The most valuable analytics questions are often the most specific.
Which pages keep users engaged but fail to convert? Where are mobile visitors encountering friction? Which behavioral signals tend to appear together before someone abandons a page?
Traditionally, answering questions like these meant stitching together exports, filters, and reports. With the Clarity MCP Server, you can pull behavioral data into AI tools and generate customized, insight-rich outputs in a fraction of the time.
In this post, we’ll explore five advanced queries that demonstrate the true power of Clarity’s MCP server, helping you go beyond basic metrics to actionable insights.
1. Pages with High Scroll Depth but Low Conversions
Why it matters: A page that keeps users scrolling but doesn’t convert can indicate misaligned calls-to-action or confusing design.
MCP prompt example:
Show me pages with average scroll depth above 75% but conversion rate below 5% for the last 30 days.
Mock output:
| Page URL | Avg. Scroll Depth | Conversion Rate |
| /blog/advanced-analytics | 82% | 3.2% |
| /signup/form-optimization | 78% | 2.8% |
| /product/features-overview | 80% | 4.5% |
Insight: You might have compelling content that engages users, but your calls to action aren’t strong or visible enough. Consider repositioning buttons, simplifying forms, or experimenting with more persuasive copy.
2. Sessions with Multiple Negative Engagement Signals
Why it matters: Single metrics only tell part of the story. Combining behavioral signals like rage clicks, excessive scrolling, and quick backs can reveal hidden UX friction.
MCP prompt example:
List sessions where users exhibited rage clicks AND excessive scrolling AND quick backs in the last 7 days.
Mock output:
| Session ID | Page URL | Rage Clicks | Excessive Scrolls | Quick Backs |
| 1427 | /checkout/cart-review | 6 | 4 | 3 |
| 1589 | /signup/form-optimization | 5 | 5 | 2 |
Insight: These sessions highlight where users are frustrated. The checkout page might have unclear instructions, while the signup form could use fewer fields or more inline guidance.
3. Segment Engagement Across Multiple Dimensions
Why it matters: Engagement patterns differ by device, location, and traffic source. Understanding these differences can reveal optimization opportunities.
MCP prompt example:
Show average engagement time for mobile users from organic search in North America vs Europe, broken down by browser.
Mock output:
| Region | Device | Browser | Active time spent (minutes) |
| North America | Mobile | Chrome | 3.5 |
| North America | Mobile | Safari | 4.1 |
| Europe | Mobile | Chrome | 2.8 |
| Europe | Mobile | Safari | 3.0 |
Insight: Mobile users in Europe are less engaged, particularly on Chrome. A responsive design review or content adjustments could improve experience and retention.
4. Identify Pages with Rising or Falling Engagement Trends
Why it matters: Tracking changes over time highlights content or feature performance that static metrics can’t capture.
MCP prompt example:
List pages where average session duration changed by more than 20% over the past month compared to the previous month.
Mock output:
| Page URL | Trend % |
| /blog/ai-insights | +25% |
| /product/pricing | -22% |
| /signup/form-optimization | -30% |
Insight: Rising trends indicate successful optimizations or growing user interest, while falling trends flag areas needing attention. For example, the pricing page may need clearer value propositions or a simplified layout.
5. Combine Session Recordings with Metrics for Deep Insights
Why it matters: Metrics alone don’t always tell you why users act in a certain way. Linking session recordings to quantitative signals uncovers the story behind the numbers.
MCP prompt example:
Fetch session recordings for pages with low scroll depth and high exit rate last week.
Mock output:
| Session ID | Page URL | Scroll Depth | Exit Rate |
| 2135 | /pricing/enterprise | 28% | 87% |
| 2178 | /signup/form-optimization | 25% | 91% |
Insight: Viewing these sessions shows exactly where users drop off or get confused. This insight lets teams redesign forms, restructure content, or improve navigation to retain users.
Tips for Writing Your Own Advanced Queries
MCP queries are most effective when they are structured, intentional, and focused. Following a few guiding principles will help you uncover deeper insights without overcomplicating your workflow:
- Combine multiple metrics to surface patterns and anomalies that single metrics alone might miss.
- Segment across dimensions such as device, browser, location, or traffic source to reveal hidden differences.
- Incorporate time-series comparisons to detect trends, improvements, or declines over time.
- Filter sessions by behavioral triggers to focus on high-priority areas for UX or performance optimization.
- Use clear and specific language in your prompts to ensure accurate results.
- Document and reuse queries to streamline workflows and maintain consistency across teams.
- Visualize outputs to make insights easier to interpret and act on quickly.
Conclusion
Interested in trying these queries with your own data? The Microsoft Clarity MCP Server makes it easy to pull analytics into AI tools and generate customized insights in minutes.
To get started, check out our step-by-step guide.