Estée Lauder uses AI to transform personalization in beauty

Key Concepts:

• AI in beauty and retail
• Consumer insights and predictive analytics
• Personalization at scale
• Trend identification and analysis
• AI agents (Consumer IQ)
• Legacy company transformation
• Empathy and AI
• Skill sets for an AI-driven world
• AI as a collaborator

1. Kalindi Mehta's Role at Estée Lauder Companies (ELC)

• Kalindi Mehta is the Global Vice President for Consumer Foresight, Strategy, and Predictive Analytics at ELC.
• Her role involves reacting to current trends with speed and anticipating future consumer needs.
• She focuses on building future-forward capabilities that integrate consumer understanding, data science, and predictive analytics, grounded in business strategy and brand knowledge.
• Her goal is to empower the business to make consumer-centered decisions and uncover growth opportunities in both the short and long term, at scale and with speed.

2. The Competitive Beauty Industry

• The beauty industry is highly competitive, with 20,000 brands worldwide and 2,800 actively marketing in the US alone.
• A beauty product is sold every two seconds on leading social commerce platforms.
• Consumers are highly engaged, discussing needs, searching across multiple platforms, and interacting in physical stores.

3. Speed and Agility in Trend Adoption

• Beauty microtrends can spread rapidly (days to weeks or even hours) via social media, influencers, user-generated content, and viral content.
• Increased global connectivity means trends can spread from one region to others in months instead of years.
• Example: The "Asoka" makeup trend started in Indonesia in March 2024 and spread to India, Brazil, Mexico, and the US by April 2024.

4. Opportunities for AI in Beauty and Retail

• ELC is integrating AI across the business.
• Virtual try-on technology allows consumers to see how makeup or skincare products would look on them.
• AI enables personalized recommendations and customized solutions based on individual needs (lifestyle, skin type, weather, time of day).

5. Personalization and Data Analysis

• AI is used to analyze vast amounts of consumer data to understand individual needs.
• Consumer data is combined with product data to develop products that meet specific needs.
• Example: Identifying trending ingredients for a specific season and profile, matching them to existing products, and creating targeted campaigns, resulting in a 10-15% sales increase for a brand.

6. Empathy at Scale with AI

• ELC built an end-to-end trend studio to sense trends across markets and match products to those trends.
• The system can recommend the right product for a trend or the right trend for a product.
• It helps create content, concepts, briefs, and messaging quickly, reducing the time to market from weeks to hours.

7. Consumer IQ: An AI Agent Initiative

• Consumer IQ is an AI agent that leverages ELC's vast database of consumer, market, and social listening insights.
• It synthesizes insights across multiple sources in real-time, providing strategic insights at the point of decision-making.
• This improves the speed and quality of decisions.

8. Advice for Legacy Companies

• Legacy companies are rich in proprietary insights (market research, social listening, consumer data).
• AI can be used to leverage these insights into actionable results.
• Embrace AI as a copilot, but take a measured approach, focusing on low-risk, high-value use cases.
• Ensure responsible and ethical AI implementation.
• Start with the problem, not the solution.

9. AI and Empathy

• AI enables a deeper understanding of consumer needs with precision and depth.
• There is always a human in the loop, using AI-driven insights to enhance empathy and drive creativity.
• AI helps translate understanding into personalized approaches, products, and marketing campaigns.

10. Influencer Engagement

• AI is used to synthesize insights about trends and products, which are then shared with influencers in a simplified way.
• This helps influencers better understand the consumers they are targeting.

11. Engineering Virality

• AI helps distinguish meaningful trends from noise.
• Deeper understanding of society, culture, and beauty is crucial for identifying actionable trends.
• An always-on learning approach is necessary, where experiments are conducted, learnings are gathered, and scaling decisions are made based on early results.

12. Required Skill Sets

• Soft skills (power skills) are more important than technical skills.
• Key skills include problem-solving, creative thinking, curiosity, and adaptability.
• Constant learning is essential due to the rapid evolution of AI.
• ELC provides training and fosters an AI culture, with leadership setting the tone and integrating AI into strategy plans.

13. Legacy Organizations' Potential Superpower

• Legacy organizations have amassed vast amounts of data, which can be a significant advantage if they can leverage it effectively.
• This data can help them compete with smaller, digitally native competitors.

14. Decision-Making Process

• Aim for clarity, not certainty.
• Lay out all the facts and data clearly, with insights that highlight the pros and cons of each decision.

15. Transforming Workflows with AI

• AI helps transform entire workflows, from sensing trends to matching products, creating content, and measuring impact.
• This leads to increased efficiency, business results, and ROI.
• It also promotes seamless collaboration.

16. Kalindi Mehta's Personal Use of AI

• AI is an indispensable tool in her daily routine, both at work and personally.
• She uses it to synthesize reports, analyze consumer transcripts, craft emails, develop product concepts, and create engaging headlines.
• Example: Synthesizing 75 hours of consumer interview transcripts in one hour.

17. Future of Work with AI

• AI will be a true collaborator, handling data crunching, forecasting, and optimization.
• Humans will focus on strategy, creativity, emotional intelligence, and intuition.
• AI will free humans to be more human, creative, and impactful.

Conclusion:

The conversation with Kalindi Mehta highlights the transformative potential of AI in the beauty industry and beyond. By leveraging AI for consumer insights, personalization, trend analysis, and workflow automation, companies can gain a competitive edge, make better decisions, and ultimately, create more meaningful experiences for their customers. The key takeaway is that AI should be viewed as a collaborator that enhances human capabilities, not replaces them, and that a focus on soft skills and continuous learning is essential for success in an AI-driven world.