Dashboard (Analytics)

The Dashboard is the analytics and metrics page of your project (workspace). It provides an overview of the platform's performance and usage, allowing you to monitor activities, interactions, and important metrics of your workspace.

Overview

The Dashboard displays real-time graphs and metrics that help you understand:

• Platform Usage: How many users are active and how they interact with the platform.
• Assistant Activity: How the assistants are being utilized.
• Time Metrics: Trends over time with different analysis periods.
• Temporal Analysis: Visualization of data in time series to identify patterns.

Accessing the Dashboard

To access the Dashboard:

1. Navigate to the Projects section in the side menu.
2. Select the desired project.
3. Click on Dashboard in the project’s side menu.

Dashboard Components

The Dashboard consists of several cards and graphs that display different metrics. Each graph is interactive and allows you to explore the data over different time periods.

Period Filters

Each graph has period filter buttons that allow you to view the data over different time intervals:

• 30 Days: Views data from the last 30 days.
• 6 Months: Views data from the last 6 months.

The period filters allow you to adjust the granularity of the displayed data. Shorter periods (30 days) show more detail, while longer periods (6 months) show long-term trends.

Active Users Metrics (DAU, WAU, MAU)

The Dashboard displays active users metrics that are calculated based on login events on the platform. These metrics help understand user engagement:

DAU (Daily Active Users)

• What it is: The number of unique users who accessed the platform on a specific day.
• How it is calculated: Counts unique users who logged in within a 24-hour period.
• Purpose: Helps understand daily engagement and identify activity peaks.
• Interpretation: High values indicate good daily adherence; increasing values indicate growing usage.

WAU (Weekly Active Users)

• What it is: The number of unique users who accessed the platform in a week (7-day period).
• How it is calculated: Counts unique users who logged in during a calendar week (Monday to Sunday).
• Purpose: Provides a medium-term view of engagement, smoothing out daily variations.
• Interpretation: Useful for identifying weekly trends and comparing different weeks.

MAU (Monthly Active Users)

• What it is: The number of unique users who accessed the platform in a month.
• How it is calculated: Counts unique users who logged in during a calendar month (from the 1st to the last day of the month).
• Purpose: Provides a long-term view of engagement and growth of the user base.
• Interpretation: Increasing values indicate sustained growth; useful for retention metrics.

Note: WAU and MAU metrics use calendar limits (week/month), not sliding windows of 7/30 days.

Time Series Metrics

The Dashboard displays time series graphs that show the evolution of different metrics over time:

• Format: Line graphs where each point represents a day.
• Data: Aggregated daily, showing the count of events per day.
• Visualization: Allows identification of patterns, activity peaks, and trends.
• Interactivity: You can hover over the graph points to see specific values for each day.

Types of displayed metrics:

• Authentication events (logins)
• Interactions with assistants
• Created messages
• Other system events

Assistant Usage

The Dashboard includes specific metrics about assistant usage:

• Usage Distribution: Shows which assistants are most used.
• Temporal Trends: Graphs showing how usage of each assistant evolves over time.
• Daily Aggregation: Data aggregated by day, allowing identification of usage patterns.
• Grouping: Unidentified assistants are grouped as "unknown."

How to interpret:

• Assistants with increasing usage indicate good adoption.
• An even distribution between assistants suggests diverse use cases.
• Usage peaks may indicate specific events or campaigns.

Interactive Graphs

All graphs on the Dashboard are interactive:

• Hover: Hover over the graph points to see detailed values.
• Zoom: Some graphs may allow zooming in to view specific periods.
• Filters: Use period buttons to adjust the displayed time frame.

Interpreting the Data

Understanding Trends

• Upward Trend: An upward line indicates an increase in the metric over time.
• Downward Trend: A downward line indicates a decrease in the metric.
• Stability: A flat line indicates that the metric is constant.
• Peaks and Valleys: Sharp variations may indicate specific events or seasonal patterns.

Comparing Periods

When switching between "30 Days" and "6 Months," you can:

• 30 Days: View recent details and identify short-term changes.
• 6 Months: View long-term trends and identify seasonal patterns.

Relationship Between Metrics

• DAU vs WAU vs MAU: The relationship between these metrics indicates usage frequency.
  • If DAU ≈ WAU ≈ MAU: Users access almost daily.
  • If MAU >> DAU: Users access sporadically.
• Assistant Usage vs Active Users: Helps understand if the increase in users leads to more assistant usage.

Use Cases

Growth Monitoring

Use the Dashboard to monitor platform growth:

• Track the increase of DAU, WAU, and MAU over time.
• Identify periods of accelerated growth.
• Compare different periods to measure the impact of campaigns or changes.

Engagement Analysis

Understand how users are engaged:

• High DAU values indicate frequent usage.
• The relationship between DAU/WAU/MAU shows return patterns.
• Assistant usage indicates feature adoption.

Problem Identification

Use metrics to identify problems:

• Sharp drops may indicate technical issues.
• Reduced assistant usage may signal quality problems.
• Unexpected variations deserve investigation.

Next Steps

• Explore the different graphs and metrics available.
• Experiment with different analysis periods to better understand the data.
• Use the metrics to make informed decisions about using the platform.
• Regularly monitor to identify trends and patterns.