> ## 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. # AI KPIs, Pivots, Measures > AI KPIs capture the results and performance of AI analysis across user sessions, errors, conversations, recommendations, and AI requests. KPIs `7 AI KPIs` Availability 2025.1 or later > **[KPIs](#kpi-catalog)** > > The 7 AI KPIs > **[Pivots](#pivots)** > > Slice the results > **[Measures](#measures)** > > Numerical values > **[Examples](#example-analyses)** > > Questions answered ## Overview GermainUX provides AI KPIs that capture the results and performance of AI analysis across **user sessions, errors, conversations, recommendations, and AI requests**. These KPIs make AI-generated insights available throughout GermainUX for dashboards, analysis, reporting, alerting, and automation. ### KPI Catalog | KPI | Description | | - | - | | **AI Error Analysis** | AI-generated summary analysis of **error** events. | | **AI Session Analysis** | AI-generated summary analysis of **user sessions.** | | **AI Session Friction** | AI-generated **friction** detected in a user session. | | **AI Session Recommendation** | AI-generated **recommendation** from a collection of **user sessions.** | | **AI Speed** | Measures the **time AI takes** from receiving a question until returning a response. | | **GermainUX AI Request** | Measures the duration of queries executed against GermainUX by AI. | | **AI Chat Friction** | AI-generated friction detected in a chat or conversation. | ## AI Error Analysis **AI Error Analysis** contains an AI-generated analysis of detected error events. Instead of reviewing individual error occurrences manually, AI can analyze the available error information and summarize what happened. **Use this KPI to:** * Quickly understand an error * Summarize error context * Identify patterns across error events * Support troubleshooting and root-cause investigation * Provide additional context for alerts and tickets A typical investigation can progress from: Error AI Error Analysis Affected Population Related KPIs Instances Likely Root Cause ## AI Session Analysis **AI Session Analysis** contains an AI-generated analysis of a recorded real user session. It summarizes significant activity within the session so teams can understand what happened without manually replaying the entire session. **Depending on the monitored data, the analysis can identify:** * User actions * Pages, screens, or features used * Business processes and workflows * Tasks completed or abandoned * Errors encountered * Application slowness * Repeated or inefficient actions * Other significant events When additional context is required, teams can open the associated **Session Replay** to see exactly what the user experienced. User Session AI Session Analysis Significant Events Session Replay ## AI Session Friction **AI Session Friction** contains friction identified by AI while analyzing a real user session. Detected friction can include conditions affecting: * Conversion * Adoption * Productivity * User Experience * Technology Examples can include confusing interactions, repeated actions, unsuccessful attempts, abandonment, errors, application slowness, or inefficient workflows. These friction KPIs make it possible to aggregate findings across sessions and determine which problems affect the largest populations. User Sessions AI Session Frictions Recurring Frictions Affected Population Analysis ## AI Session Recommendation **AI Session Recommendation** contains recommendations generated by AI from a collection of analyzed user sessions. Rather than focusing only on what happened in one session, this KPI can surface recommendations based on patterns observed across multiple sessions. **Recommendations can identify opportunities to improve:** * Conversion * Adoption * Productivity * User Experience * Business workflows * Application performance * Error resolution For example: Thousands of User Sessions AI Analysis Recurring Frictions AI Session Recommendations Prioritized Improvements This helps teams move from identifying individual issues to determining what should be improved across a broader user population. ## AI Chat Friction **AI Chat Friction** contains friction detected by AI within a monitored chat or conversation. AI can analyze conversations involving customers, employees, agents, or bots to identify interactions where the conversation may not be progressing successfully. Examples can include: * Customer questions not adequately answered * Repeated questions * Misunderstandings * Negative sentiment * Customer frustration * Unsuccessful bot responses * Agent or bot interactions that do not resolve the request * Other conversation friction When chat data is associated with a monitored user session, teams can investigate the surrounding user experience for additional context. Conversation AI Chat Friction User Session Session Replay Related Events Analysis ## AI Speed **AI Speed** measures the time required for GermainUX AI to process a question and return a response. This KPI provides visibility into the responsiveness of AI Speed itself. **Use it to monitor:** * AI response time * Changes in AI response performance * Slow AI interactions * AI Speed performance over time > [!NOTE] > > This KPI measures **AI service performance**, rather than an AI-generated business or user-experience insight. ## GermainUX AI Request **GermainUX AI Request** measures the duration of queries executed against GermainUX by AI. It provides visibility into the time required to retrieve and process GermainUX data used by AI capabilities. **Use this KPI to:** * Monitor AI query performance * Identify unusually slow requests * Analyze AI processing performance * Track request duration over time > [!NOTE] > > This KPI is primarily a **technology-performance KPI** supporting the monitoring and troubleshooting of GermainUX AI operations. ## Analyze AI Insights at Scale Because AI findings are stored as KPIs, GermainUX can analyze them individually or aggregate them across larger populations. For example: **1. 1,000 User Sessions** **2. AI Session Analysis** **3. AI Session Friction** **4. Identify Recurring Frictions** **5. Determine Affected Population** **6. AI Session Recommendations** **7. Prioritize Improvements** This allows teams to move from understanding **one user's experience** to identifying the most important issues and opportunities across thousands of users. ## From AI Insight to Evidence AI KPIs can be correlated with the underlying data collected by GermainUX, including user sessions, application activity, errors, transactions, performance, and other KPIs. A typical investigation can progress from: AI Insight Friction / Issue Affected Population Related KPIs Individual Instances Session Replay / Trace Likely Contributing Factors This allows teams to use AI to quickly identify what deserves attention while retaining access to the underlying evidence for further investigation. ## Pivots AI KPIs can be analyzed using pivots to understand where AI-generated insights, frictions, recommendations, or performance issues occur. Available pivots vary by KPI and can include:
Pivot Category Examples
**User** User Name, ID, Full Name, Department, Group, Role, Type, Location
**Application** Application Name, Component
**Session** Session ID, Business Object, Last Friction, Converted, Success
**Page** URL, Path, Query, Title
**Device** Device, Browser, Operating System
**System** System Name, Hostname, Type, Environment, Location
**Target** Target Name, Hostname, Type, Environment, Location
**HTTP** URL, Method, Path, Query, Status, Message
**Business** Business Levels 1–4
**Hierarchy** Hierarchy Levels 1–4
**Campaign** Campaign Name, Source, Medium, Term, Content
**Classification** Category, New Category
**Time** Year, Month, Day, Hour, Minute
For example: AI Session Friction Application User Session Session Replay can help identify which applications generate the most friction, which users are affected, and the individual sessions where the friction occurred. ### Pivots by AI KPI
KPI Key Available Pivots
**AI Error Analysis** System, Target, User, Device, Application, Page, HTTP, Hierarchy, Business, Campaign, Session, Category, Time
**AI Session Analysis** System, Target, User, Device, Application, Page, HTTP, Hierarchy, Business, Campaign, Session, Category, Time
**AI Session Friction** System, Target, User, Device, Application, Campaign, Session, Last Friction, Converted, Time
**AI Session Recommendation** Target, Application, Business Level, Category, Time
**AI Speed** System, Target, User, Device, Application, Page, Business, Session, Success, Last Friction, Converted, Time
**GermainUX AI Request** System, Target, User, Node, Engine, Source File, Source Trigger, Process/Thread, Category, Time
**AI Chat Friction** System, User, Device, Application, Session, Converted, Time
> [!NOTE] > > The exact pivots available depend on the AI KPI and monitored data. ## Measures Measures provide the numerical values available for analyzing AI KPIs. | KPI | Measures | | - | - | | **AI Error Analysis** | Value, Color Threshold | | **AI Session Analysis** | Value, Color Threshold | | **AI Session Friction** | — | | **AI Session Recommendation** | — | | **AI Speed** | Value, Duration (s), Color Threshold (s) | | **GermainUX AI Request** | Value | | **AI Chat Friction** | — | KPIs without a dedicated numerical measure can still be aggregated, counted, filtered, and analyzed using their available pivots. ## Example Analyses Combining AI KPIs with pivots and measures makes it possible to answer questions such as: | Question | KPI | Pivot / Measure | | - | - | - | | Which applications generate the most AI-detected friction? | AI Session Friction | Application | | Which users experience recurring friction? | AI Session Friction | User | | Is session friction associated with conversion? | AI Session Friction | Converted | | What are the most common AI-analyzed errors? | AI Error Analysis | Category | | Which applications are associated with errors? | AI Error Analysis | Application | | What recommendations are generated across sessions? | AI Session Recommendation | Application / Business Level | | Where is AI detecting chat friction? | AI Chat Friction | Application | | Is chat friction associated with conversion? | AI Chat Friction | Converted | | How long does AI Speed take to respond? | AI Speed | Duration | | How does AI Speed performance change over time? | AI Speed | Duration + Time | | How long do AI queries against GermainUX take? | GermainUX AI Request | Value + Time | These combinations allow teams to move beyond an individual AI result and determine **what is happening, where it is happening, who is affected, how frequently it occurs, and how it changes over time**. ## Additional Resources > **[AI Management](https://docs.germainux.com/main/ai-settings.md)** > > AI Features Management > **[AI Advice](https://docs.germainux.com/main/ai-advice-dashboard.md)** > > AI Advice Dashboard > **[AI Summary](https://docs.germainux.com/main/user-monitoring-and-replay.md)** > > AI Summary for Real User Session > **[Frictions](https://docs.germainux.com/main/frictions-dashboard.md)** > > Frictions Dashboard > **[Analytics](https://docs.germainux.com/main/analytics.md)** > > More Analytics Features > **[Automation](https://docs.germainux.com/main/automation.md)** > > More Automation Features > **[Dashboard](https://docs.germainux.com/main/dashboard-and-report.md)** > > Dashboards and Reports > **[Reports](https://docs.germainux.com/main/reporting-automatic.md)** > > Reports (Automatic, Scheduled) > **[Management](https://docs.germainux.com/main/management.md)** > > Management Features ## Get Help > **[Contact GermainUX Support](https://docs.germainux.com/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. The content of this document is proprietary to GERMAIN SOFTWARE. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.