Empowering the next generation of fans of sports leagues, teams, and entertainment companies

Internship with Vixlet

Internship with Vixlet Visuals

During the last year of my engineering, I along with my project members, Aditya Kaustubhan & Yudhveer Singh, were selected by a Los Angeles-based company, Vixlet – to develop business analytics dashboard, Empowering the next generation of fans of experiences.

Vixlet is a social network that unites people around their passion for sports. It delivers unprecedented engagement across all channels with the sports teams, artists and brands that fans love; through proprietary technology, official brand partnerships, and exclusive content and campaigns. Transcending age, gender, socio-economics and geography, passion for sport, music, art, and culture is what brings Vixlet users together.

For a start, Vixlet developed and operates for social networking applications linked to sports leagues, teams, and entertainment companies, namely, Slipknot, MLB, ATP, and LFC Xtra.

The roaring success of their applications leads to an expansive collection of data. Thus using all that unstructured data to make informed decisions became a challenge. So there was a necessity of a dashboard, that could help not just visualize the plethora of data collected but also perform predictive analysis on the training data. This data was primarily used to learn and improve the user experience of fans (the end customers).

I have also written an article about - The Romance of Data & Design.

“Every Business can benefit from becoming more analytical- understanding its customers, performing its operations, and making its decisions. But even the most analytically oriented company needs to target its analytical efforts where they will do the most good.”

Problem 1

It is of prime importance for a social media company to find patterns in user-interactions and succeed in the cutthroat social media environment. Here we used the Apriori Algorithm to predict insights from the data.

Problem 2

Analyzing customer feedback is important. This requires an intensive analysis of the reviews received of the application. For this part of the problem, we developed a module to access Google Play Store Reviews using the N-Gram version of the Random Forest Algorithm.

Under the guidance of Pawan Gupta, (who was the Mobile Engineering Lead at Vixlet), I and my team were able to produce a robust platform for their team in LA. During this project, we were also able to publish a technical paper in IJOART titled - Google Play Store Review: Mining Application Store to interpret User Experience, the relationship between Business and Technical Characteristics through Sentimental Analysis. You can find a complete overview of the project in this presentation below.