Coming in to the hackathon and looking at all the data and the challenges involved, we were sure it would be quite difficult but we were inspired to work with the large sums of data. We wanted to provide advertisers and black Friday retailers with a marketing tool to spend their marketing dollars in the areas (regions within a city) which had the most traction for sales.

What it does

This application is a simple web application which provides advertisers and black Friday retailers insight into mobile application data! We created a heat map to display the data and density based on the longitudes and longitudes. The end product reveals which applications running on mobile phones were utilized the most and where on a physical map. In terms of the process of creating it, we used tableau to mine and link 4 tables in the M2 catalyst database provided. We then utilized the longitudes, latitudes, and frequency information to feed the google API to show case the heat map of mobile app usage. We also implemented markers to show top application uses within a region. For further insights, we provided Instagram and Snapchat heatmaps to view application uses throughout a region.

What we learned

We learned a lot about data mining, and we succeeded in creating a pre-revenue model for our prototype.We learned a lot about data analysis, product development, and API configuration with data sets. It was challenging at first in terms of mining the data and figuring out which parts of the data we wanted to utilize in order to present a good marketing tool for advertisers and black Friday retailers.

What's next for Black Friday Insights

Black Friday Insights looks to develop further to provide better data related marketing tools! Obviously, because the data was limited, we were only able to identify regions within a certain segment in New York; however, this could easily be applicable to other regions as long as the data facilitates.

Share this project: