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How Estée Lauder Is Cultivating a New Culture of Measurement With AI

Kristen Hunt
raheel
Raheel Khan, SVP, Foresight and Growth Intelligence, The Estée Lauder Companies

Consumer goods companies are having to reassess the interplay between people, processes, and technologies, particularly amid a surge of AI implementations. 

As the keynoter for the Consumer Goods Sales & Marketing Summit 2024, Raheel Khan, SVP of foresight and growth intelligence at The Estée Lauder Companies, shared how the multi-billion-dollar corporation leverages AI to drive teams toward growth and innovation, blending "math and magic" to establish a new culture of measurement. 

Generative nerative AI continues to dominate tech and business conversations, and Khan and his team at Estée Lauder are creatively harnessing data to enhance decision-making processes within data science and consumer insights. By aligning AI with strategic objectives and studying its practical applications, Khan believes that generative AI is essential for achieving long-term profitable growth and maintaining a competitive advantage.

“If you have a culture of creativity where people understand [AI], know how to use it, and then know that there’s a process for people to come together and build on top, that’s where the competitive advantage comes from,” Raheel said. 

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AI in Action

AI is helping to deliver new levels of personalization and agility, making companies smarter and more effective in tailoring their offerings to consumers. Current use cases for AI at Estée Lauder include agenda preparation, image editing and creation, product imagining, and identifying unmet consumer needs.  Khan encourages teams to leverage these tools to reduce time spent on tedious tasks, freeing up opportunities for creative problem-solving. 

In April, the company partnered with Microsoft to establish an AI Innovation Lab to drive GenAI-powered innovation in the prestige beauty sector, optimizing product development and consumer engagement. In addition to working with established players like Microsoft, Google, and Adobe, they're also partnering with such startups as Open AI and Quilt.ai and with universities like NYU and the University of Pennsylvania to explore the future of marketing, focusing on strategy and brand positioning. 

Also read: Estée Lauder is using AI to spot trends for marketing activations

These collaborations aim to enhance strategies through advanced data analytics, machine learning, and AI-driven insights to optimize operations and deliver personalized consumer experiences.

Estee Lauder

Getting the Equation Right

Khan emphasizes the importance of blending analytics and creativity, referring to this combination as “math and magic.” The "math" involves using generative AI for analytical tasks to enhance time efficiency. He notes that accessible AI solutions can significantly boost productivity without requiring extensive IT infrastructure.

Alternatively, the "magic" component focuses on cultivating a creative culture. Khan argues that neither generative AI nor human intelligence is sufficient on its own; their synergy is what drives success. When it comes to maintaining consumer relationships, Khan emphasizes the importance of AI while also recognizing the growing trend toward authentic human interactions. To address this, Estée Lauder is prioritizing innovative trends through precise measurement. 

Read more: Estée Lauder undergoing IBP improvements 

The company focuses on specific consumer preferences by integrating AI tools with human intelligence to create end-to-end value. By measuring these trends through key performance indicators, they can effectively scale their initiatives. This balanced approach enhances speed to market while nurturing meaningful relationships with customers around the world.  

Khan shared one of his key learnings from Estée Lauder's journey: there is no one-size-fits-all AI solution; the emphasis should be on tailored approaches. A culture of thoughtful inquiry is critical for effective AI implementation, as the quality of questions determines the value of responses.

“It's no longer about who knows the answer; it’s actually going to be about who knows the question to ask,” said Khan. “Generative AI is going to have all the knowledge, but knowledge won’t just come out. You have to know the art of asking questions.” 

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