The Hidden Customer Segment Discovery Engine

 Build an interactive analytics application that discovers overlooked customer segments from ordinary business transaction and interaction data.

Allow users to upload CSV files containing purchase history, product categories, order frequency, customer feedback, acquisition channels, and transaction values.

Create a discovery engine that:

• Identifies behavioral groups without requiring users to define segments in advance.

• Explains which observable characteristics distinguish each group.

• Highlights customers whose behavior does not fit existing segments.

• Compares segment profitability, repeat-purchase rates, and product preferences when the required data exists.

• Generates evidence-backed hypotheses for why each segment behaves differently.

• Simulates how a pricing change, product bundle, or retention offer might affect different segments.

• Creates an actionable experiment for validating each discovery.

Include interactive visualizations, segment filters, editable segment names, and exportable reports. Clearly separate statistical groupings from causal explanations. Do not infer sensitive personal attributes or fabricate missing metrics. Provide a sample dataset and explain the assumptions behind every calculated score.