Data Science & Analytics Flashcards

Vocabulary flashcards covering key concepts from the Data Science & Analytics lecture notes.

Customer Churn (Churn Rate)

The percentage of customers who stop doing business with you over a given time period.

Demographics

The basic background traits of your customer base—such as age, location, gender, income level, or occupation.

Clustering (Customer Segmentation)

An unsupervised learning technique that automatically groups similar customers together based on shared habits or traits.

RFM Analysis (Recency, Frequency, Monetary)

A framework to rank customers by how recently they bought (Recency), how often they buy (Frequency), and how much they spend (Monetary).

CLV (Customer Lifetime Value)

The total estimated net profit a business expects to earn from a single customer throughout their entire relationship.

Classification Models

Algorithms trained on past patterns to output a category label—like predicting whether a user will "Churn" or "Stay".

Feature Importance

A score showing which specific variables (features) had the biggest influence on the algorithm's decision.

Recall

Out of all the real churners, how many did your model successfully catch? (Prioritizes missing as few churners as possible).

Precision

Out of everyone your model flagged as a churner, how many actually churned? (Prioritizes avoiding false alarms).