Key Driver Analysis Skill

This skill helps you understand why a metric changed between two time periods. It identifies which dimensions (regions, products, categories, segments) contributed most to revenue growth, sales drops, or other period-over-period changes.

How It Works

The Key Driver Analysis skill compares metric values between two time periods and identifies which dimensions contributed most to the change. When activated, the assistant:

  1. Identifies the metric and two time periods to compare
  2. Creates a Key Driver Analysis specification
  3. Executes the analysis to calculate contributions from each dimension
  4. Identifies the top contributors (positive and negative)
  5. With data sharing enabled, provides natural language explanations of what drove the change

The skill helps you understand not just that a metric changed, but specifically which dimensions (regions, products, customer segments, etc.) were responsible for the change, enabling targeted action.

Data Sharing

The Key Driver Analysis skill always respects the AI Assistant data sharing setting. When data sharing is disabled, the assistant can help create the Key Driver Analysis specification, but it cannot execute the analysis or calculate the contributing dimensions from chat.

Examples

Understanding Revenue Growth The user asks: Why did revenue increase from Q1 to Q2? The AI Assistant then:

  • compares the two periods,
  • identifies the biggest contributing regions or products, and
  • summarizes the key drivers behind the change.

Analyzing a Sales Drop The user asks: What caused the sales drop this month compared to last month? The AI Assistant then:

  • runs a period comparison,
  • highlights negative contributors, and
  • explains what changed.

Identifying Growth Drivers The user asks: Which regions contributed most to the growth? The AI Assistant then:

  • runs a period comparison,
  • ranks regions by contribution to the period change, and
  • visualizes the results.

More Example Prompts

  • What products drove the revenue increase?
  • Compare this quarter to last quarter and show what changed.
  • What dimensions explain the difference between these two periods?

Limitations

  • Requires two distinct time periods for comparison
  • Analysis focuses on dimensional contributions, not external factors
  • Results interpretation requires data sharing to be enabled (when disabled, provides visualization only)
  • Works best when dimensions have sufficient data in both periods

This is an experimental feature that is still under active development. Its behavior may change in future releases.

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