Impact Analytics is helping a non-profit organization improve their content creating strategies and operational processes using advanced AI and ML-based applications that further enhance customer engagement
The client could not zero-in on the exact groups of students who accessed the app on the tablet or even the content that worked well within these groups. Categorizing them into any specific cluster was not feasible without the help of deep analytical insights.
Data collected from each tablet was housed in a local server that would record the multiple variables needed to analyze the data. Various data sets such as the subjects, quizzes, time logged in, engagement levels, etc., were recorded to get an understanding of the overall effect of the smart-tablets distribution.
Voluminous data generated did not have any pattern for easy comprehension and implementation of new strategies to improve engagement. Impact Analytics performed extensive exploratory data analysis and clustering to understand trends in the data.
Days in a month
1.The average number of days the app was accessed in a month by a group.
2.The metric was divided by 30 days to normalize the variable.
The total number of resources accessed by the group in their history as a percentage of the total number of resources available to the group.
Time spent on the app
1.The total time spent on the app per day (in seconds)
2.The variable was normalized by dividing by 86400 (no. of seconds in a day).