Icon

JKI4_​008_​Airline_​Customer_​Loyalty

<p><strong>Challenge 8: Airline Customer Loyalty</strong></p><p><strong>Level:</strong> Easy<br><br><strong>Description:&nbsp;</strong>You work for a Canadian airline company that wants to better understand its most loyal customers. Before creating personalized offerings for this group, the company needs to uncover their demographics from the available data. As a data scientist, your task is to identify how these loyal customers are distributed across different demographic segments—such as gender and marital status—in each city. Who are the most loyal customers and how are they segmented in different locations? <strong>Hint 1:</strong> You can use loyalty points for calculating a basic loyalty score or combine multiple factors to create a more comprehensive one.<br><br><em>Beginner-friendly objectives:</em> 1. Calculate Loyalty for each user; 2. Extract the most loyal users along with their information; 3. Find out how these customers are distributed in different demographic groups in each city.</p>

URL: Airline Customer and Loyalty Data in KNIME Community Hub https://hub.knime.com/just%20knime%20it/spaces/Solutions/Season%204/Challenge%208/Challenge%208%20-%20Datasets~jLpQGLFlcQmosaK5/
URL: Vibe Codingの設計パターン検討[AIとやってみた(Perplexity)] https://zenn.dev/space_k/articles/20250416-vibecoding
URL: Vibe Coding(バイブコーディング)完全ガイド https://triggermind.com/ai-basic/vibe-coding-guide/

Nodes

Extensions

Links