Difference between revisions of "Proposed projects"
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Ideally: the solution can self learn from its own set of data. Eg. In University A, there are 10,000 students. The more students upload their resumes, the more sample data the system can use as sample data. You have to consider how Kinobi/System itself can classify & train the data (Consider supervised training). <br>--> | Ideally: the solution can self learn from its own set of data. Eg. In University A, there are 10,000 students. The more students upload their resumes, the more sample data the system can use as sample data. You have to consider how Kinobi/System itself can classify & train the data (Consider supervised training). <br>--> | ||
| − | === Project proposed by Willowmore === | + | <!--=== Project proposed by Willowmore === |
[https://www.willowmore.com.sg/ Willowmore] is a leading Smart Access, IoT and Analytics company based in Singapore. | [https://www.willowmore.com.sg/ Willowmore] is a leading Smart Access, IoT and Analytics company based in Singapore. | ||
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* '''Deliverables:''' To be defined together with the student team during initial discussions. | * '''Deliverables:''' To be defined together with the student team during initial discussions. | ||
* '''Point of contact:''' Joseph Tey (joseph.tey@willowmore.com.sg) | * '''Point of contact:''' Joseph Tey (joseph.tey@willowmore.com.sg) | ||
| + | --> | ||
Revision as of 11:03, 4 August 2023
Instructions on sponsor engagement
The information has been updated in March 2023. As many teams may be approaching sponsors, sponsors will discuss with the various teams and decide which team to work with. If your team has already confirmed a project with a sponsor, please let the faculty manager know so that we can update the website for other students.
For self sourced sponsors
Teams are encouraged to source sponsors from internships, SMU-X modules and personal contacts. The deck here can be shared with the sponsors to clarify any roles and responsibilities with them and request them to contact the faculty manager at kiruthikar@smu.edu.sg for any clarifications File:Sponsor information deck.pptx
Projects
<!=== Project(s) proposed by Standard Chartered === 1. Onsite personalization to maximize the digital engagement
The Digital use case is divided into two parts:
1) Journey evaluation : Study how users traverse the StanC website, understand the broken journeys, their option selection preferences, etc - by different segments, countries and products
a. Prepare an analysis which talks about how different users navigate on our website (major routes they take to reach their goals), what are the options they show more interest in, how many have journey breakages and why, etc
b. Propose recommendations to improve/smoothen the site navigation and prevent drop offs
c. How the above two vary by different user segments, their location, etc
2) Personalization : Predict the likelihood of a product transaction (eg cash payment, trade transaction, etc) at each step/page of the journey from the time a user lands on the website and recommend the next best click/clicks at that step (which can be shown as a pop up or a CTA) to optimize the conversions. - This would require participants to use the clustering techniques for customer segmentation and Machine Learning / Statistical modelling for predictive analysis
Data that will be provided : Google Analytics data from StanC’s Digital platforms (Web, Mobile, etc)
For further information, please contact Rahul Gupta (Rahul.gupta5@sc.com).-->
For more information, please contact Sky @ sky.lim@zhongguoremittance.com -->
