The problem analyticsAtScholify solves

This analytic tool is specifically design to develop a user journey graph model that captures and presents on a sophisticated yet simple to operate lightweight admin dashboard. The main aim to identify articuation points with the user flow of the system and provide a tool for appropriate actions to mitigate those pain points.

The will further optimize scholarship campaign with each listing and help the company manage it's users based on their interaction with the platform.

This tools can be further integrated with a Machine Learning model to derive insights on types of users based on the user path they cluster into.

Challenges we ran into

The big challenge was to visualize the semi structured data into a graph format and then derive a CSM system within the graph. Due to the inherent complexity of graph algorithms, we had to come up with a workaround and directly convert a design file into a graph format which makes the dashboard design-independent.
The other challenge was to apply the appropriate ML model which could cluster the users based on their user-paths and provide a valuable insight to the company. We referred several research papers on human psychology and found a special form of clustering algorithm that divides user catergories based on their sentiments while using the app.