With the Chart Builder tool, you can easily create and customize multiple chart types:
Scorecards
Donut charts
Horizontal bar graphscharts
Vertical bar graphscharts
Available in Tools > Chart Builder, this feature lets you adjust:
Chart type
Colors
Legends
Metrics and dimensions
Customize your chart
ScoreCard
The Scorecard is ideal for highlighting a single metric and tracking it over time.
To configure it, you can rely on
filters: focus the metric on specific page groups or conditionsMetric, either:
Count of pages based on your filter, or
An aggregated metric from the dataset
Color: choose the color you want based on the color picker.
Trend line: Display historical trends. We recommeand to keeping this option visible.
Donut chart
The donut chart shares many of the same settings of the Scorecard but adds:
Dimension: segment your data by a specific attribute (using OQL filters if needed)
Example: Group pages by depth, status code, or any custom field.
Bar graphs (horizontal or vertical)
Bar graphs allow for deeper analysis with:
Breakdown dimension — add a second layer to compare groups within groups (e.g: depth by status code)
Scales, choose between:
Linear scale — constant intervals (1, 2, 3…)
Logarithmic scale — exponential steps (1, 10, 100…)
Use the scale that best fits your data distribution.
Concrete use cases - Unlock more value from Custom Fields or Data Ingest
“As an e-commerce site, I want to build a chart showing how many Product Listing Pages display zero products.”
For this concrete example:
I create a scraping rule named:
PLP_productsNBto capture the number of products per page during the crawl.After the crawl, the Data Explorer returns the product count for each PLP.
In the Chart Builder, create a Scorecard to monitor PLPs with zero products.
Use a Product Listing segmentation
Apply an OQL filter: pages where PLP_productsNB = 0
Oncrawl displays a scorecard result — for example: “17 product listing pages display zero products.”
“As a user, I want a quick breakdown of which page groups rank and generate clicks on the SERP.”
To achieve this:
Use the GSC connector to import click data from Google SERPs.
Apply a Segmentation based on URL patterns to group pages logically.
In Chart Builder, create a bar chart showing clicks per group.
The result? A visual breakdown highlighting the top-performing page groups in
terms of search traffic.
