Contentsquare MCP

@Contentsquare show me the top 5 pages with the highest bounce rate in the last 7 days

Based on your Contentsquare workspace data, here are the five pages with the highest bounce rates over the past week: (1) /checkout/payment at 68.4%, (2) /product/category/shoes at 61.2%, (3) /account/register at 58.9%, (4) /blog/post-123 at 54.7%, and (5) /search/results at 52.3%. The checkout payment page shows a significant spike compared to your 30-day average of 42%. This example reflects typical analytics query patterns; actual metrics depend on your site's traffic and configuration.

This example assumes read access to session analytics and page performance metrics. OAuth2 scope must include analytics data. Contentsquare's API typically aggregates data with a delay (often 2-4 hours), so real-time queries may return incomplete results. Useful for identifying UX friction points quickly.

@Contentsquare create a zone analysis for the homepage hero section and flag any elements with click rates below 2%

Zone analysis created for your homepage hero section (zone ID: hero_20250124). Scanning 12 interactive elements: three buttons and one form field are underperforming. The 'Learn More' CTA shows a 1.4% click rate (expected ~5% for primary CTAs), the newsletter signup field has 0.8% engagement, and two secondary nav links are below 1.2%. The analysis will continue collecting data; check back in 24 hours for statistically significant trends. This illustrative output shows how zone-based heatmap data surfaces in a structured format.

Creating zone analyses may require workspace admin permissions and can consume API quota depending on traffic volume. Contentsquare processes heatmap data asynchronously, so immediate results are often preliminary. Best used when you need to instrument specific UI regions for A/B test prep or redesign validation.

@Contentsquare summarize the user journey for visitors who abandoned cart in the last 3 days, focusing on friction points

Analyzing 1,847 cart abandonment sessions from the past three days: 62% of users who abandoned reached the shipping address form but did not proceed. Common friction points include: (1) the address autocomplete failed to populate for international users (23% of abandonments), (2) average form completion time was 4.2 minutes vs. 1.8 minutes for successful checkouts, and (3) 18% of users rage-clicked the 'Continue' button, suggesting validation errors weren't clearly communicated. Session replays show confusion around the promo code field placement. This synthesis combines journey analytics with behavioral signals to highlight conversion blockers.

This example pairs Contentsquare's session replay and journey data with AI reasoning to identify patterns. Requires OAuth2 scopes for both analytics and session replay access. Journey analysis can be computationally expensive; large date ranges may hit rate limits. Most valuable when diagnosing specific conversion drop-offs rather than broad exploratory queries.

When session replay data needs to live in your AI workspace

A 5-person product team runs weekly conversion reviews, pulling Contentsquare heatmaps and session replays to diagnose why users abandon checkout. This MCP is the right call if your team already uses Contentsquare and wants AI to query session data without tab-switching—ask 'show me rage clicks on the payment page this week' and get answers in Switchy. The OAuth2 flow keeps credentials out of shared prompts. The trade-off: if your team only checks analytics monthly, the integration overhead isn't worth it—just screenshare the Contentsquare dashboard. If you're triaging user behavior daily and want AI to surface patterns across sessions, this MCP closes the loop between your analytics platform and your team's decision-making.

Connecting customer complaints to actual session behavior

A 3-person support team gets vague tickets like 'the form doesn't work' and needs to see what actually happened. This MCP lets you paste a user ID or timestamp into Switchy and pull the Contentsquare session replay without leaving the conversation. It's the right move if you're already paying for Contentsquare and your support flow involves constant back-and-forth between tickets and session data. The boundary: if your support volume is under 20 tickets a week, manually opening Contentsquare is faster than setting up OAuth and teaching the team a new workflow. If you're triaging 50+ tickets and half require session context, this MCP turns a 4-click lookup into a one-line AI query.

When UX research needs quantitative session evidence

A 4-person design team ships a new navigation layout and wants to validate that users actually find the features they moved. This MCP is useful if your team runs Contentsquare and needs to ask 'how many users clicked the old menu location vs. the new one in the last 48 hours' without waiting for a data analyst. The OAuth2 setup means designers can query session metrics directly in Switchy during design reviews. The limit: if your team only validates designs once per quarter, the integration is overkill—schedule a Contentsquare walkthrough instead. If you're iterating weekly and need session evidence to settle design debates in real time, this MCP makes behavioral data a first-class input to your design process.