Estée Lauder’s Raheel Khan On Maximizing Generative AI

Speaker A: Foreign

Speaker B: Lauder has long been a pioneer in using artificial intelligence, and they're now breaking new ground with their in house Beauty Trends platform. In this episode, I'm talking with Raheel Khan, SVP of Foresight and Growth Intelligence, about how it helps them stay ahead of today's consumer preferences. We're talking about the role of generative AI at the company, some of the new talent needs it requires, and where their data plays in all of this. Stay tuned for that and more on this episode of Tech Transformation. Welcome to Tech Transformation with cgt. I'm Lisa Johnston, Editor in chief. Thanks for listening to us today. We took a little vacation, but we are back with a bang. So in this episode, I'm talking with Raheel Khan, svp, Foresight and Growth Intelligence at Estee Lauder, about the role of generative AI within their organization. Raheel was the keynote speaker at CGT's Consumer Goods Sales and Marketing Summit this fall. If you were there, you had the chance to see their in house Beauty Trends platform in action, which helps Estee identify social trends more quickly. If you missed it, no worries. You're in luck because he's going to talk a little bit about it today, as well as share some details into how they're building up their organization to better use AI. So, Raheel, welcome.

Speaker A: Hey, Lisa. It's so good to see you and, uh, happy to be here.

Speaker B: It's awesome having you here. It's great to see you again. Uh, you did a tremendous job as a keynote speaker. You always want someone to kick the event off with a bang and be really provocative, and you delivered. Um, but for those of who weren't there or perhaps aren't familiar with you, can you just get us started? Tell us a little bit about yourself and about your role at Estee.

Speaker A: Sure. And by the way, it was, uh, amazing to be there and learn a lot as well. So thank you for having me. Uh, so, yeah, uh, my name is Raheel Khak. I am the senior Vice president, uh, for enterprise marketing at the Estee Lauder Companies. Um, for those of, uh, your audience who may not know, Estee Lauder Companies is a prestige, beauty, pure play, uh, with a portfolio of aspirational brands serving different consumer segments and consumer needs across skincare, makeup, uh, fragrance, hair. Uh, so my role, I'm, uh, really honored to lead an amazing team that is responsible for foresight across our brands and category. Um, you know, we, uh, in our company, um, build brands, and my team's job is to ensure that we're nurturing the distinct identities of each of those brands, um, such that, you know, we're able to deliver to those consumer needs, um, and create consumer love, um, as well as I lead the, uh, AI task force for the company. Um, and the AI task force is really responsible for the AI strategy, uh, across our and enterprise, across brands, functions as well as regions.

Speaker B: Great. And that's what you're here to talk about a lot today, is how you're using AI. So let's, you know, let's set the stage. Um, so AI isn't new for Estee Lauder, right? I mean you've been using it for quite some time. Generative AI, it's, it's fairly new like it is for everyone. But, um, you've gained a lot of ground pretty quickly. So to start us off, what can you tell us about some of the most impactful ways, you know, some really the strongest ways that your teams are using generative AI?

Speaker A: Yeah, exactly as you said, look, we've been using AI for a long time, right? And um, um, people often ask me, you know, what is your AI generative AI strategy? And I always say, look, like we actually don't have a generative AI strategy. We have a company strategy, right? And our company strategy is about creating superior products, um, delivering high touch experiences. Uh, we are, uh, really focused on doing activities that build brands. We are about faster speed to market, delivering consumer love. And so really, uh, when it comes to AI, generative AI, what we're thinking about is how can we deliver to this strategy that we have for our company and do it in a way where it either is driving growth, which is about new consumer recruitment, consumption, as well as efficiency, which is about doing things in a way where, um, it's faster or takes less time or resources to get there. When it comes to generative AI, again, it's really AI or generative AI, it's really thinking about how we deliver, uh, to this strategy with AI and Genai being the enabler, um, and doing it in a way where the platforms, the generative AI platforms or the solutions are actually connected end to end so that we can create value, uh, we can actually, uh, capture the value that we know that we're creating through these platforms.

Speaker B: So I mentioned when I first introduced you, you had talked about the, and speaking of platforms, you had talked about the beauty trends platform. So this is a big initiative at Estee Lauder. Um, you know, tell us for those who aren't familiar with it, who didn't get to come to the Event. First off, what, you know, what is the beauty trends platform?

Speaker A: Yeah, so look, um, you know, obviously within, um, Estee Lauder companies, uh, or within our industry rather, I should say that trends are extremely, extremely important. When we think about trends, um, there's sort of actually a triumvirate. We are in the business of creating trends, anticipating trends, as well as reacting to trends. Right? So, um, it is very important for us to do the creation and anticipation and we do that through our portfolio of brands. But when it comes to reacting to trends, uh, which is really what I spoke about and I believe I shared the platform as well, um, we want to be able to understand because trends are really moving so quickly. Um, and what we want to do is be able to understand, capture what those trends are in real time. So the beauty trends platform is really, um, it's. We have AI, actually we've had AI as you mentioned, right. AI we've been using for many, many years. For the last actually seven years, eight years or so, we've been mining millions of daily conversations. And these conversations have been across review and you know, ratings platforms or social, uh, media platforms as well as like blogs, right, um, et, etc. So we've been really capturing, uh, these consumer conversations and trying to really parse out and understand what are the signals that can help us with trends and consumer needs. So right across benefits, forms, finishes, textures, subcategories, looks, but also culture. Um, and so this beauty trends platform, actually it sort of leverages our ability to capture this data which we've been doing for many years. But now with AI actually it's able to very quickly also generate, um, concepts. It's able to match our best assets, right? Our product assets or our uh, you know, even some of our, uh, creative assets, ah, claims assets. It's able to match it to those, um, trends that are happening in real time in the market. It's actually also able to then tell us if we have enough inventory sitting or not. Right? Because we want to be able to if, uh, we're going to.

Speaker B: That's really the key, right? Because like if you this, you have this amazing trend and that you want to make sure you can deliver on it.

Speaker A: Yeah, uh, uh, just, I think just earlier I was talking about end to end. This is really what it means, right? Because the trends platform isn't just about what is the trend. Obviously that's a very important thing. Right. And I would say that's a competitive advantage that we have because we're actually capturing in real time the trends. But Then be able to like focus uh, on execution and action becomes equally important. And that's really where we've sort of built a system that such that it delivers um, uh, this um, uh, it's able to deliver actions with granularity for us.

Speaker B: So it's the double edged sword. You see so many uh, beauty companies talking about. You see all of a sudden you're part of this vital trend and everyone wants your product. But if you can't serve the consumers and it can just turn into the opposite of an experience, of a good experience.

Speaker A: Absolutely. And you know what, it's interesting, um, there are so many questions to think about here because I talked about anticipation as well. Um, and what happens is that trends actually are actually come in cycles. Um, and so for example, uh, we've addressed skin cycling for the last uh, many years. Skin cycling is a trend for those of you who may not know where you use different products. Just like uh, when you work out in a gym, you work on different muscles and that's kind of, you cycle them. So similarly uh, for your skin there's sort of skin cycling that um, uh, that consumers do and it delivers results. Now that trend actually every year sort of, it evolves a little bit. Right. Tweaks a little bit. So also having the ability to understand for certain consumers it starts and then you have to anticipate where is it going to go for other consumers, when is it going to happen. And then in some cases also you know, the product solutions are probably are different. Right. Because cycling looks different for a certain segment of consumers than it does for another. So um, it's you know, really capturing value from trends is complex and we're really, that's where you know, I'm super proud what the team has done because we've thought about these different um, aspects of it. Not just what you said, which is inventory. Right. Which is all about like if you think about matching product, having inventory and then delivering against the trend, great. But then also this idea of anticipation becomes so important because then you're able to think about new product innovation. Right? You can think about, okay now how do I create a new trend which maybe addresses um, you know, skin cycling as a need that uh, for some of the other consumers who may not be participating in it. Mhm.

Speaker B: You mentioned data. Obviously data is a huge part of this strategy. So can you talk. You're collecting massive amounts of data points. Um, we all know garbage in, garbage out, right? That's certainly uh, uh, it's well known at this point. But so what is the role though? Like how are you ensuring that you're optimizing all this data that you have? How are you ensuring that you're organizing it correctly? I mean this is not a small undertaking.

Speaker A: Yeah, it's a great question. And what I would say is that um, look, we're proud to have um, uh, you know, some of the like most robust first party data um, that's really in our company. We, one of our most important assets is the data that we have and we want to ensure that we protect it and use it um, in a way that actually um, delivers more value to our consumers. It really is one of our competitive advantages. So look, that said though, everyone is on a journey to um, cleanse data, organize data. Right? Uh, it's never going to be perfect. Right? It's never going to be perfect. That's the point. I was just going to say I think it's important to not let imperfect data get in the way of value creation when it comes to Gen AI.

Speaker B: Right.

Speaker A: Let's, you know when we first started one of the first thing, um, that my boss, uh, Jane Lauder, who was a chief data officer of the company is fantastic. She was like let's start with what we have and create value where we have good data and then we can think about other aspects as well. And so what I would say is that the role of data really is around um, fine tuning what is already coming out of the box. Which is amazing. Right. So I think I said this at the um, at that conference, uh, in my talk that now for the first time for the price of maybe a cup of coffee, you know, you have some of the most sophisticated AI that is available to you, uh, and it's available to everyone, right. Like whether you're a big company or a small company. So we have to really start to use uh, the power of what um, um, this technology is giving to us. If we don't, we're going to get left behind. But just leveraging that technology gives us um, um, a start. The competitive advantage comes from leveraging our data and fine tuning this platform with our data and doing it where it's part of our strategy, our company strategy. Right. Like if we're focused on you know, fine tuning where it's not a core competitive advantage, that uh, is part of our strategy. Not worth it if we're fine tuning on data which is, you know, not in a way place where we can use it. Waste of time, right. I feel like these technologies are every six months right now we have reasoning which is the equivalent of, you know, a PhD chemist, right? That ah, with um, uh, with, with some of the models, like for example from OpenAI's O1 model. So let's use it where we have good data and generate value from it that delivers to our strategy. Really that's how we're thinking about, um, you know, how to sort of bring all this together.

Speaker B: And there has been a democratization of AI, right? I mean now as you mentioned, it is available to just about everyone. Um, but it does require some new talent needs. So when can you talk a little bit about when it comes to building new talent, cultivating AI talent, You know, what do you look for? What are some of these must have skills that, that leaders should have or emerging leaders?

Speaker A: No. Great question. Again, you know, it's interesting, I would say, um, there's almost like three musts when it comes to creating competitive advantage, right? One, um, is um, what we just talked about and not in any particular order but you know, the data and fine tuning it. Second one is really like really understanding competitive advantage and what our strategy is. Third is the people. And it is so important, right? So um, for me, competitive advantage when it comes to people comes from creating this virtuous circle cycle of um, having what we call in our company math and magic. And so what it really means is that the human potential is increased by the creativity that human brings, right? And that's the magic. And so we have to have a culture of creativity to start off with. Then we have to really have um, talent upskilling such that they're able to use this generative AI, um, solutions to really enable the math or bring the math. And so what I mean, what I mean by the math is really we want to be able to have our people focus their creativity where it matters, right? Where consumers are requiring us to, where there's growth, you know. And AI and I talked earlier about granularity, right? AI brings the granularity. So when it comes to trends, AI can surface, you know, what are the most granular trends for a certain consumer segment? You know, what are the products that we can use that are matching? Right? So this is all um, AI bringing the math. How we actually get consumers to fall in love with the communication that we have. And you uh, know that first trial and fall in love with the product and have repeat. It's really about the magic, right? And that's really where, what I really mean by focusing that creativity where it matters. I don't know Lisa, if you know this, but like we have Some of the highest repeat rates our products do in our industry and the reason why we have these high repeat rates is because, um, we create amazing products that are delivering to these consumers needs. Now AI can tell us what the consumer needs are, right, but. And AI can also tell us what ingredients are best. But it's really the creativity of our people that takes it to that next level. And so, um, you know, having this high, uh, quality product which delivers high repeat is such a strong engine for our company's growth. Um, and you know, for those who are in marketing, we always say, right, that trial costs money, repeat brings profits. And so it's really about focusing on having repeat which really, you know, creates this engine for the company for, um, you know, continuous growth.

Speaker B: I want to double click a little bit on the skills that, that you need for AI talent. So it's, you know, it's really interesting for you. It reminds me of when everyone is saying everyone needs to learn how to code, right? Like there was, there's definitely saying everyone needs to learn prompt engineering, right? And it feels like that's kind of the new trend. When you were at the summit, you were saying that it's, it's not really quite like that, that prompt engineering isn't quite as complicated as it sound or maybe quite as required. So, you know what, can you talk a little bit about that and what you mean, what you meant by that?

Speaker A: Yeah, look, obviously I was being a bit provocative around prompt engineering because when I first about, when I first heard about prompt engineering, it scared me a little bit, right? Like, you know, what am I engineering? You know, why am I engineering? You know, even though I'm a chemical engineer by training, I still don't want to engineer. You know, like that just sounds too complicated. So, um, look, when it for me, right, like what I've learned and maybe before I answer this question, what I will say to you is that, you know, no one should be outsourcing how to use generative AI to consultants or you know, team members or you know, quote unquote, other. Right.

Speaker B: Um, you think it should all be done in house?

Speaker A: No, not even in house. So even we should be all learning it ourselves.

Speaker B: Gotcha.

Speaker A: You know, beyond just in house, right? So absolutely. We don't want to have some consultant come and tell us, like how to use generative AI. I'm actually saying, you know, I want everybody to actually use it for themselves, right. And learn it and not just at work. Like, you know, I use it with my daughter for her homework. You know, I think Lisa, maybe you and I spoke about this because I want to teach my kids, my teammates, you know, my leaders, that the world is no longer going to be about people who know answers, right? Because we've been really think about it, right? Like when it comes to schools or universities or hiring or promoting, traditionally it's been done based on, uh, you know, we judge people or we like, we measure people based on what they know. And actually it's going to completely flip. And that's really what I mean about prompt engineering. And I'll come back is that it's at the end of the day, it's about the art of asking questions, you know, and our CEO Fabrizio says that it's about art of inquiry, right? Which is another way, right? It's art of asking questions. So when it comes to generative AI, my learning has been because I don't want to outsource it, I want to use it myself and I want to experiment with it. I want my kids to experiment with it, I want my team to experiment with it. And then together we, you know, we share our learnings. And, and what I realized is that, you know, first when I heard about prompt Engineering, I thought we needed some engineers, tech, digital engineers, to like sit with business people.

Speaker B: It feels very technical, very technical that what you're being asked to do. But it's really more about having curiosity, right? It's about kind of building this deep seated curiosity to want to start asking questions.

Speaker A: Exactly. And what I learned is the best, quote, unquote, prompt engineers are actually the best teachers, right? And if you're able to teach an intern who comes into the company or teach a new employee who comes in the company, and if you can break down what we do or what you're trying to teach them in sort of simple steps, right? And you, that's how you should be basically speaking to your, um, the machine, right? The AI, the generative AI. And so what I see is that the prompt engineering is really about, you know, asking questions in a simple way where you're teaching this, uh, this machine how to respond and what to say. It has the knowledge of everything, right? It has the world's knowledge, it has your company's knowledge. But if you are, if you're not going to know what to ask and how to ask it, it's not going to give you. So it's a little bit, you know, earlier you said garbage in, garbage out. When it comes to data, it's also garbage in, garbage out when it comes to asking questions, right?

Speaker B: Ask Stupid questions, get stupid answers.

Speaker A: Right. Or ask broad questions and get broad answers. People, you know, it's interesting. People talk a lot about hallucinations. Well, you're probably not asking the right question if the machine is hallucinating. So maybe think about, maybe blame yourself rather than blaming the machine.

Speaker B: Anyway, uh, when you, when you look to the future, I mean we talked a little bit about, you know, you mentioned you having your, your daughter use AI. When you kind of look to the future of the potential of AI, I mean, what, what do you think is going to be really exciting? Whether that's, you know, in a couple years or maybe even further, further out.

Speaker A: Yeah, look, and you know what?

Speaker B: Sorry, just this best. Maybe we'll just keep this, you know, within consumer goods and retail. Right? Because I mean, I'm sure there's amazing potential and across many fields, but within, for our audience, within consumer goods, for our audience.

Speaker A: I'm glad you asked that because I was going to go in a really broad.

Speaker B: There's a lot of different ways you could go life changing. So maybe we'll keep it, we'll go a little.

Speaker A: Yeah, I've thought about this. Right. Obviously. And look, in a way, the way I think about this is we got to get the right compass, but we don't have to have the right exact strategy and the right path because it's going to evolve. Right. Um, even when it comes to um, our projects that are a year out, we know that the technology is going to double in its quality every six months. Right. And so, um, you know, really thinking about where we're going to go go it sort of we need to have the compass. Right. But the specifics, obviously we need to. That's why we shouldn't be outsourcing it because we should completely be learning it ourselves and iterating as we go along. But let me give you my broad strokes thoughts on like where this thing is going to go. Uh, I think value is created in the world not by generating content, um, which is what Genai does today. Not even by generating content which is connected, which is I think the next level of where, uh, we're getting there. We're not there yet as an industry, but we're going to get there. This connected end to end, which is what the trend example was about. I think that it's actually, you know, when, when you can get consumers to really connect to what they need. Right. From a product standpoint or, you know, that's really when it starts to get interesting. And it gets even more interesting when you can really enable connections that allow people to connect with each other. Right. So connect with community. When it comes to beauty, right, Beauty is about really, it's about self, uh, expression, right? It's about um, emotional and physical well being, it's about discovery. But at the end of the day, self expression is really about connecting to culture, right? You express yourself through beauty, through makeup for example, because you want to connect with a community. Um, and so that's what the human desire is, that's what human wants. So generative AI today is about generating content. Just like Internet Maybe in the 90s was about, you know, uh, giving information. But then when the Internet was able to connect people with products, right. Amazon was created, right? And really it took uh, the Internet sort of to the next level. And then obviously when uh, the Internet was web two, right. Like when Internet was able to connect people to each other, social media platform companies created, right. So, so if we think about that really, I think that's where um, you know, this technology goes as well. And I, I think for us as a company it is extremely exciting, Lisa, because I still order companies, right? Like we are about, uh, we're a culture company, right? And uh, we're here to like I was saying earlier, to deliver to these consumers, um, that we have this like ability to connect, you know, belong with communities, express themselves, um, you know, be, you know, sort of have well being. And so I think that this is where this technology goes. Broad strokes from a compass standpoint.

Speaker B: It's going to fundamentally change the conversation on how we can connect with consumers and how we can connect with each other digitally. Um, ah, last question. Looking ahead. Let's keep looking ahead a little bit. Uh, but within Estee Lauder, can you talk a little bit about what's next with AI? Anything coming down the pipeline that you can share?

Speaker A: Yeah, look, what's next? I mean obviously, um, we have a lot of exciting things uh, that are going to come next. And my m. Focus is on capturing value when it comes to generative AI and AI and capturing value at scale. So really that's what we're focused on, um, capturing value at scale in a way which is as I said earlier, end to end. Right. So we have extremely exciting solutions uh, that we're creating right now that are going to address, for example how we do R and D so that we can create products that are faster, ah, and that are um, delivering to those consumers needs, uh, like how we do faster testing of products, how do we get claims that are more relevant, etc. Um, so certainly. Right. Like that's an area that we're focusing on. Then we go down sort of the funnel. Um, you know, how do we think about marketing? Right. How do we create concepts? Um, you know, then we go further down and we think about execution. And this is really what I'm excited about because we have this strategy, um, of precision marketing. Right. And precision marketing really is where AI enables us to deliver, um, to the specific, uh, customer, consumer, what they want, where they want, when they want and how they want. So we're going to go, um, right. Like really, uh, have essentially the right product, the right communication, right in the right channel. Um, and AI is going to enable that education. Right. We're spending a lot of time there as well because we have this amazing um, uh, you know, uh, force of our makeup, uh, advisors and beauty advisors who are, you know, absolutely amazing and there who give our consumers this high touch experience. We want to enable them and give them the tools they need to be able to do that better. So really it's about going end to end across our strategy, um, that we have and having AI which is going to connect end to end such that we're able to really at the end of the day create um, consumer love that then converts to long term profitable growth for our company.

Speaker B: Definitely some exciting days ahead. So Raheel, I want to thank you so much for coming on Tech Transformation and giving us a preview into what's going on at Estee Lauder and a peek into the future.

Speaker A: Thank you so much, Lisa. It's always a pleasure and fun to speak to you and uh, hopefully we can do some next uh, time as well in the future.

Speaker B: Always great to have you. Always great to chat. Thanks for healing. Thanks for listening to Tech Transformation with cgt. Be sure to subscribe to learn more strategies and trends in the retail and consumer goods industries. And don't Forget to visit ConsumerGoods.com to sign up for our newsletters.