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Cartel Coffee Lab: Customer Analysis, Segmentation, & Marketing Impacts

Description
This paper explores a cluster analysis and data-driven marketing recommendations for Cartel Coffee Lab, a local coffee shop. Building a loyal customer base is the biggest asset to a company’s success. This is crucial when Cartel’s main location has a fast-changing environment, such as a university, located nearby. The reason…

This paper explores a cluster analysis and data-driven marketing recommendations for Cartel Coffee Lab, a local coffee shop. Building a loyal customer base is the biggest asset to a company’s success. This is crucial when Cartel’s main location has a fast-changing environment, such as a university, located nearby. The reason for this is mainly due to the influx and customer churn that a hub produces. Our team’s focus was on analyzing customer buying patterns to determine the different customer segments within Cartel Coffee Lab. Our methods included creating temporary databases in Microsoft SQL Server and performing a cluster analysis in SAS Enterprise Miner. The cluster analysis results were then used to propose data-driven marketing recommendations for each customer segment in order to provide a well-designed value proposition. Additionally, a loyalty program was recommended in order to increase customer profitability and loyalty, depending on the cluster segment. Through identifying the current situation, business questions, research methodology, analysis results, and plan of action, this creative project will cover multiple key areas of a business analytics project.
ContributorsSummersgill, Sarah Katherine (Co-author) / Fabre, Eve (Co-author) / Zhang, Zhongju (Thesis director) / Giles, Charles (Committee member) / Department of Marketing (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05