Guell Appliances: A Refrigerator's World We're Just Living In

In July 2022, a senior data scientist for Guell Appliances was aggregating customer reviews from the company’s recent appliance launch. The previous month, the company had launched a revamped product line that required a significant amount of investment in research and development. The success of the product line was paramount because it defined the success of the company. The senior data scientist wanted to apply modern analytical techniques to thousands of product reviews to thoroughly understand the preferences of customers, based on what they were saying about their new appliances.

This case is suitable for courses at the undergraduate and graduate level that cover topics in machine learning and analytics, such as clustering, in particular. Students with a background in programming will be able to greatly simplify their analysis, although calculations can also be performed using tools such as R or Python. This case allows students to explore a popular problem that most retailers face: receiving and understanding real and honest customer feedback about their products. Students are presented with real-world retailer data and are tasked with analyzing textual review data and determining customer sentiments of product reviews to help the business improve its product feedback cycle and remain competitive in the market. After completion of this case, students will be able to accomplish the following objectives:<br><br><ul><li>Learn about topic modelling, natural language processing, and cross-validation.</li><li>Create visualizations that make sense in the context of the business problem (product sentiments).</li><li>Compare classification models, calculate accuracy, and generate insights for retail.</li></ul>

• customer preferences
• text mining
• machine learning