Name
Abstract | ||
|---|---|---|
Employers today are struggling to engage positively with their employees to reduce attrition and improve productivity. There are solutions in the market which are trying to solve the problem but they suffer from two critical issues. Firstly, the scope of the existing solutions is too narrow to capture each and every interaction happening within the company. Secondly, their learning from the employee behaviour is either non-existent or minimal at best. Personalized Messaging Engine (PME) is an attempt to provide end-to-end system to organizations for effective employee engagement. PME uses SOA principles to connect to each and every system through which employees engage with their employers. It uses the data aggregated from multiple systems to provide a hyper-personalized and dynamic experience to each employee. With the help of APIs, multiple systems can push data to PME and it then processes the data to send relevant pre-configured messages to the employees in the domain of Health, Wealth and Career. Additionally, PME uses several factors to prioritize messages for each and every employee. It uses a state-of-the-art learning engine to combine Subject Matter Experts opinion, Client Strategy, User Experiences and behaviour to find the messages which are most effective for the employees. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-662-48616-0_36 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Service oriented architecture,Recommendation engine,Personalized messaging,Employee engagement | World Wide Web,Computer science,Subject-matter expert,Employee engagement,Attrition,Service-oriented architecture | Conference |
Volume | ISSN | Citations |
9435 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Varun Sharma | 1 | 1 | 0.70 |
| abhishek tripathi | 2 | 0 | 1.01 |
| Saurabh Srivastava | 3 | 184 | 19.27 |
| Aditya Hegde | 4 | 4 | 1.42 |
| Koustuv Dasgupta | 5 | 626 | 46.44 |