> ## Documentation Index > Fetch the complete documentation index at: https://docs.germainux.com/llms.txt > Use this file to discover all available pages before exploring further. # Root-Cause Analysis > GermainUX Root-Cause Analysis helps teams move from what happened to why it happened, using user, workflow, application, and technology data. Service `Analytics` `Automation` Availability 2014.1 or later > **[Analysis Dashboard](#analysis-dashboard)** > > Single view for investigation > **[User & Session Evidence](#user-&-session-evidence)** > > Who was affected and when > **[Analyze Impact at Scale](#analyze-impact-at-scale)** > > Measure how widely issues spread > **[From Detection to Resolution](#from-detection-to-resolution)** > > Linking findings to follow-up actions ## GermainUX Root-Cause Analysis: Investigating User Experience and Technology Impact ## Overview GermainUX Root-Cause Analysis helps teams move from **what happened** to **why it happened**, using the user, business workflow, application, and technology data collected and correlated by GermainUX. Root-Cause Analysis can be used to investigate issues affecting: | Area | Details | | - | - | | **Conversion** | checkout failures, abandonment, errors, slow interactions, and other factors affecting conversion. | | **Adoption** | application usage, feature usage, workflow completion, and friction affecting adoption. | | **Productivity** | slow or failed workflows, delays, repetitive actions, and application issues affecting users. | | **Experience** | errors, slow interactions, user friction, feedback, and individual user sessions. | | **Technology** | application errors, transactions, APIs, services, databases, code execution, infrastructure, and integrations. | The objective is to connect a KPI or issue with the evidence available in GermainUX and identify the most likely contributing factors or root cause. ## Analysis Dashboard The **Analysis Dashboard** is GermainUX's primary interface for root-cause investigation. It brings the investigation—from a business or technical symptom to supporting evidence—into a single analytical workflow. From an Aggregate, Pivot, or Drill-through Dashboard, users can drill into the Analysis Dashboard to investigate a selected KPI or data point. The Analysis Dashboard helps answer: 1. **Is this abnormal?** \ Compare the selected KPI with its baseline, historical behavior, trends, and available statistical information. 2. **What changed with it?** \ Identify related KPIs that changed during the same period. 3. **What is most strongly related?** \ Analyze configured KPI relationships to identify signals that may help explain the selected KPI's behavior. 4. **Who or what is most affected?** \ Break down the issue by available dimensions such as users, sessions, applications, pages, workflows, products, systems, versions, or other monitored attributes. 5. **Is it isolated or widespread?** \ Determine whether the issue affects an individual instance, session, user, population, or the broader monitored environment. 6. **What happened in an individual instance?** \ Drill into the underlying event, error, transaction, request, session, or other raw data. 7. **What contributed to it?** \ Examine available traces, relationships, duration breakdowns, errors, requests, services, queries, code execution, infrastructure conditions, or Session Replay evidence. The exact analysis and evidence available depend on the KPI, monitored technology, deployed GermainUX components, and data being collected. The **new** dashboard is available with GermainUX 2026.2 or later. ## Correlation & Relationships GermainUX correlates monitored data to help identify relationships between user activity, workflows, applications, and technologies. Correlation can use: * **Exact-match correlation** * **ID-based correlation** * **Stream correlation** * **Configured KPI relationships** For example, a slow user interaction may be correlated with the browser request, backend transaction, service call, database query, or other monitored activity associated with that interaction. KPI Relationships provide additional analytical context by defining relationships between KPIs. The Analysis Dashboard can evaluate these relationships to identify signals that may help explain changes in the KPI being investigated. Learn more about [Correlation](/main/correlation-and-tracing.md) and [relationships](/main/kpi-relationships.md) which can provide evidence for root-cause investigation; a relationship or correlation does not necessarily prove causation. ## User & Session Evidence When User Monitoring is deployed, GermainUX can connect an issue to the user experience in which it occurred. Depending on the deployed monitoring capabilities, investigators can examine: * User * Session * Page or application * User actions * Errors * Network activity > **Show all 9** > > * Transactions > * Business-process activity > * Session Replay **Session Replay** can be used to see what the user was doing and experiencing before, during, and after an issue. This provides additional context when investigating errors, failed transactions, workflow friction, slow interactions, conversion issues, or customer feedback. \ \ Learn more about [Session Replay](/main/user-monitoring-and-replay.md). ## Business Workflow Analysis For configured business processes, GermainUX can analyze the workflow in which an issue occurred. Depending on the configured process and available data, teams can investigate: * Workflow duration * Process steps * Delays and bottlenecks * Failed steps * Drop-offs * Repeated actions * Workflow completion * Related user or technology events This helps determine whether a productivity, adoption, or conversion issue is associated with a particular workflow step or underlying application or technology condition. Learn more about [Process Mining](/main/business-process-workflow-monitoring.md). ## Technology Root-Cause Analysis GermainUX can correlate technology performance with user and business impact. Depending on the monitored technology and deployed components, investigation evidence can include: * Application errors and exceptions * Browser and HTTP activity * Application transactions * APIs and web services * Distributed or correlated transactions * Application services > **Show all 10** > > * Database activity and SQL > * Code execution > * Infrastructure and system metrics > * Integration activity For [supported technologies](/main/monitoring.md), this allows teams to trace an issue across multiple application layers rather than investigating each layer independently. ## Analyze Impact at Scale Root-cause investigation is not limited to an occurrence. GermainUX can use data to determine how broadly an issue is occurring and which populations are most affected. For example: Issue Related Factors Affected Population Individual Instances Supporting Evidence This helps teams distinguish an isolated occurrence from an issue affecting many users, sessions, workflows, transactions, or systems. \ \ Scheduled [AI summaries](/main/ai-driven-insights.md) for bulk user sessions are available to provide a consistent assessment of the top 10 issues. ## AI-Assisted Analysis Where AI capabilities are enabled, GermainUX can assist the investigation by analyzing available monitored data and providing additional insights and recommendations. AI can help users explore an issue, understand available evidence, identify relevant patterns, and obtain recommendations for resolving or improving the condition being investigated. [AI-generated analysis](/main/ai-driven-insights.md) should be considered together with the underlying evidence available in GermainUX. ## From Detection to Resolution Root-Cause Analysis is part of the broader GermainUX operational workflow: Observe Analyze Prioritize Act Validate For example: **KPI degradation detected** \ → Analyze abnormal behavior \ → Identify related KPIs \ → Determine affected users or population \ → Inspect individual instances \ → Trace related activity \ → Review Session Replay or technical evidence \ → Identify likely root cause \ → Take corrective action \ → Validate that the KPI and affected experience have recovered Depending on the configured GermainUX Automation capabilities, findings can also be connected to alerts, tickets, notifications, scripts, APIs, or other approved automated actions. ## Related Documentation | Document | Description | | - | - | | **Dashboard** | Investigate KPIs, relationships, affected populations, individual instances, and traces. | | **Dashboards** | Aggregate, Pivot, Drill-through, and Analysis dashboards. | | **[Correlation](/main/correlation-and-tracing.md)& Tracing** | Configure and use correlation across monitored data. | | **KPI[Relationships](/main/kpi-relationships.md)** | Define relationships used during analysis. | | **User Monitoring &[Session Replay](/main/user-monitoring-and-replay.md)** | Investigate the user experience associated with an issue. | | **Session Replay[Player](/main/session-replay-player.md)** | Review detailed user-session evidence. | | **Business Process & Workflow[Mining](/main/business-process-workflow-monitoring.md)** | Investigate workflow behavior and performance. | | **Technology[KPIs](/main/kpis.md), Pivots & Measures** | Analyze application and technology performance. | | [Automation](/main/automation.md) | Turn detected conditions and analytical findings into operational actions. | Root-Cause Analysis capabilities depend on the monitored technology and deployed GermainUX components. ## Get Help > **[Contact GermainUX Support](/main/support.md)** > > The Germain Team can help you set this up. > **Can't find what you need?** > > Search all GermainUX docs with **Ctrl + K**, or use the feedback buttons at the bottom of this page to tell us what is missing. 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