L'Oréal New CRM Platform - C360
Launched To-B Project
The goal of this project was to design a centralized consumer profile search tool (C360) that enables L’Oréal teams to quickly access accurate, complete consumer data without relying on backend support.
My role
Product Manager
UX Designer
Team
2 Project Managers
4 Developers
Time duration
Jun - Aug 2025
Project Context: From Third-Party CRM to L’Oréal-Owned Platform
As L’Oréal expanded its presence in Asia, the company shifted from using third-party CRM platforms to developing its own internal system. This move was driven by the need for greater customization, full ownership of consumer data, and better support for local market needs.
Problem
As L’Oréal transitioned to its in-house CRM system, internal teams lacked a unified way to access consumer data. Agents often had to contact backend teams to retrieve fragmented information, with no centralized view of the consumer. This not only slowed down response time but also made it difficult to deliver timely, personalized support.
Opportunity
C360 was designed to bridge that gap, which is a centralized dashboard that empowers internal teams to quickly search, view, and understand a consumer’s full profile. This was an opportunity to streamline workflows, reduce dependency on data teams, and lay the foundation for smarter consumer interactions.
Impact
Following the MVP rollout of the C360 dashboard in key APAC markets, the tool significantly streamlined agent workflows and became an essential daily tool for customer-facing teams.
80%
agent usage rate within first month
10x faster
consumer lookup time (reduced from ~5 min to < 30s)
2 new markets
launched with customized regional data display needs
My Role in the Larger System
As part of L’Oréal’s CRM system migration from a third-party platform to an in-house solution, I was the product manager intern responsible for the C360, a consumer profile dashboard used by agents and internal users to quickly access and manage consumer profiles across different markets and brands.
I was the only team member with a UX background, which gave me full ownership of the end-to-end product design. In addition to creating wireframes and interaction flows, I also worked closely with data and development teams to align technical constraints with user needs.
Key UX Challenges
Challenge 1: Balancing Global Standards and Local Adaptation
Each market had its own data visibility rules, preferred contact methods, and regulatory needs. I designed flexible UI components that could adapt based on regional rules while maintaining visual consistency.
Challenge 2: Making CRM Data Legible for Non-technical Users
Many agents using the C360 are not technical, so I simplified data presentation using grouped sections, clear labels, and status indicators to highlight key actions.
?
How might we turn scattered consumer data into a clear, centralized view for agents and CRM specialists?
Design Process - From Agents Workflow to Design Decisions
Understanding the Real Workflow
My first step wasn’t opening Figma. It was talking directly with the agents who would use the tool. I conducted interviews and informal walkthroughs with customer service agents across multiple markets (e.g. Australia, Hong Kong, Japan), and asked:
When do you need to look up a consumer’s profile?
What’s the information you need first?
What slows you down in your current process?
Some key insight I got from the interviews:
Defining the Use Cases
Based on those conversations, I mapped out the most frequent use scenarios. This helped me prioritize the data fields to display.
Use Case
Primary Info Needed
NPS Detractor Follow-up
Recent order status, NPS survey answers
Complaint Escalation
Contact preferences, Purchase history
Internal Enquiry
CRM profile completeness, opt-in status
Identifying Data Needs and Logical Categorization
First Rollout: Launching the MVP
We had a tight deadline and our primary objective was to deliver a functional MVP, especially for the Hong Kong and Taiwan markets. Therefore, our design focus was data visibility and UI layout for agents to view consolidated consumer info.
At this point, search and filtering logic were still limited. My job was to ensure key consumer data were clearly displayed and accessible.
Second Rollout: Search Optimization & AI-Powered Smart Search
In my second round of field research and usage observation, I discovered that:
Over 70% of time spent on C360 was on the search interface
CRM specialists wanted to target groups, not just individuals
Therefore, the design priorities for phase 2 are:
Designing for different user types: Agents vs. Brand CRM Specialists
Introduced concept of Ask AI to find consumer groups by natural language queries
In my second round of field research and usage observation, I discovered that:
Over 70% of time spent on C360 was on the search interface
CRM specialists wanted to target groups, not just individuals
Therefore, the design priorities for phase 2 are:
Designing for different user types: Agents vs. Brand CRM Specialists
Introduced concept of Ask AI to find consumer groups by natural language queries
Consumer Search Page Iterations
AI-Powered Consumer Segments Search
Problem
While the original C360 system allowed agents to search for specific consumers using known identifiers like email or name, it lacked the flexibility to help CRM specialists and brand teams target groups of consumers based on behavior or segmentation criteria. This limited their ability to run campaigns or personalize communication at scale.
Opportunity
Enable agents to query consumer data by natural language instead of fixed identifiers, unlocking segmentation and campaign use cases with AI-assisted interpretation and automation.
L'Oréal New CRM Platform
Launched To-B Project
Enabling a Closed Feedback Loop Through NPS Integration
My role
Product Manager
UX Designer
Time duration
Jun - Aug 2025
Team
2 Project Managers
4 Developers
L'Oréal New CRM Platform
Launched To-B Project
Enabling a Closed Feedback Loop Through NPS Integration
Time duration
Jun - Aug 2025
Team
2 Project Managers
4 Developers
My role
Product Manager
UX Designer
Project Context
The project aimed to close the NPS feedback loop by allowing brands to respond quickly to unsatisfied customers. Whenever a consumer leaves negative feedback in a post-purchase NPS survey, the system automatically generates a case and routes it to local customer care agents. The agents are then empowered to proactively reach out, resolve the issue, and turn potential churn into loyalty.