Rick Tryon
May 9, 2017

Data Driven Decisions

In the business world, it is critical for leadership to make the most well informed and precise decisions possible to lead the company to success. These decisions are not easy and the most effective path forward cannot be based on guesswork or what the fortune cookie at lunch said. That is why business analytics exists, more specifically, the data visualization piece of business analytics.

At ClearScholar we can take aggregated application usage statistics and visualize them into meaningful reports that help expose meaningful narratives. With the wide array of data available, we can transform raw data into visualizations that show us trends in how the app is being used, what the most popular features are, and many other useful insights.

Lately, we have been focused on app usage. For us, anytime a user opens the app, this counts as a day of usage. Essentially, we want to know how often users are logging into the app and at what frequency they are returning to use it. This data is currently grouped by three different time frames; daily, weekly, and monthly. For every time frame, a user falls into one of four categories; new, active, resurrected and churned. New users are those who have never used the app and logged in for the first time in the given time period being analyzed. Active users are those who have signed back in for a consecutive timeframe, as in someone who went from being new on day one, to active if they logged in again on day two. They would remain active if they continued to log in each day/week/month. Churned users are those who have logged in at one point, but the following period did not return. And resurrected users are those who have returned after a period of being considered churned. Visualized over a period, this data shows the trend in engagement with the app and allows our team to easily spot critical points where users are becoming less engaged which can ultimately reveal a need more engagement prompts, a change in the user interface or improved content.

Apps such as Snapchat or Facebook are engineered in a way to encourage users to log in daily (or in many cases, many times a day). These usage statistics serve as a proxy for how valuable an app is for the users.  Additionally, the analytics expose areas that could be improved upon to further increase the value/engagement of the app. Our goal at ClearScholar is not to simply garner high usage statistics for the sake of the statistic, but to make the app experience worthy of frequent usage and for students to find value and purpose in using our app as they navigate their college experiences. Thanks to the data visualizations we have created, we can focus our efforts and make decisions in the areas that matter most and provide the best experience possible.