Specialisterne Digital Media Analysis

Project Description

​

This project was completed in a group as a final project for Professor Villaespesa’s Digital Analytics Course. The objective of the project was to conduct an analysis of Specialisterne’s web and social media analytics. The analysis was conducted in four main phases, which followed a mixed-methods approach. These analyses utilized a number of technologies which includes Microsoft Excel, Google Analytics, Keyhole, Python and Tableau Public. In addition to delivering a final report and presentation of findings, we also designed an interactive dashboard using Google Data Studio for the organization to track key web metrics moving forward. 

​

Method

​

For this project, we were able to obtain datasets from information on Twitter and LinkedIn analytics data in the form of CSV files and created one master CSV using Microsoft Excel. We needed to do some data cleaning which was also done using Microsoft Excel. Ideally, we wanted to examine a full year’s worth of data from January 1, 2019 – December 31, 2019. However, there was no data available on LinkedIn before May 2019 so for that analysis, we examined and compared posts from May 2019 - December 2019 on both platforms. We created several visualizations of the data using Altair, which is a Python library, tableau public, keyhole, Google Analytics, and Google Data Studio. There were four major parts that were conducted through a mixed-methods approach, which ultimately arrived at meaningful recommendations. The four parts are below:

 

1.     Twitter vs. LinkedIn Comparison

2.     Post Success Analysis

3.     Hashtag Analysis

4.     Web Data Analysis

 

The final deliverables for this project were a full detailed report, a presentation of findings, and finally an interactive dashboard created using Google Data Studio. The dashboard was designed to tracked key metrics, which are pulled from Specialisterne’s Google Analytics account.

​

My Role

​

This was a group project consisting of five Pratt students - Erik Hannel,  Devinshi Gami, Devin Singh, Zane Castillo, and Tian Jing. Although we each contributed to each part of this project, I mainly focused on one aspect, which was the web analytics analysis. I initially conducted exploratory analyses on the web analytics data by creating dashboard in both Google Analytics and Google Data Studio. Additionally, I worked on data analysis for all four parts of the study, served as a point of communication between our team and client, worked on all aspects of the final report and presentation, and presented findings in the form of a video presentation.

​

Learning Outcome Achieved 

​

User-Centered Design - Students can identify relevant users and develop intuitive, meaningful, and engaging experiences for them.

​

Rationale

​

User Centered Design - This project demonstrates my understanding of issues related to use and user data. Throughout this project, I employed a variety of research approaches aimed at understanding user behavior through data analysis from web and social media data. We created a number of visualizations to effectively visualize findings in a digestible manner. Finally, I was able to design an interactive dashboard which was grounded in data from our client interview, social media, and web data analysis.