COSMOFACTORY

Deanna: [00:00:00] This episode is about leading edge product innovation. It's about artificial intelligence and trend analysis. It's about keeping pace with consumer expectations and about setting a pace for the future of beauty. My guest on today's episode of the Cosmo Factory Podcast is Kalindi Mehta Global Vice President of Consumer Foresight and Predictive Analytics at the Estée Lauder Companies.
Deanna: Welcome, Kalindi.
Kalindi: Hi, I'm thrilled to be here [00:01:00] today. Yeah, thanks so much for inviting me, and it's great to be a part of this exciting conversation.
Deanna: Yeah, you're welcome. I'm, I'm really glad you took time to share your work with us. Um, let's get started with a, a big picture question, if you don't mind. Why is artificial intelligence or AI so significant for the beauty industry? I.
Kalindi: Yeah, in in the beauty industry, never has the pace of change been so fast on so many fronts as it is today, and it's not gonna slow down, you know? So to help compete and keep up with this pace of change with speed and agility, it'll be important for companies in the beauty industry to embrace ai. You know, with new technology, digital commerce, social media, there's so many more new brands, new innovation, new content, new looks, new trends, all happening to the speed of light.
Kalindi: And we will need ai, and we are using AI to keep up with that speed of light. And another reason is, you know, to really leverage. The power of, you know, all the insights that are [00:02:00] available. Beauty has so many insights, so much of information, so many conversations going on, so much of data everywhere. And so, and, and this because consumers are so involved in beauty, it's one of the most talked about categories on the internet.
Kalindi: So, you know, how do we leverage all of these, all of this insight that's available, you know, because it can be overwhelming. And how do we harness the power of these insights effectively? And AI can. Is playing and will play a very important role in this.
Deanna: Yeah.
Deanna: Yeah, no, that makes good sense. You have something further there.
Kalindi: yeah, maybe one more point, right, which is, which I think is actually the most important point.
Kalindi: You know, today's beauty consumer. Once products is demanding products and experiences that are really tailored to their individual unique needs, they want something specifically for themselves and they will not engage with you unless it's hyper relevant to their specific need to that their lifestyle, to their life [00:03:00] stage.
Kalindi: And, you know, AI enables us, you know, to drive this hyper-personalization in order to meet that individual, you know, consumer need.
Deanna: Yeah. No, that's super interesting. And your reply there reminds us how fast moving, especially just now, um, the cosmetics and personal care industry is, it's. It's normal for people to say it's, it's such a fast-paced business. Um, and I think as you've suggested, it's especially true when this comes to consumer trends. Um, and you've, you've mentioned sort of the need to leverage AI in response to those trends. Can you say a little bit more about how you are actually doing that in your work? I.
Kalindi: Yeah, sure. Um, and, and so, you know, uh, as we spoke about, you know, beauty industry does demand super rapid re response to all the trends, to all the moments that are happening, uh, in culture and in people's lives. And so, and, and now think about our company, right? Estel Lauder Companies, we have nearly 25.
Kalindi: Brands, we are there in almost 150 markets.
Kalindi: [00:04:00] So how do you react now to, you know, these trends, these moments, you know, social content? How do you react to it at scale? How do you react to it consistently and with speed? Because, you know, it's easy to do it on a one-off basis for a few brands, but I think the real value for any business comes when you react at scale consistently.
Kalindi: And AI can help us. Do that and create that real value. Uh, so, uh, you know, very specifically we have built a comm, uh, a platform, super simple platform. It's like a Pinterest board. Very simple platform to sense trends using, you know, visual and cultural ai, you know, across 20 plus markets and the way it's been built.
Kalindi: Is that, you know, we, uh, what do you actually need? What does the team need to activate the trends? And we've kind of built it backwards. And so it provides exactly the information that you need to activate the trends, the hashtags, the [00:05:00] keywords, uh, so you can do it quickly and you don't have to go looking for information.
Kalindi: Second is, what it does is once you send the trend, you have all the exact language, hashtags, keywords, AI uses, um, you know, uh, leverages. We use, uh, AI to. Connect this trend to the right product in a portfolio.
Kalindi: You know, in beauty, we have so many different subcategories, formats, colors, variance, and so what's the right product against this trend?
Kalindi: So AI helps us match that. You know, uh, so that we don't spend time trying to figure out what should we use. And then not only, uh, does it match it, then it takes it to the next level. You know, as you brief creators, influencers, or your own creative team, it helps create those concepts and briefs. I. That you, uh, using the insights, using the trends, using a product knowledge so that you can quickly write to the influencer or write, give it to our [00:06:00] creative people.
Kalindi: Uh, and it can also help identify the right assets or create the assets. And then finally, once we activate the trends, it helps you quickly measure the impact in a simple way.
Deanna: Mm-hmm. I love it. It's, it's so clear that you work with data the way your, um, your mind is answering these questions. It's, it's so, um, it's
Deanna: so careful. I, I love, I love learning how people think. Um, and, and what you've shared, it sounds like it's, um, super effective for these short term trends. Like you said, something pops up, you know, we need to be on the hashtag, we need to think about the product that responds to it. But how then is AI helping maybe with product innovation beyond these short-term opportunities?
Kalindi: Yeah. Uh, so, you know, Estel companies, uh, as you may have heard, is really focused on its new strategic vision of Beauty Reimagined, right? Which is really trying to get to that sustainable double digit growth. And as a part of that, we are significantly transforming our operating model to be, you know, faster, leaner, more agile, [00:07:00] and to step change and drive even more.
Kalindi: Consumer-centric innovation. Now, when you talk about innovation, that's where data and analytics, uh, data insights analytics can give us a clear advantage over our competitors. Now, what, uh, too few, you know, appreciate is how insights rich. Legacy and big beauty companies like Estella are,
Kalindi: you know, with ai, this richness of insights and information can now turn into a distinct advantage.
Kalindi: We have over a lot of these newcomers and smaller brands, so we have an extensive, we have extensive proprietary insights and data
Kalindi: learn, millions of brand assets, thousands of product formula. Information claims, consumer and market insights of millions of consumers. Beauty trend reports that are generated real time and so much more.
Kalindi: We can use gen AI to transform all of this information, you know, marrying the past, the present, the legacy, all the new information. Uh, [00:08:00] you know, and create like treasure. And this can be our competitive advantage in this highly dynamic and trend-driven, you know, beauty landscape. And so, uh, so this, you know, this competitive advantage really comes from this virtuous cycle of math and magic where math, you know, uh, or AI helps focus creativity where it matters.
Kalindi: Uh, helping us drive that consumer-centric innovation and, you know, step change it for us.
Deanna: No, that's super cool. I love it. Um, so earlier this year I actually had the opportunity to hear you speak about AI in beauty, and one of the slides you showed in your presentation reminded me of something that we all know is happening. And you've even suggested it earlier in your conversation, mentioning how many markets you serve, how many brands you have, right?
Deanna: But all multinationals and international companies even. You know, have a foresights team like yours and, and many might have AI process, um, tools at work, but they're looking at fully global sources, [00:09:00] right? Data that comes in an array of languages, and I'm guessing, I. Each market, um, you know, maybe even each neighborhood in some instances has its own cultural nuance.
Deanna: Right? And this, this would certainly complicate, you know, my work trying to analyze any sort of trend, let alone, um, at the scale that a company, you know, like the Estee Lauder companies is managing it. Can you talk about that aspect of the technology that you're working with?
Kalindi: Yeah, so I think firstly we have to make sure we cover. More than just the us, you know? So we cover all markets around the world
Kalindi: in trying to understand what's going on in each of those markets. And we have AI that, uh, I mean, I'm sure a lot of people do, but that helps us translate languages, right? Uh, we have AI that helps us translate languages.
Kalindi: We have ai, which is visual and, uh, semiotics, and it captures. The visuals, the semiotics, the cultural, um, uh, nuances and translates that [00:10:00] into, uh, insights. And so it's not just reading the text and translating the language, it's actually interpreting the whole context and the. Uh, uh, and the visual and the video.
Kalindi: So it's able to, and, and, and able to translate it into very tangible, you know, insight. And so you do this across multiple markets. You use this visual and cultural AI model, uh, to help, uh, translate the cultural context into, uh, you know, into some meaning. Uh, so I think that's, that's really, uh, uh, uh, helping us.
Kalindi: Able to get insights from all over the world, from, uh, different markets, but also from local communities, from niche online subcultures, uh, which are influencing beauty. Uh, so that's, that's important, right, from an AI perspective. But secondly, we, we have AI that allows us to also talk to real consumers sitting here in the us.
Kalindi: Easily,
Kalindi: you know, so, uh, so, uh, it's super [00:11:00] quickly and there's AI helps us. Uh, you can, uh, you can, uh, moderate the interviews, you know, in the local language and what the consumers are saying. It can get translated back into English and then it can synthesize the insights, uh, and share it back with us in English, capturing all the nuances.
Kalindi: Uh, you know, that the consumer spoke about. So, so it's both using ai, you know, to evaluate the social landscape and communities and subcultures and cultures, uh, on, on the internet, but at the same time talking to real consumers around the world. Super easy with AI helping us moderate in different local languages.
Deanna: Yeah. No, that's fantastic. I, I love hearing about this and you know, the, even the way I phrased my question, I think suggested that. Every market. You know, I think I said every neighborhood, you know, might turn up to be different, but I would imagine too with technology, you know, able to sort of see and hear and listen and analyze at this level, you might find communities that are more similar than different [00:12:00] in various places around the world that, that we might not have thought about.
Deanna: So
Kalindi: Yes, so true. Yep.
Deanna: Yeah, that's so interesting to think about. Now, I don't think anyone will be surprised, uh, to hear me describe the Estee Lauder companies as a leader in all sorts of technologies. Um, leading edge ingredient science certainly comes to mind for me. Um, but clearly here we're thinking about, um, I.
Deanna: Your leadership or your company's leadership in artificial intelligence. I'm wondering if you can say more practically sort of how are you doing it? Is this all in-house or have you partnered with external tech or maybe computer science companies here?
Kalindi: All of the above. Uh,
Deanna: Okay.
Kalindi: there's no one approach.
Kalindi: Uh, we have incredible co-innovation partnerships, uh, you know, to help us, you know. Create and unlock these new capabilities and support AI scalability, right? So we work with different technology experts who've, who've developed tremendous, you know, capabilities and LLMs.
Kalindi: [00:13:00] Uh, and so we, we leverage them. We partner with them like Microsoft or Adobe or Google. Uh, but at the same time. We are also, uh, working with AI startups, of course, open ai, uh, but also other startups. We work with a company called Quilt AI that does this visual cultural AI modeling. And so, uh, they help us with, uh, you know, say quilt helps us with end-to-end trend enablement.
Kalindi: Uh, and Microsoft helps us with productivity assistance. Adobe helps us with creatives. Google's helping us with personalization and go to market. Uh, and at the same time we are working with universities. Like NYU to help us, you know, reinvent some of our processes or, you know, or upen, you know, that's helping us, uh, upscale talent.
Kalindi: And so really is leveraging all our partners, working with them as true partners and co-creating the capabilities, the processes, uh, to kind of enable AI across the organization.
Deanna: Oh, that's spectacular. I love hearing about that. So certainly [00:14:00] some of our Cosmo factory listeners are themselves, beauty brand leaders at companies, perhaps both large and, and others small. Um, I imagine they might want to learn from the benefit of your experience if, if a company is just now starting on their AI journey, do you have some recommendations?
Kalindi: Yeah. Um, I would say don't just do it for the sake of doing ai. Don't do it. It's not about fomo. Take a measured approach. Gen AI requires thought through strategy, you know, uh, and not just, oh, this person is doing this, so let's do it. I would say three fundamental principles, uh, as you build, uh, your AI strategy, right?
Kalindi: Focus on use cases that deliver the most value to you and don't risk brand trust. Which are the ones that are likely to give you the most value without brand risking any brand test. And then as you take in any tool, any capability, make sure you're blending human intelligence with [00:15:00] ai. I mean, in the end it's about augmented intelligence.
Kalindi: You know, AI is, that is augmented intelligence. And so, uh, as you. Think about ai, uh, think about it from a very human perspective. Uh, how does it, how can all, all your team really use it? How can you integrate it into the human workflows? Uh, and that's when you can really maximize the potential of ai. Uh, thirdly, watch very closely regulations and the ethical use to maintain brand integrity and consumer trust.
Kalindi: Uh. This has been very key to, you know, our progress. We have the legal team with us hand to hand as we, uh, design what to use, what not to use, how to use it, et cetera. Um, I. Another point is, you know, articulate a business case, a business problem. You know, as I said, don't just do it for the sake of doing it.
Kalindi: It's not a solution looking for a problem, but gen AI should be problem first. What is, what are some of the biggest problems in your company that you're trying to solve, right? And [00:16:00] then find the right tools for those programs. Uh, and, and, you know, obviously there's so many things that you can do. Uh, so, so that's great.
Kalindi: But, uh, as you get started. Don't just think of one specific initiative. First. Start by thinking about the future. Think. Think about a vision. Think about what it could be. Think big, think really big of what AI could do to your company, to the, to how you can have the consumers, the employees, to your business.
Kalindi: You know? So think big and create that vision. But start small. Don't worry about doing too many things at once. Take a handful of simple things that are high value, low risk, and then start them and, you know, only then do progress to more complex ones. Uh, and so, uh, yeah, really start small, but think big.
Kalindi: Start with specific use cases, but think not just about tomorrow, but think about the future and how big it [00:17:00] could be.
Deanna: Mm.
Kalindi: Yeah.
Deanna: I love
Deanna: that. Super, super exciting. Something else.
Kalindi: Yeah. And, you know, just, just something which, uh, is I'm very passionate about
Kalindi: is just learning every day, you know, for whether you are a new, a new professional, or you're an experienced professional.
Kalindi: Learn every day. I. Or it's game over. Things are changing so fast. So, so it's for us personally, but for the company as well, to have that learning mindset, uh, and continue updating yourself on what's there, what's not there, how are things evolving? So.
Deanna: Yeah. No, that's fantastic advice. And, and what about, um, for folks getting started in AI or maybe already. Working with it a little bit, are there maybe bottlenecks that they can expect to come across? Are there, um, you know, challenges that you might be able to help them prevent?
Kalindi: I mean, I think, uh, cultural resistance, right? Expect it. Expect not everybody. There'll be some people who will wanna embrace it, but not everybody. And [00:18:00] so I think if you have to really drive this at scale, understand the barriers. Empathize with them and, uh, you know, I don't dismiss it, understand the whys, and, uh, work around that and, you know, uh, address it, you know, upfront plan for it, you know, because it will be there, there will be some culture resistance.
Kalindi: Second is, you know, I, as I spoke about, just. Privacy and data, data privacy and, and the legal aspect of it and the ethical use of it. And so just make sure you're partnering hand in hand with legal right from the beginning and not later on in your process, uh, so that you really understand what we should and what we should not be doing.
Kalindi: Uh, another thing is just understanding what AI can and cannot do. And so create, creating that community of learning and experimentation, uh, is gonna be critical because a lot of people are [00:19:00] assuming a lot of things. And so how do we create the formal or informal community of learning and experimentation that allows us to learn from each other?
Kalindi: I think, uh, uh, because that learning, it is not, it's not easy for people to just embrace new tools on their own. So connecting that and building a community around it. It helps people feel that you're along, you know you're there with others on the same learning journey, and then they're more open to, uh, that behavior change and that habit change.
Kalindi: I.
Deanna: Yeah. Yeah. Excellent. Um, you know, we've talked a lot about, you know, your work and specialty and trends in product innovation, uh, you know, supporting the product innovation team with your work. But, um, I'm wondering if there are other use cases where you see AI being a real benefit to, to beauty brands?
Kalindi: You, you know, uh, it's like in everything, like
Kalindi: it's, uh, you know, there's, uh, who said that AI is a new electricity? I think Kevin Kelly said it. Who's, uh, you know, [00:20:00] uh, an editor at the Wired magazine.
Kalindi: And so he said AI is a new electricity and there is more so for beauty. Then I think for many other indu, CPG industries, uh, so just as electricity transformed all industries, uh, AI set to electrify beauty.
Kalindi: So, you know, right from meeting needs of consumers, right? It helps you, uh, better meet. The right needs of consumers, which we spoke about from a personalization perspective.
Kalindi: It enables you to offer those personalized products and recommendations, uh, to your consumers, to your customers. And you know, the level of customization just increases with ai.
Kalindi: Uh, so whether it's building products for very specific needs or consumer experiences or content. So really that personalization, helping consumers find that right product give. For themselves and for their lifestyle. Right. Another thing is ease of application. You know, makeup, just an example, right? Again, this is all meeting consumer needs, so it's not easy to apply [00:21:00] makeup, and it's even harder for certain, you know, visually impaired users, for example, right?
Kalindi: So Estee Lauder has developed this voice enabled makeup assistant. It's, uh, it's an app that helps visually impaired users more accurately and easily apply makeup, you know, and, uh, it's really a significant step, step towards inclusive beauty.
Kalindi: Uh, but really, and it could help everyone at the end, it's, I find it difficult to accurately apply my makeup.
Kalindi: So, uh, so that's another use case. And the third, which you see is virtual try-on technology, right? It's so hard to find. The right color for you when you're buying and shopping online to find the right makeup for you. And so, uh, they are these apps and there's websites like our, the Mac website, for example.
Kalindi: You can try on that color quickly before you decide if you want it or not. And that makes it so easy. To make the decision and to find something that you like and, you know, uh, [00:22:00] and this, this virtual try-on is gonna become even bigger and, you know, uh, be more, you know, become just absolutely a must when you're shopping for makeup for it there. And then I think there are like so many use cases I could
Deanna: Yeah. Yeah.
Kalindi: and. So it's, it's like it's endless, you know, whether, so this is meeting your consumer's needs, but it could also be helping our own employees. For example, we have beauty advisors in some of the stores helping people select what's right for them.
Kalindi: So it can really help the beauty advisors to make the right recommendations for the right consumer. Uh, for the unique need. It, it allows them to get all the latest up-to-date detailed information about products and ingredients and benefits and usage instruction so that they can do their job better in serving the end consumer.
Kalindi: I.
Deanna: Yeah. Yeah. No, that makes really good sense. And um, I, I guess my last question for you is an extension of that one, but is there anything particularly exciting or maybe unexpected about AI that. You've seen in your work or you're just, um, you know, able to [00:23:00] imagine coming online that that might change things all over again.
Deanna: Is there another phase to, um, our new electricity?
Kalindi: Uh. I would say one, right? So one something very, uh, which I'm very passionate about is, so I, I had the consumer insights team here, and I, and when you think about consumer insights and, uh, market research, you know, AI is just transforming it. So if I wanna, uh, uh, I can of course talk to real consumers faster and easier like I spoke
Kalindi: about, but you can also.
Kalindi: You know, uh, work with synthetic data and, you know, quickly get, uh, feedback on, uh, on an advertising or content that you've developed using ai. You can get con I, uh, feedback on, uh, concepts and ideas quickly in like 10 seconds. Uh, you can talk to, you know, personas and digital twins of your consumer quickly to get, you know, to help you fine tune your ideas.
Kalindi: Uh, you know, so. [00:24:00] Uh, it's, you can truly be consumer centric in everything you do by leveraging ai, uh, and, and, uh, that just helps you drive that incremental growth that you're really looking for. So it really is gonna transform market research and consumer insights, and I'm so excited about that. And it helps us, you know, it, if it can do all of these things quickly, we can really focus on deeper human ethnographic, uh, cultural inciting, uh, and take.
Kalindi: You know, uh, our insights to the next level. Uh, and that is of course, across all industries and not unique to beauty.
Kalindi: Um, but if you think about beauty, right? Uh, and, and I know I spoke about this, but you know, AI is, uh, uh, unlocking, you know, revolutionary changes, particularly in personalized beauty experiences.
Kalindi: You know, we are seeing AI not only predict. Create new beauty standards by understanding individual preferences and even unique biological aspects of each consumer. It's truly about delivering on that promise [00:25:00] that beauty lies in the eyes of the beholder. So if you look ahead, I expect ai, I. To continuously surprise us crafting these beauty solutions that are so unique to each person's needs for that moment of the day, for that time of the month, of the year, you know, for that lifestyle and possibly even, you know, for a person's DNA,
Kalindi: you know, so as we often say, you know, AI can create possibilities that were once unimaginable.
Deanna: Yeah. No, absolutely. Absolutely. And Kalindi, I have to say, the passion you have for your work comes through so clearly. Um, and I, I really enjoyed hearing you say, um, how important it is to learn every day and to continue to learn from each other. I, I can promise you, we have learned so much from you today, and I thank you very much for joining me on the Cosmo Factory Podcast.
Kalindi: Yeah. Thank you so much. I really enjoyed the conversation and I do believe that this is the time for the beauty industry to reimagine the boundaries of what's possible.
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