Conditional Calculations
Perform different calculations based on conditions within your data.| Calculation Type | Description | Examples |
|---|---|---|
| Conditional Aggregation | Count or sum only items meeting certain criteria. Enables segment-specific metrics without pre-filtering. | • “Count orders where status is ‘completed’” • “Sum revenue only for repeat customers” • “Average handling time for priority cases versus normal cases” • “Show total revenue, enterprise revenue, and SMB revenue by month” |
| Case-Based Logic | Create categories or calculated fields based on conditions. Derived categories can be used for grouping and analysis just like original columns. | • “Categorize customers as ‘high’, ‘medium’, or ‘low’ based on their total spend” • “Flag orders as ‘large’ if over $1000” |
Derived Tables & Reuse
Save analysis results as queryable datasets for further analysis:- “Save this result as a new table”
Analysis Patterns
Common analytical patterns across different domains:| Domain | Example Patterns |
|---|---|
| Customer Analysis | • “Calculate customer lifetime value as total revenue per customer” • “Segment customers by purchase frequency” • “Average time between purchases for repeat customers” |
| Sales Analysis | • “Show win rate by salesperson” • “Average deal size by segment” • “Pipeline coverage over the past 6 months” |
| Product Analysis | • “Rank products by revenue contribution” • “Attach rate of Product B when Product A is purchased” • “Revenue concentration—how many products generate 80% of revenue” |
| Operational Analysis | • “Average processing time by request type” • “Cases exceeded SLA by how much” • “Identify bottlenecks—which step has the longest average duration” |