The Pivot Table lets you cross two segmentation labels to measure and compare search volume across all their combinations. Rather than analyzing one label at a time, it reveals where demand is actually concentrated at the intersection of two dimensions — giving you a more nuanced read of your market structure.
Data-Visualization & Widgets
1. How to set up your Pivot Table
a) To build your table, start by selecting what you want to display in columns. This is usually the first label you want to analyze, such as a topic, a brand, or a category, ect.
b) Then, choose what you want to display in rows. This is the second label you want to compare against, such as a topic, a brand, or a category, etc.
Once both labels are selected, the Pivot Table automatically calculates the values inside the table so you can compare search weight across all combinations.
You can toggle between Search Volume and Share of Volume depending on whether you want to assess raw demand or relative weight across your dataset.
2. Cross-label table
The table displays the search volume or share of volume for every intersection between your two selected labels. Color gradients make it immediately easy to identify which combinations concentrate the most demand and which remain marginal.
What you get out of it:
Identify the label combinations that drive the most search volume
Understand how demand is distributed across your segmentation dimensions
Spot white spaces — combinations with little or no search activity
Compare the relative weight of each combination with the share of volume view
3. Monthly Volume Bar Chart
Below the table, the bar chart shows the monthly evolution of total search volume for the selected pivot, giving you a temporal dimension to complement the structural view of the table.
What you get out of it:
Track how overall interest in a label evolves month over month
Identify seasonal patterns or inflection points in search demand
Contextualize the table values within a broader time horizon
4. Making Strategic Decisions with Pivot Table
By crossing two labels, you can move beyond isolated analysis and understand where demand is truly concentrated:
Prioritize high-volume combinations to focus SEO, content, and campaign efforts where they will have the most impact
Identify underserved intersections that represent untapped opportunities
Avoid spreading resources across label combinations with low search weight
Use the share of volume view to benchmark combinations against each other regardless of absolute volume differences