the large language model is a natural language processing. Now it’s quite advanced that enable us to go deeper into what really the root cause of the customer is complaining about. Where are the journey that the customers really always complain about? Where are our value creation elements that customers like and dislike as well? So this is including some of the things that we talk about, like resources and activities that we’re doing with our customers in this case. And connecting this as well with the typical customer life value, quantitative metrics and behavioral data, enable us to saying the valuable customers for us, like the gold customers or the platinum customer, where are the issues that they have with us versus the thing that they like about us? How can we replicate this with the golden customers? And also as well, does our effort to recover some of our low value customers is really valuable or justify what we should do with them or not? And with the 360 AI, we provide this quantification and insights to enable firms, A, to systematically connect this data together, B, try to develop these kind of dashboards and metrics to enable them to become on top of their customers’ issues and behavioral problems, and also as well advise them about what will be the right actions as well to enable them to really recover some of these issues.
Adrian Tennant: Sounds fantastic. What’s the most important takeaway you want readers to implement after reading your book?
Professor Mohamed Zaki: I do a lot of executive education as well, Adrian from undergraduate all the way to executive, to some of our industry consultancies, doing with a lot of firms. And one of the, if you like, the proud moments that we have when a lot of these executives come back and saying, oh, we took the portfolio of tools in Bluebrand. that you taught us, or in the case of the book now, it’s been listed there, and try to see in their context how they can implement their future configuration of services by connecting digital with physical and social, and where are their, if you like, investment should go for in terms of the resources and activities you do with their customers. And it’s a prime moment when some people say, we took this, we go to our managers, for example, they told us, let’s implement it, right? This is something, obviously, as an academic, as an industry advocate as well, for some applied research, would love to see, hopefully, from the people that are reading the books, take some of these tools and framework, change their current practices that they are doing at the moment, given the complexity that we’re living in. Hopefully, this can have a lot of outcomes and positive outcomes for their firms.
Adrian Tennant: I look forward to reading that in maybe the second edition.
Professor Mohamed Zaki: After I’ve taken a break from the first edition!
Adrian Tennant: Great conversation. Mohamed, if listeners would like to learn more about your work at the Cambridge Service Alliance, your Data-Driven Design for Customer Experience course, or your book, “Data-Driven Customer Experience Transformation,” what’s the best way to do so?
Professor Mohamed Zaki: Reach out. So probably my email as well. We’re going to be with you. We are available. If you have any questions, please drop us an email. I’m in LinkedIn as well. So please reach out if you would like to be connected. I would like to hear your stories, how people use these tools and frameworks, and hopefully you found it useful for yourself and your firm as well.
Adrian Tennant: Excellent. And a reminder that IN CLEAR FOCUS listeners can save 25 percent on “Data-Driven Customer Experience Transformation,” when you order directly from KoganPage.com using the promo code BIGEYE25 at checkout. Mohamed, thank you very much for being our guest this week on IN CLEAR FOCUS.
Professor Mohamed Zaki: Thank you, Adrian. It’s a pleasure to be with you here and your audience.
Adrian Tennant: Thanks again to my guest this week, Professor Mohamed Zaki, the author of this month’s featured book, “Data-Driven Customer Experience Transformation.” As always, you’ll find a complete transcript of our conversation with timestamps and links to the resources we discussed on the IN CLEAR FOCUS page at Bigeyeagency.com. Just select Insights from the menu. Thank you for listening to IN CLEAR FOCUS, produced by Bigeye. I’ve been your host, Adrian Tennant. Until next week, goodbye.
TIMESTAMPS
00:00: Introduction to Personalization in Customer Experience
00:26: The Impact of Customer Experience on Brand Perception
01:30: Guest Introduction: Professor Mohamed Zaki
02:50: Inspiration Behind the Book
05:09: The Experience-Driven Economy
09:28: Challenges in Transitioning to Customer-Centric Models
10:40: Key Challenges: Attitude, Capabilities, and Methods
14:06: Distinguishing Customer Satisfaction from Delight
20:27: Creating Delightful Customer Experiences
22:05: The Role of AI and Data Analytics in Customer Experience
27:13: Case Study: Caterpillar’s Customer Experience Transformation
29:36: Takeaways from “Data-Driven Customer Experience Transformation”
31:12: Conclusion and Further Engagement
