A professional association is funded by membership fees. The membership renewal occurs every 5 years. Although, they have a strong subscription rate each year, their renewal rate is low. They are working with an external firm specializing in Business Analytics to identify the groups of customers that have a high likelihood of cancelling their subscription after their first 5-year term ends.
This type of study is called:
Supervised learning is appropriate for this type of study because it involves using historical data where the outcomes are known (in this case, whether customers canceled or renewed their subscriptions) to train a model. The model can then predict the likelihood of cancellation for current customers based on their characteristics and behaviors.
Supervised learning not in the guide.... none of the answers are. Research got me to this: 1.3 Bss Data Analytics Objectives: • Predictive: Analyzes past trends in data to provide future insights. Predictive analytics is used to answer the question “What is likely to happen?” • Example: Predicting profit or loss that is likely to happen in the next financial year. Supervised learning is the correct term for this type of study. It involves using historical data where the outcomes are known (in this case, whether customers canceled or renewed their subscriptions) to train a model. The model can then be used to predict the likelihood of cancellation for current customers based on their characteristics and behaviors. Supervised learning = Predictive analytics