How L’Oréal Stays Ahead With AI, Lessons for Support Teams

L’Oréal has mastered the art of using AI to revolutionize customer support and product innovation. Their secret? Agentic AI. This advanced technology helps predict beauty trends, automate customer support, and deliver personalized experiences at scale. For example, their AI assistant, Lore, handles millions of tailored customer interactions via WhatsApp and Instagram, boosting conversion rates by 430% for brands like Lancôme and Kiehl's.

Key takeaways for support teams:

• Automate repetitive tasks with AI to save time.
• Personalize customer support to build loyalty.
• Use AI analytics to identify trends and improve services.
• Leverage data insights to make smarter decisions.

L’Oréal shows how AI can transform both customer satisfaction and business efficiency.

How to Automate Customer Service with AI: A Success Story with TeamSystem

What Is Agentic AI and Why Do Support Teams Need It

Agentic AI refers to advanced AI systems that can operate independently, make decisions, and adjust their behavior based on real-time data and user interactions. Unlike traditional bots that stick to predefined scripts, agentic AI evolves with every interaction, delivering responses tailored to the specific context.

In essence, agentic AI behaves more like a knowledgeable service associate, adapting to the nuances of each customer conversation.

How Agentic AI Works in Customer Support

Agentic AI leverages natural language processing and machine learning to interpret customer queries and past interactions. It continuously learns, enabling it to provide precise, personalized responses.

When a customer reaches out, the AI analyzes the query in real time, considering the context. It pulls from its training data - which might include your company’s FAQs, previous support tickets, and product details - to craft a response tailored to the customer’s needs.

What sets agentic AI apart is its ability to adapt. It doesn’t just answer simple questions - it can interpret complex scenarios. For instance, if a customer asks, "What’s the best skincare routine for someone with sensitive skin who travels a lot?" the AI can deliver a detailed, customized response that accounts for multiple factors.

Why Support Teams Benefit from Agentic AI

Agentic AI’s capabilities translate into practical advantages for customer support teams, improving efficiency and service quality.

One of its standout features is the ability to automate up to 90% of customer inquiries. This allows human agents to focus on more nuanced or emotionally sensitive issues, where empathy and creative problem-solving are essential.

Another major advantage is cost savings. By handling routine queries, agentic AI helps reduce operational expenses while maintaining high-quality service. Support teams can do more with fewer resources, all while keeping customers happy.

The 24/7 availability of agentic AI is a game-changer, especially for global businesses. Customers can receive instant responses anytime, regardless of time zones or business hours, ensuring a seamless experience.

Additionally, agentic AI generates valuable data insights. By analyzing large volumes of customer interactions, it identifies recurring issues, tracks emerging trends, and provides actionable insights that help teams refine their approach and improve service.

Finally, agentic AI ensures consistent responses. While human agents might provide different answers to the same question, an AI system delivers accurate and reliable information every time, all while considering the unique context of each customer.

A great example of this in action is L'Oréal's AI assistant, which showcases how agentic AI can improve efficiency, reduce costs, and enhance customer satisfaction - all at once.

L'Oréal's AI Strategy: 4 Ways They Stay Ahead

L'Oréal uses four key AI strategies to maintain its competitive edge in understanding customer needs, delivering tailored support, and innovating its product offerings. These strategies not only drive product development but also strengthen the company's focus on personalized customer experiences.

Predicting Consumer Trends With AI

L'Oréal's TrendSpotter program is a cutting-edge tool designed to predict beauty trends before they become mainstream. Launched in 2023, this system scans over 3,500 online sources - including social media, influencer content, and market signals - to identify trends 6 to 18 months ahead of time.

By analyzing millions of data points, TrendSpotter gives L'Oréal a significant advantage in product development. The company also integrates Ipsos Synthesio, a social listening and trend analysis platform, to transform this unstructured data into practical insights. These insights shape everything from product formulations to marketing strategies, ensuring L'Oréal stays ahead in a fast-changing market.

Personalizing Customer Support With AI

L'Oréal has also revolutionized customer support by using AI to create more personalized interactions. One standout example is Lore, the AI assistant launched in 2022 by L'Oréal Chile. Operating on WhatsApp and Instagram, Lore is powered by NTT DATA's conversational AI platform and Azure OpenAI.

Unlike traditional chatbots, Lore can handle complex, context-specific questions. For instance, customers can ask for makeup recommendations for a job interview or skincare advice tailored to their needs. Lore provides detailed, customized answers and even facilitates instant purchases. Since its debut, Lore has managed millions of conversations, offering 24/7 support and creating a seamless channel for beauty advice.

Enhancing Shopping Experiences With AI

L'Oréal has also used AI to improve both in-store and online shopping. The SkinGenius tool, for example, provides a quick, five-second skin analysis and recommends personalized skincare routines and products. In 2021, L'Oréal Nordics used Google's Performance Max to drive traffic to SkinGenius, achieving a 50% year-on-year increase in tool usage - the highest globally for the brand.

L'Oréal also employs Modiface technology for virtual makeup try-ons, helping customers visualize products before buying. Additionally, the HAPTA device - a handheld computerized makeup applicator designed for individuals with limited mobility - demonstrates the company’s commitment to inclusivity and personalization.

Empowering Teams With AI-Driven Insights

L'Oréal's AI strategy extends beyond customer-facing tools to its internal operations. The "One Intelligence" platform provides over 40,000 employees with real-time access to market and consumer insights. This platform breaks down silos within the organization, enabling teams to make informed decisions quickly.

Complementing this is Revuze, a tool that delivers up-to-date insights on customer preferences, competitor actions, and market trends. Together, these tools allow L'Oréal teams to validate ideas and adjust strategies based on real-time data, ensuring agility and alignment across the company.

Strategic Area	AI Tool/Program	Outcome/Metric	Timeline
Trend Prediction	TrendSpotter + Ipsos Synthesio	3,500+ sources analyzed, 6–18 month trend lead	2023
Customer Support	Lore (WhatsApp/Instagram)	Millions of conversations, 24/7 availability	2022
Shopping Experience	SkinGenius, Modiface, HAPTA	50% YoY increase in tool completion rate	2021–2022
Team Insights	One Intelligence + Revuze	40,000+ employees with real-time data access	Ongoing

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Case Study: L'Oréal's AI Assistant Lore

L'Oréal continues to push boundaries in customer engagement with its AI-powered assistant, Lore. What began as a basic chatbot in 2023 for L'Oréal Chile has transformed into a highly sophisticated AI assistant, reshaping how the brand interacts with its beauty customers.

By integrating generative AI and Azure OpenAI technologies, Lore has become a game-changer in delivering personalized, efficient customer experiences.

What Lore Can Do

Powered by NTT DATA's conversational AI platform and Azure OpenAI, Lore operates seamlessly on WhatsApp and Instagram, connecting with customers on platforms they already use daily. Unlike traditional chatbots with rigid, pre-programmed responses, Lore manages nuanced conversations, understands context, and even remembers past interactions.

Here’s what makes Lore stand out:

• Tailored Product Recommendations: Lore asks insightful questions to provide advice that’s specific to each customer’s unique needs.
• Instant Purchases: Customers can complete their purchases directly within the chat, making the shopping process quick and effortless.
• Continuous Improvement: Lore learns from every interaction, refining its recommendations over time to deliver even better experiences.

This advanced functionality allows Lore to offer a more human-like and engaging interaction, setting it apart from standard customer service tools.

Results L'Oréal Achieved With Lore

Lore’s introduction has led to impressive outcomes for L'Oréal Chile, particularly in customer service and sales performance:

• Faster Response Times: Lore has significantly reduced customer wait times, mirroring the speed gains seen in similar AI projects across L'Oréal.
• Boost in Conversions: With the ability to handle millions of personalized conversations, Lore has driven a staggering 430% increase in conversion rates.
• Enhanced Customer Satisfaction: Customers frequently praise Lore’s tailored advice, which fosters trust and strengthens loyalty.
• Valuable Insights: Each interaction generates data on customer preferences and emerging trends, feeding into L'Oréal’s broader business strategies.

Lore not only enhances customer experiences but also provides L'Oréal with critical insights to refine its approach to beauty retail. By combining convenience, personalization, and actionable intelligence, Lore exemplifies how AI can elevate both customer service and business performance.

4 Lessons Support Teams Can Apply

L'Oréal's success with agentic AI offers practical insights for support teams looking to improve efficiency and customer satisfaction. Here are four key lessons your team can apply.

Automate Repetitive Tasks With AI

Support teams frequently deal with repetitive questions about orders, products, or troubleshooting. L'Oréal's Lore assistant manages these routine inquiries on platforms like WhatsApp and Instagram, allowing human agents to focus on more complex issues that require empathy and creative problem-solving.

This strategy not only speeds up response times but also enables simultaneous handling of multiple conversations. To replicate this, identify the top 10-15 questions that take up most of your agents' time. Train an AI assistant using your FAQs, help articles, and past chat logs. This way, your team can concentrate on high-value interactions that strengthen customer relationships.

Personalize Support at Scale

Generic responses can frustrate customers and damage your brand image. L'Oréal's Lore assistant goes beyond this by offering personalized beauty advice, using customer profiles, purchase histories, and real-time queries. It remembers previous interactions and tailors recommendations to specific needs, such as event types or personal preferences.

This level of tailored support fosters trust and encourages repeat engagement. Support teams can achieve similar results by training AI tools with company-specific data, including product guides, service scripts, and historical chats. This ensures the AI speaks in your brand's voice and provides accurate, context-aware responses that reflect your expertise.

Use AI for Trend Analysis

Great support teams aren't just reactive - they're proactive. L'Oréal leverages AI to identify beauty trends early, enabling them to adjust product strategies and marketing efforts before issues escalate.

Your team can use AI analytics to detect emerging customer concerns by monitoring social media mentions, support ticket trends, and feedback. For instance, if AI identifies a surge in questions about a particular product feature, you can update help articles, create tutorials, or adjust scripts proactively. This reduces ticket volume while enhancing customer satisfaction.

Give Teams Data Insights to Make Better Decisions

L'Oréal employs platforms like Revuze to share consumer insights across marketing, product, and sales teams, enabling quicker responses to market changes and more informed decisions.

"Our decision-making processes have been transformed with CoSupport AI Business Intelligence. It provides our team members with easy access to data insights directly through Slack, helping managers make informed decisions faster. You must try it." - Karyna Naminas, CEO, Label Your Data

Support teams can adopt a data-driven approach by tracking metrics like conversion rates, customer satisfaction scores, response times, and the distribution of queries between AI and human agents. These insights help refine strategies and improve operations.

Real-time analytics allow managers to identify bottlenecks, reallocate workloads, and enhance service quality. With access to actionable data, your team can make smarter decisions that improve both customer experience and operational efficiency.

FAQs

How does L’Oréal use Agentic AI differently from traditional customer support chatbots?

L’Oréal employs Agentic AI to elevate customer interactions far beyond the limitations of standard chatbots. While traditional chatbots often stick to pre-written scripts, Agentic AI uses advanced machine learning to dive deeper - analyzing customer behavior, predicting preferences, and delivering highly customized support.

This technology enables L’Oréal to do more than just answer questions. It anticipates customer needs, offering tailored product suggestions and solutions before users even ask. By embedding AI-driven insights into their approach, L’Oréal creates a more dynamic and forward-thinking customer experience, standing apart from the typical reactive chatbot systems.

How does Agentic AI help support teams save time and reduce costs?

Agentic AI takes customer support to the next level by automating up to 90% of inquiries, freeing up your team to tackle more complex, strategic tasks. This approach doesn’t just cut down on operating costs - it also ramps up efficiency by swiftly and accurately managing repetitive tasks.

With less pressure on human agents, businesses can trim staffing expenses while still delivering excellent customer service. Plus, Agentic AI ensures precise responses, cutting down on mistakes and boosting customer satisfaction in the process.

What can businesses learn from L’Oréal’s use of AI to enhance customer support and drive product innovation?

Businesses looking to elevate their operations can draw lessons from L’Oréal’s use of AI. By integrating AI tools, companies can gain deeper insights into customer preferences and make smarter decisions about products. AI’s ability to analyze customer data allows businesses to spot emerging trends and tailor their offerings accordingly.

When it comes to customer support, AI-powered agents can take on repetitive tasks like responding to FAQs or handling order-related queries. This frees up human agents to address more complex or sensitive issues. The result? Greater efficiency and a smoother, more satisfying experience for customers.