Job details
Job Responsibilities
- Provides strong, dynamic leadership that mentors, develops and guides team members to efficiently leverage the value of every enquiry for turning brokers become advocates of Cigna Healthcare Hong Kong;
- Establish policies and procedures, to promote good governance while maintaining good broker relation;
- Ensure an effective and efficient pipeline management processes established to the team and to ensure all new business cases are followed & implemented accurately and in a professional manner;
- Drive continuous improvement on brokers experience;
- Support Broker Contact Strategy for assigned book of business to develop and maintain relationships with brokers and clients;
- Handle brokers’ escalated enquiries & complaints, and solving problems using independent judgment and ensuring satisfaction. Identify improvements to prevent issues from re-occurring;
- Provide regular training to staff to meet performance expectations. Ensure effective staffing and resource utilization to meet the needs of BAU & Projects;
- Be a backup to address brokers’ enquiries on global medical plans
- Maintain knowledge of all systems, products, programs, services, benefits and utilize this knowledge in effective resolution of broker and customer issues regarding the quote and buy process;
- Own broker portal utilization and action on broker feedback for driving better broker journey
- Manage ad-hoc projects and duties;
- Be a liaison among the team and internal departments and to the brokers;
- Prepare monthly management report and ad-hoc report for management.
- University education with minimum 5 years’ working experience in broker support functions
- 4 years in supervision experience
- IIQE Paper 1,2,3 required
- Solid experience to work with Sales/Brokerage
- Health insurance background preferred
- Self-motivated and able to manage priorities in meeting tight deadlines
- Detailed oriented, organized and able to work independently
- Excellent communication skills in both written and spoken English and Chinese
- Solid knowledge of Microsoft applications including Word, Excel, PowerPoint and Outlook
- Strong communication and organizational skills to effectively communicate and interact with all levels and functions within the organization.
- Ability to manage multiple and divergent priorities and deadlines, work independently and proactively, negotiate and manage expectations for mutually acceptable solutions and creatively problem-solve effective customer solutions
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Increased competition has put more focus on optimizing business processes and make informed business decisions. Analytics provide informed insights for effective decision making by data collation processing and analysis. Retail analytics is the upcoming technology which helps in increased retail sales and better inventory management.<br /> <br /> <strong>The course covers</strong> <ul> <li>Basics of Analytics and statistics </li> <li>Using MS-Excel for analytics</li> <li>Pricing Analytics</li> <li>Retail Operations Analytics</li> <li>Clustering Techniques</li> <li>Customer Analytics</li> </ul> <strong>Why should I take Retail Analytics Certification?</strong><br /> This course is intended for retail professionals, managers, consultants and graduates wanting to excel in retail analytics. It is also well suited for those who are already working and would like to take certification for further career progression. Earning Vskills Certified Retail Analytics Professional Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.<br /> <br /> <strong>How will benefit from taking this Certification?</strong><br /> Job seekers looking to find employment in retail, stores, inventory, retail management departments of various retail companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification.<br /> <br /> <strong>Benefits of Certification</strong> <ul> <li><strong>Government certification</strong></li> <li>Certification valid for life</li> <li>Lifelong e-learning access</li> <li>Learning Hours: 30+ hrs</li> </ul> <br /> <strong>How It Works</strong> <ol> <li>Select Certification & Register</li> <li>Receive Online e-Learning Access (LMS)</li> <li>Take exam online anywhere, anytime</li> <li>Get certified & Increase Employability</li> </ol> <strong>Test Details</strong> <ul> <li>Duration: 60 minutes</li> <li>No. of questions: 50</li> <li>Maximum marks: 50, Passing marks: 25 (50%).</li> <li>There is NO negative marking in this module.</li> <li>Online exam.</li> </ul> <br /> <strong>TABLE OF CONTENT</strong><br /> <br /> <strong>Introduction to Retail Analytics</strong> <ul> <li>Overview of the Retail Industry</li> <li>An Overview of Role of Analytics</li> <li>Overview of Retail Data Sources</li> <li>Data Collection and Preparation Techniques</li> <li>Retail Analytics Applications</li> <li>Retail Analytics Tools</li> </ul> <strong>Retail Data Collection and Preparation</strong> <ul> <li>Retail Data Sources</li> <li>Data Collection Methods</li> <li>Data Cleaning</li> <li>Data Warehousing</li> <li>Data Visualization</li> <li>Data Security</li> <li>Data Governance</li> <li>Retail Data 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Basics</li> <li>Measurement Systems</li> <li>Some Basic Terms</li> <li>Types of Sample Designs</li> <li>Bases of stratification</li> <li>Characteristics of a Good Sample Design</li> <li>Determining the Sample Size</li> </ul> <strong>Data Processing and Analysis</strong> <ul> <li>Data Preparation</li> <li>Data Validation</li> <li>Data Editing</li> <li>Coding</li> <li>Tabulation</li> <li>Data-Processing Methods</li> </ul> <strong>Introduction to Data Analytics</strong> <ul> <li>Origin of Data in Retail Analytics</li> <li>Processes in Retail and Supply Chain Analytics</li> <li>Analytical methods used in Retail Analytics</li> <li>Use of Data Analytics and Decision-Making Models</li> <li>Advanced Analytics in Retail</li> <li>Overview of IoT (Internet of Things) and its application in Retail</li> <li>Understanding Contemporary Analytics</li> </ul> <strong>Clustering Techniques in Retail Analytics</strong> <ul> <li>Introduction to Clustering</li> <li>Types of Clustering Algorithms</li> <li>K-means Clustering</li> <li>Hierarchical Clustering</li> <li>Density-based Clustering</li> <li>Model-Based Clustering</li> <li>Clustering Evaluation Metrics</li> <li>Applications of Clustering in Retail Analytics</li> <li>Limitations and Challenges of Clustering Techniques</li> </ul> <strong>Customer Analytics</strong> <ul> <li>Introduction to Customer Analytics</li> <li>Customer Data Collection and Management</li> <li>Customer Segmentation</li> <li>Customer Profiling</li> <li>Customer Lifetime Value</li> <li>Customer Churn Analysis</li> <li>Customer Behavior Analysis</li> <li>Customer Feedback Analysis</li> <li>Customer Journey Mapping</li> <li>Applications of Customer Analytics</li> </ul> <strong>Introduction to Pricing Analytics</strong> <ul> <li>Price Elasticity of Demand</li> <li>Competitor Pricing Analysis</li> <li>Customer Segmentation</li> <li>Price Optimization</li> <li>Price Perception</li> <li>Price Psychology</li> <li>Price Discrimination</li> <li>Price Bundling</li> 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