Understand and attribute KPI change between two periods
What % of the KPI change is due to category weight mix vs. rate change?
This tool isolates the impact of within-category performance (rate) and category composition (weight) on your KPI.
Select the structure of your KPI
Weighted average across categories (e.g., conversion rate, AOV)
Conversion Rate = Orders / Visits
Sum of products across categories (e.g., revenue, total sales)
Num of Orders × Avg Order Amount (Σ(Count × Mean))
Multiplicative funnel with steps (counts only)
Entry → Clicks → Conversions → Revenue
Define your metric and analysis dimensions
Enter numerator and denominator values for each country
| Country | Period A | Period B | Derived Values | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
Numerator (e.g., number of orders) | Denominator (e.g., number of visits) | Numerator (e.g., number of orders) | Denominator (e.g., number of visits) | Conversion Rate (Period A) | Conversion Rate (Period B) | Share (Period A) | Share (Period B) | Conversion Rate (Overall) | ||
| 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | ||||||
| Totals | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 1.00 | 1.00 | 0.0000 | |