ConsumerIQ is an AI-powered intelligence hub that The Estée Lauder Companies (ELC) built using Microsoft Copilot Studio and Azure OpenAI Service. It’s designed to help teams quickly surface insights from the company’s large volume of consumer, market, and industry data. With nearly 25 brands operating in about 150 countries, ELC generates a huge amount of information across product innovation, marketing, and sales. That information lives in many formats—PDFs, PowerPoints, spreadsheets, research reports, charts, and images—spread across different teams and systems. This created several challenges: - It took weeks to manually gather and synthesize data for decisions. - Teams often didn’t know what research already existed, leading to duplicate studies and wasted effort. - In a fast-moving “TikTok world” where beauty trends change quickly, slow access to insights made it harder to get products and campaigns to market at the right time. ConsumerIQ addresses these issues by: - Centralizing ELC’s data in one place. - Using Azure OpenAI Service to read and analyze documents, charts, graphs, and images. - Providing a natural language chat interface so employees can ask questions (for example, “What are the trends in night cream?”) and get summarized, data-backed answers with citations. As a result, ELC has reduced the time to gather data from weeks to minutes, eliminated duplicate efforts, and enabled teams to make more consumer-centric decisions faster.

ConsumerIQ functions as a dynamic, AI-driven research partner for ELC’s brand, marketing, and insights teams. Here’s how it works in practice: 1. Centralized data foundation - ELC first brought its research and insights into a centralized environment. - Azure OpenAI Service was then used to “teach” the system to interpret different content types, including charts, graphs, images, and long-form documents. 2. Natural language queries - Teams interact with ConsumerIQ through a chat-style interface built in Microsoft Copilot Studio. - A marketer can ask questions like: - “What are the trends in night cream?” - “What is the mascara trend with daily exercisers?” - ConsumerIQ responds with synthesized insights, trend summaries, and strategic recommendations. 3. Actionable, traceable insights - Answers include citations and links back to original sources so users can validate findings or dive deeper. - The tool connects disparate data sources, combining historical knowledge with current studies and trends. 4. Tangible benefits - Time savings: ELC has reduced the time required to gather data from weeks to minutes. - Better focus: By automating tedious data-gathering and summarization, teams can focus on higher-value work like strategy, creative development, and product innovation. - Reduced duplication: Central visibility into existing insights helps avoid running the same or similar studies multiple times, saving both time and money. - Faster response to trends: With quicker access to insights, brands can move more quickly in response to shifting consumer behavior and beauty trends. In day-to-day terms, ConsumerIQ helps ELC teams get to the “so what?” of their data much faster, supporting more informed, consumer-centric decisions across brands.

ELC views ConsumerIQ and Microsoft Copilot Studio as a foundation they can extend across more functions and use cases over time. Key elements of their expansion plans include: 1. Broader data integration - ELC plans to bring additional data sources into ConsumerIQ so that insights become even more comprehensive. - The goal is to make the AI agent a go-to hub for intelligence across brands and functions, not just marketing and insights. 2. Scaling across brands and teams - ConsumerIQ is being scaled across ELC’s portfolio of nearly 25 brands, so teams at Origins, Estée Lauder, and others can all access the same intelligence backbone. - The company is working toward an “agentic world” where multiple Copilot agents support different parts of the business. 3. New business domains (beyond marketing) - Thanks to Copilot Studio’s low-code/no-code capabilities, ELC can create additional domain-specific agents. - One example already in motion is a supply chain agent built by an IT business partner using Copilot Studio. This agent pulls answers from supply chain documents the creator has access to. - ELC sees potential to extend similar agents into areas like supply chain, manufacturing, and other operational functions. 4. Empowering more employees to build and use AI - Copilot Studio’s intuitive, low-code environment allows business users—not just developers—to experiment with building their own agents. - This supports ELC’s culture of upskilling, giving employees opportunities to learn how to implement generative AI products using industry best practices. Overall, ELC is reimagining how its decades of intelligence can be put to work for everyone in the organization, using Copilot Studio and Azure OpenAI Service to make AI agents a practical, scalable part of everyday work.