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Welcome

Hello, and welcome to my analytics portfolio. My name is Jordan Cherry, and I'm currently finishing up my master's degree in Analytics from Villanova University. I've established this space as a platform to show you what I've been able to do with my training, skills, and insight. I hope that this space gives you an opportunity to get to know me and my work, and perhaps learn a few things about the world as I post about various data projects I've been working on.

Thanks for coming. I'm glad you're here.

-Jordan

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Text and Web Mining Analysis of Nike's 2018 Just Do It Campaign

Colin Kaepernick, Nike, and the Consequences of the 2018 Just Do It Campaign: An Analysis of Social Media, Press, and Stock Reactions Kwong Yau Sarah Erbes Scott Mow & Jordan Cherry December 14, 2018 Executive Summary This project attempts to analyze the effect of Nike’s use of Colin Kaepernick as the lead athlete for its 2018 marketing campaign on its stock price during that period. We outlined a three-fold approach: ·         Examine the social media reaction to determine overall sentiment about Colin Kaepernick’s partnership with Nike ·         Examine press reactions to determine press coverage sentiment about Colin Kaepernick’s partnership with Nike ·         Examine financial data to examine possible correlations between media (both trad...
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A Prediction Model for High-Dollar Black Friday Shoppers

Overview Black Friday is the most significant retail shopping day in America and being able to plan strategy around attracting high-dollar buyers would be an important advantage for retailers in an increasingly competitive retail market. Using a Kaggle dataset and Alteryx, I created three predictive models for finding shoppers likely to spend more than $10,000 on their Black Friday shopping.   Description of the Data The dataset for this project was obtained from Kaggle and uploaded into Alteryx. I used Alteryx to examine the data, looking for missing values or outliers. None were found in the data, and the data seemed to be very clean, so little to no cleaning the data was necessary. The dataset contained 537,577 records. Given the cleanliness of the data, I proceeded to explore the data. Model Selection I created multiple models in Alteryx, including boosted tree, decision tree, and neural network models. The model results are as follows: -    ...
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