Unilever
This project aimed to enhance Unilever's customer experience (CX) by implementing a ticketing system
Project Overview
This project aimed to enhance Unilever's customer experience (CX) by implementing a ticketing system. Unilever, a global leader in consumer goods, sought to improve efficiency, optimize resource allocation, and gain valuable insights to better meet customer needs across its diverse product portfolio.
The solution involved developing a custom application using a technology stack including:
- PHP: Server-side scripting language for backend functionalities.
- Asterisk: Open-source telephony framework for managing communication channels.
- MySQL: Relational database management system for storing and managing customer data and ticket information.
- Elasticsearch: Search engine and analytics platform for enabling efficient search and retrieval of data.
- HTML and JQuery: Web development technologies for building the user interface.
Our Technology Stacks
Project Challenges
The primary challenge was to create a system that addressed the specific needs of Unilever's diverse customer base and global operations. This involved:
Efficiently categorizing
a wide range of customer inquiries, encompassing various products and service needs.
Automating repetitive tasks
such as initial inquiries and basic troubleshooting, freeing up human resources to handle complex cases.
Gathering customer feedback
to continuously improve the experience and build trust and loyalty.
Optimizing workflow
by intelligently assigning tickets to relevant support teams based on expertise and workload.
Proactive escalation management
to ensure timely resolution and avoid missed service level agreements (SLAs).
Project Outcome
The implemented AI-powered ticketing system yielded significant improvements for Unilever's customer experience:
Improved categorization
Utilizing AI algorithms, the system efficiently categorized customer inquiries, enabling faster and more accurate routing to the appropriate support team.
Optimized workflows
Automated ticket assignment based on factors like expertise and workload distribution allowed for more efficient resource allocation and faster response times.
Reduced workload
By automating repetitive tasks, the system freed up valuable time for customer service agents to focus on complex cases and personalized interactions.
Proactive escalation management
Real-time monitoring of SLAs and AI-powered predictions helped identify potential escalation scenarios and expedite resolution.
Solidified customer loyalty
Actively soliciting feedback allowed Unilever to identify areas for improvement and demonstrate their commitment to customer satisfaction.
Data-driven insights
Powerful data analytics provided valuable insights into customer trends, enabling data-driven decision making for further CX improvements.
Project Conclusion
The ticketing system has been a success for Unilever, leading to a more efficient, responsive, and data-driven customer experience. This project demonstrates how leveraging advanced technologies can empower businesses to enhance customer interactions, build trust, and achieve strategic goals.