Merge pull request RasaHQ#11670 from RasaHQ/metrics-table

Added metrics table and categories

docs/docs/monitoring/analytics/example-queries.mdx

@@ -7,9 +7,11 @@ description:
 
 import useBaseUrl from "@docusaurus/useBaseUrl";
 
-This section helps you to started with ways how to analyze
-the conversations your assistant has. The examples use SQL queries
-together with an example visualization in Metabase.
+This section helps you get started with analyzing your assistant's conversations. 
+The examples use SQL queries together with an example visualization in Metabase.
+
+For more metrics and categories of conversations,
+see [Types of metrics](./getting-started-with-analytics#types-of-metrics).
 
 
 <!--

docs/docs/monitoring/analytics/getting-started-with-analytics.mdx

@@ -61,6 +61,41 @@ The pipeline will compute analytics as soon as the docker container
 is successfully deployed and connected to your data warehouse and
 Kafka instances.
 
+## Types of metrics
+
+Metrics collected from your assistant can broadly be categorized as
+
+- User Analytics: Who are the users of the assistant, and how do they feel 
+about it?  Examples: demographics, channels, sentiment analysis
+- Usage Analytics:  How is the assistant’s overall health and what kind of 
+traffic is coming to it?  Examples:  total number of sessions, time per 
+session, errors and error rates
+- Conversation Analytics: What happened during the conversation?  
+Examples: number of messages sent, abandonment depth, number of topics 
+introduced by user, top N intents
+- Business Analytics: How is the assistant performing with regard to business goals?
+Examples: ROI of assistant per LoB, time comparison of assistant vs agent, containment rate
+
+In this version of the Analytics pipeline, measurement of the following metrics 
+is possible 
+
+| Metric | Category | Meaning |
+|--------|----------|---------|
+| Number of conversations| Usage Analytics | Total number of conversations |
+| Number of users | Usage Analytics | Total number of users | 
+| Number of sessions | Usage Analytics | Gross traffic to assistant |
+| Channels used | Usage Analytics | Sessions by channel | 
+| User session count | User Analytics | Total number of user sessions or average sessions per user |
+| Top N intents | Conversation Analytics | Top intents across all users | 
+| Avg response time | Conversation Analytics | Average response time for assistant | 
+| Containment rate | Business Analytics | % of conversations handled purely by assistant (not handed to human agent |
+| Abandonment rate | Business Analytics | % of abandoned conversations |
+| Escalation rate | Business Analytics | % of conversations escalated to human agent | 
+
+
+For examples of how you can extract these metrics, 
+see [Example queries](./example-queries).
+
 ## Prerequisites
 
 - A production deployment of Kafka is required to set up Rasa Pro.