Work
Below you will find a few of the projects I completed during my time as a student at the University of Texas at Austin Masters of Marketing Analytics program that underscores my skills and versatility in the marketing field. Click on the projects pictures to see each slide deck!
7-Eleven
7-Eleven was my client for my final capstone project in the Master of Science in Marketing program. The main objective of the project was to increase sales and revenue from the loyalty program. To achieve this, my team defined loyalty program segments from 30 million POS transactions, and used Market Basket Analysis in SQL. From our findings, we developed promotional and in-app messaging tailored to each segment, taking into account their specific demographics and purchasing behaviors.
Gooden Sweet
My team created a proposal for a small business to showcase the skills we learned in our digital marketing class. We redesigned 2 pages of the company's existing website, complete an SEO audit on the company's website, and designed and implemented both an email and a social media campaign.
GAP
My team developed a go-to-market plan for GAP that takes into consideration challenges brands face in today's fragmented marketplace. The project was divided into 3 sections, with each section building upon the content of the previous sections to simulate the sequence of marketing decision making and program management. The first section focused on brand strategy, development, and management; the second section, product development and management; and the final section, development of go-to-market plans to take brands or products to market. We created a go-to-market strategy for a new GAP product broadly targeting Gen Z.
Sporkful
My team created a proposal in response to Cascatelli's RFP (request for proposals) with the broad goal of assisting the company acquire new customers, ideally ones with high CLV. We had 3 days to construct a plan for how Sporkful, the parent company, could best invest $100k.
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Movie Attribute Analysis
I analyzed a Kaggle data set of 6,820 movies released between 1986 and 2016 to understand which factors such as budget, country, and genre contributed most to a movie's success. After investigating the data and creating a model, I was able to predict if a given movie was going to be successful or fail with an accuracy of 95%.
Airbnb
I conducted an analysis on a dataset called "Airbnb Listings," which had information on thousands of Airbnb's in the New York boroughs. The dataset includes details on listing locations, pricing, property types, and various other features. By employing visualizations and data analysis techniques, I was able to better understand the nature of the Airbnb listings in data set, determine qualities that could make an Airbnb successful and pinpoint the most favorable areas for acquiring a property suitable for Airbnb hosting.
