Academic Work
ABILITIES AT A GLANCE
CONTENTS AT A GLANCE
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1. MSc & Pre-MSc Theses
2. Analysis Result Reports
3. Extra: "MADS Madlad" Course Summaries
In this chapter, I showcase my MSc and Pre-MSc theses. The programming behind these can be found on my GitHub.
(click on the document to see the next page or download it with the link)
Willingness to Share Health Data in Italy:
Investigation under a Multi-context Paradigm with DCE data.
Keywords: Digital Health data · Secondary use of Data · Discrete Choice Experiment · Latent Class Analysis
Download*
Download* · Stata Code* · R Code*
Download* · R Code*
Note: As the survey feedback was written in Italian, all feedback entries had to be translated. I used the Translate API provided by Google to automatically translate all the entries in my data frame. Therefore, the quality of translation may influence the results of the subsequent sentiment analysis.
* Limited access until further notice.
Investigating the Effect of Earnings Call Sentiment on Stock Volatility.
Keywords: Earnings conference calls · Sentiment analysis · Stock volatility
In this chapter, I showcase the culmination of my data analysis and programming efforts in the form of visual and written reports. The code behind every project can be found on my GitHub.
This section specifically focuses on visual reports, showcasing my abilities in data visualization and storytelling.
(click on the document to see the next page or download it with the link)
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Investigating the effectiveness of communication in online marketing campaigns using traditional and machine learning methods, focusing on text mining, sentiment analysis & more.
Analysing the impact of Wehkamp's AR app on their customers. Focusing on repeat purchases, customer value, repurchases, revenue and transaction frequency.
Reporting the results of time-series analysis, investigating the 4Ps of Redstar vs. Competitors.
Reporting the results of hierarchical & nonhierarchical cluster analyses, investigating car buying preferences of consumers based on survey data.
Performing a Factor Analysis to investigate important factors in people's attitudes towards sustainable clothing.
Reporting the results of exploratory analyses investigating various aspects of consumer attitudes towards meal kits based on survey data.
Proposal for a retail mix strategy for Kruidvat, based on internal and external market conditions in the makeup industry.
Proposal for an omnichannel strategy to L'Oreal based on internal data analysis and external market analysis.
Video proposal for a brand extension to Volkswagen based on market analysis.
Showcase of VW Ad Concepts
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This section specifically focuses on written reports, showcasing my abilities in academic and corporate reporting.
(click on the document to see the next page or download it with the link)
Modelling churn with both traditional methods and machine learning (tree models, bagging, boosting and neural networks).
Building a regression model for the Dutch lemonade retail market, working with data from various retailers (Albert Heijn, Jumbo, etc.) for brands such as (Raak, Karvan Cevitam, etc.).
Investigation of key drivers of conversion rate and their optimization for product category of an online retailer.
Tackling three business ethics issues in the form of three short papers, based on ethics theory & literature review.
During my master year I set out to write the most complete premium course summaries available for the MADS MSc program. After writing over 800 pages and helping over 50 students during my studies, I decided to sell them with 100% of proceeds going to various Dutch charities. My summaries maintain a position as the most thoroughly-written documents on Stuvia and Knoowy, the two most prominent summary platforms in the Netherlands.
Sample Documents
In this section I provide samples of my summaries as a showcase. The full summaries are distributed through Stuvia & Knoowy, with 100% of the proceeds being accumulated for charity.
(click on the document to see the next page or download it with the link)
Data Science Methods
Market Models
Digital Marketing Intelligence
Retail & Omnichannel Marketing
Data Engineering
Statistical Learning in Marketing
Companies, Brands & Consumers
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