Page Analysis in Noibu shows user behaviour, technical issues, and performance indicators at a granular, page-by-page level. Like Digital Experience Analytics (DXA) tools, it helps product and UX teams evaluate the user experience after launching a new page or making iterative changes to existing pages.
By unifying session-based click and scroll data, technical issues, and performance monitoring metrics in a single view, teams gain a comprehensive understanding of how each page performs and where there may be opportunities to improve the user experience.
| Note: this feature is currently in beta. Beta features are still in development as we test and evaluate. They may have limited functionality and can change without notice. |
Choosing a page for analysis
Begin analyzing a page by selecting or inputting a specific URL. Noibu pre-populates your highest-traffic pages for quick access, but any valid site URL can be analyzed. Filter controls allow segmentation by device type (desktop or mobile) and time range (last 7, 14, or 30 days). Custom date ranges are also supported.
After selecting a page, the Customer Behaviour, Issues, and Performance tabs will populate with data from the period of time selected.
Customer Behaviour tab
This tab helps teams understand user interaction patterns with visual heatmaps of where users click and how deep they scroll on a page. It includes two core components: Click Maps and Scroll Maps.
Unlike other analytics tools that use synthetic or placeholder layouts, Noibu’s visualizations are based on reconstructed snapshots derived directly from a representative user session within the selected timeframe. This ensures the snapshot contains real content, styling, and elements as rendered in the user’s browsers.
Note: this snapshot only reflects visible elements on the page from the representative session. Elements that require user interaction to occur, like dropdown menus, carousels, or slide-outs, may not display unless they were open during the session used for the snapshot.
Click Maps
Click Maps display an interactive reconstruction of the page, overlaid with a color gradient that visualizes the frequency of user clicks. They are useful for evaluating the effectiveness of CTAs, image placements, and page elements, and for validating if interaction patterns change following content updates.
At the top of the click map, you’ll see in indicator of the total number of clicks and pageviews logged by Noibu that make up the data for the selected period of time
A colour scale indicates the frequency of clicks on elements on the page. Red denotes areas with high interaction; blue indicates low engagement. Hovering over any element reveals the percentage of total clicks during the selected timeframe and device type.
Scroll Maps
Scroll Maps present the depth at which users engaged with the page. They help assess content visibility and can inform layout adjustments to surface high-value content higher on the page.
Similar to Click Maps, colour gradients represent scroll depth engagement. Red indicates a high proportion of users scrolled to the given page depth; blue indicates fewer users reached that page depth. Hovering over the scroll map will display a tooltip indicating scroll depth as a percent of page height) and the proportion of users who reached that depth.
Note that due to variations in browser dimensions and responsive design, scroll data is estimated across normalized viewport measurements. This allows Noibu to aggregate data across sessions while minimizing distortion.
Issues tab
The Issues tab provides a view of technical errors over time specific to the selected page, which can be particularly helpful when investigating user-reported issues tied to specific page URLs.
A time-series chart illustrates error occurrences by day, allowing users to identify trends or sudden spikes in issue volume. If enabled, release events will be indicated along the horizontal axis of this chart via a </> icon. Clicking the icon will show you a preview of release events that occurred on that date, allowing you to investigate further.
Clicking and dragging on this chart allows you to narrow down the data to a custom date range
Below the chart is a detailed list of issues affecting the selected URL, segmented by:
- Priority Issues: issues categorized by Noibu as Priority Issues
- Spiking Issues: important issues with a >20% spike in occurrences compared to the previous time period
- Frequent Issues: all issues affecting the page, sorted by Conversion Impact and frequency of occurrence
Clicking on any issue in this table will open its corresponding Issue Details in a new tab – including impacted sessions, error metadata, and stack traces.
Performance tab
The Performance tab shows Core Web Vitals—Loading Speed (LCP), Interactivity (INP), and Visual Stability (CLS)—for the selected page:
- Loading Speed (LCP): measures the load time of the largest visible content element on the page.
- Interactivity (INP): tracks how quickly the page responds to user interactions.
- Visual Stability (CLS): captures how stable the layout is during load.
Each metric is displayed in an individual time-series chart for the selected time period, compared against Google’s and Noibu’s benchmarks. Learn more about performance monitoring metrics.
If enabled, release events will be indicated along the horizontal axis of this chart via a </> icon. Clicking the icon will show you a preview of release events that occurred on that date, allowing you to investigate further.
Clicking and dragging on any chart allows you to narrow down the data to a custom date range.
Analyzing for conversion insights
By individually analyzing pages that have been recently launched or updated, you can glean insights that can inform UX decisions and technical improvements to optimize conversions. Types of questions that can be answered with Page Analysis include:
Are people scrolling far enough to see the important content?
- Example: The “Find My Store” button is among the most clicked elements on a Product Detail Page (PDP), but it’s located low on the page.
- Insight: Moving the button higher may improve accessibility and drive faster customer decision-making.
Are users engaging with key elements placed in highly visible locations?
- Example: A "Collections" link occupies prime space in the main navigation but receives very few clicks.
- Insight: Users may not expect to find Collections there. Consider relocating the link to reduce clutter and focus attention on higher-value actions.
Are campaign landing pages driving the right actions?
- Example: Users land on a marketing campaign page but often click the top navigation, moving away to the main site instead of converting on the landing page.
- Insight: Consider simplifying or hiding the main site navigation on marketing landing pages to keep users focused on the intended CTA.
Additionally, opening two browser tabs with the Customer Behaviour set to different time ranges (e.g. before and after a conversion drop) can yield insights into how customer behaviour has changed.
For example, comparing click maps across different date ranges can help you understand if the total number of interactions scaled with traffic, and whether click distribution patterns shifted. Similarly, differences in scroll depth across different date ranges may help uncover layout issues or content fatigue. This kind of side-by-side comparison can be invaluable for diagnosing changes in customer behaviour related to recent feature releases, marketing launches, or UX updates.