Which data mining task is most appropriate for the following business question?: "What is the probability that a customer will revisit our store within the next two months? (e.g. 32%)"

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BlackTom AI · Accepted Answer

Interpreting the business question, we’re asked to estimate a numeric probability (the likelihood a customer revisits within two months). This calls for a model that outputs a continuous numeric value rather than a discrete class label.
Option 1: Clustering. Clustering is an unsupervised technique used to group similar observations together without using a target variable. It does not directly provide a probability of revisiting, so it’s not suitable for predicting a numeric probability.
Option 2: Similarity matching. This approach focuses on measuring how similar two entities are, often for recommendation or retrieval tasks. It does not produce a probability or a numeric forecast of future behavior, so it does not answer the business question as posed.
Option 3: Classification. Classification predicts discrete categories (e.g., churned vs. not churned, high vs. low risk). While it can indicate whether a customer will revisit, it does not yield a probability in percent terms unless extended with probabilistic calibration, which is not the core aim here. Since the question asks for a probability (a continuous value), classification is not the best fit.
Option 4: Regression. Regression is designed to predict a continuous numeric outcome, such as a probability or expected value, which aligns with estimating the chance of a customer revisiting within a specified time frame (e.g., 32%). This makes regression the most appropriate data mining task for producing a numeric probability rather than a class label or a cluster assignment.
In summary, the task that directly delivers a numeric forecast for a future behavior metric fits the requirement of predicting a probability, whereas the other techniques focus on grouping, similarity, or discrete outcomes rather than a numeric probability.

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Which data mining task is most appropriate for the following business question?: "What is the probability that a customer will revisit our store within the next two months? (e.g. 32%)"

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