How This Workflow Works
This workflow creates a KNIME Data App for analyzing customer and transaction data. It brings together demographic, transactional, and store information, allowing users to filter by geography and time, and then visualize key sales metrics and customer behaviors.
Key Features:
- Combine multiple data sources for a unified view of sales and customer activity
- Enable dynamic filtering by date, geography, and customer attributes
- Visualize customer segments and transaction patterns with interactive charts
- Support user-driven exploration through a Data App
Step-by-step:
1. Aggregate and Enrich Customer and Transaction Data:
The workflow merges customer demographics, transaction records, and store details into a single dataset. It extracts relevant time periods (such as years, quarters, and months) and prepares the data for analysis, ensuring that each transaction is linked to the correct customer and location.
2. Enable Interactive Filtering and User Input:
Users can filter the data by selecting specific date ranges, cities, or customer groups. The Data App responds to these inputs in real time, updating the underlying data and visualizations to reflect the selected criteria.
3. Analyze and Segment Customer Behaviors:
The workflow groups customers based on their transaction frequency, basket size, and total spending. It calculates summary statistics for each segment, making it easier to identify high-value customers and understand different purchasing patterns.
4. Visualize and Share Insights:
The Data App presents key metrics and trends through interactive charts, including scatter plots for basket size versus spending, bar charts for customer group frequency, and parallel coordinates plots for spending behavior. Users can highlight data points of interest and review detailed tables of customers and transactions for further exploration.