In addition to our traditional readings and assignments throughout the semester, we will work through 5 in-depth analytic cases. Each case has its own page (with detailed instructions coming soon):

Google Analytics: Predicting Goal Conversions

LimeCuda, a web development company focused on meeting the needs of small businesses, has graciously provided access to a few clients and their associated Google Analytics’ accounts. By understanding these companies’ business goals, our endeavors will not only provide learning opportunities for the class, but hopefully actionable insights for the companies.

Predicting Customer Churn

Endurance International Group (EIG) serves millions of customers with a variety of web hosting services. Given the nature of the business, customers come and customers go. Regarding the latter, in an ideal world, EIG would know which customers were considering leaving, and when. With that information, EIG would be able to reach out to these customers to prevent unprofitable churn. We will build a predictive model to hopefully help EIG get closer to this ideal world.

What Drives Customer Satisfaction in Service Projects?

Professional services are on the rise in the global economy, and due to the private nature of business to business (B2B) transactions, very little is known about the profitability and successfulness of such projects. In partnership with the Technology Services Industry Association (TSIA), we will explore a proprietary database of over 600 IT professional service projects with 50+ metrics. We are tasked with segmenting the projects and uncovering the main drivers behind customer satisfaction. Our work will leverage clustering algorithms, followed by multivariate predictive analysis.

Market Basket Analysis: Predicting the Next Product Purchase

EIG offers a portfolio of over 50 products its customers. Unfortunately, every customer is different and a major challenge is to figure out what products are best suited for each customer at a given moment in time. Given customer demographics, time with the company, and other products currently utilized, we must predict what products are most likely to be purchased next by the customer. With that predictive power, EIG would be able to upsell its current clients in an efficient manner.

Textual Analysis

Over 75% of a typical company’s information is in the form of unstructured text. In small groups, you will track a topic of interest throughout the semester and build up a database of relevant text. Through a series of blog posts, you will reveal the context and specific analysis questions related to your topic. When we began this section of the course, small groups will carry out the necessary analysis to provide answers to these questions.

For those students interested in working on a text project for a business, Luna Metrics, a certified Google Analytics Partner, has provided a unique problem and relevant data for this part of the class. This group will crawl previous versions of client websites for leading text indicators of client profitability and revenue – stay tuned for more info.