Title: Insights Overview
Locale: en
URL: https://sensorswave.com/en/docs/analytics/overview/
Description: Learn about the core capabilities and value of the Insights module, and quickly grasp the overall framework for data analysis
Insights is the core analysis module of Sensors Wave, offering multiple analysis models to help you understand user behavior and business performance from different perspectives. With Insights, you can track key metrics, discover growth opportunities, identify root causes of issues, and provide data-driven support for product decisions.

Insights helps you answer the following questions:
- What are users doing in the product, and which features are most popular?
- What does the path from visit to conversion look like, and where is the highest drop-off?
- Are users continuing to use the product, and how is the retention rate changing?
- How can you perform more flexible custom analysis using SQL?

## Core Capabilities

The Insights module provides the following core capabilities:

### Multi-Dimensional Data Analysis

Supports analyzing user behavior from multiple angles:

- **Event Analysis**: Track and measure user behavior events to understand feature usage and trend changes
- **Retention Analysis**: Measure users' continued return visits to assess product stickiness and long-term value
- **Funnel Analysis**: Analyze the conversion efficiency of multi-step processes to identify drop-off points and optimization opportunities
- **SQL Query**: Use SQL for arbitrarily complex custom analysis

### Flexible Data Exploration

Each analysis model supports rich data exploration capabilities:

- **Segment By**: Filter data by User Property, Event Property, or Cohort
- **Group By**: Break down data by dimensions to discover distribution patterns and differences
- **Time Comparison**: Support various time comparison methods including period-over-period and year-over-year
- **User Drill-down**: Drill down from metric values to specific user lists

### Integration with Other Modules

Insights works closely with other Sensors Wave modules:

- **Integration with User Operations**: Drill down from analysis results to User List to view specific user behavior
- **Integration with Cohorts**: Use Cohorts as filter conditions in analysis to compare different groups
- **Integration with Feature Gates**: Analyze metric changes before and after Feature Gate activation
- **Integration with Experiments**: Analyze differences between experiment and control groups

## Module Overview

| Analysis Model | Core Value | Typical Scenarios | Complexity |
|---------|---------|---------|--------|
| **[Event Analysis](event-analysis.mdx)** | Measure user behavior and understand usage trends | Feature usage analysis, daily data monitoring | Beginner |
| **[Retention Analysis](retention-analysis.mdx)** | Measure user stickiness and assess product value | Retention rate tracking, feature value validation | Intermediate |
| **[Funnel Analysis](funnel-analysis.mdx)** | Analyze conversion efficiency and identify drop-off points | Registration conversion, purchase conversion analysis | Intermediate |
| **[SQL Query](sql-query.mdx)** | Flexible customization for complex needs | Cross-table joins, complex aggregate calculations | Advanced |

Not sure which analysis model to use? See [Choosing the Right Analysis Model](choosing-analysis-model.mdx).

## 5 Key Metrics to Get Started

If you're just getting started with Insights, we recommend starting with these 5 key metrics:

### 1. Daily Active Users (DAU)

**Definition**: The number of unique users who trigger at least one active event per day.

**How to create**:
1. Create a new Event Analysis
2. Select an active event (e.g., "App Launch" or "Any Event")
3. Set the measure to "Unique Users"
4. Set the time granularity to "By Day"

**Value**: Understand the daily active user scale of your product — the most fundamental health metric.

### 2. New User Registrations

**Definition**: The number of new users who complete registration each day.

**How to create**:
1. Create a new Event Analysis
2. Select the "User Registration" event
3. Set the measure to "Unique Users"

**Value**: Track user growth and evaluate acquisition effectiveness.

### 3. Core Feature Usage Rate

**Definition**: The proportion of active users who use a core feature.

**How to create**:
1. Create a new Event Analysis
2. Select a core feature event
3. Set the measure to "Unique Users"
4. Compare with DAU for the same period to calculate usage rate

**Value**: Understand core feature penetration and identify optimization opportunities.

### 4. Day-1 Retention Rate

**Definition**: The proportion of new users who remain active on the 1st day after registration.

**How to create**:
1. Create a new Retention Analysis
2. Set the Starting Event to "User Registration"
3. Set the Return Event to an active event
4. View the Day-1 Retention Rate

**Value**: Measure the initial experience of new users — an early indicator of product stickiness.

### 5. Key Process Conversion Rate

**Definition**: The proportion of users who complete a key business process.

**How to create**:
1. Create a new Funnel Analysis
2. Configure the steps of the key process (e.g., "Browse Product → Add to Cart → Submit Order → Payment Successful")
3. View the overall conversion rate and per-step conversion rates

**Value**: Understand the efficiency of business processes and identify optimization priorities.

## Prerequisites

Before using Insights, make sure you have:

- Completed [SDK integration](../data-integration/client-sdks/javascript.mdx) and started receiving data
- Understood the basic concepts of the [Data Model](../data-integration/data-model.mdx) and [Events and Properties](../data-integration/events-and-properties.mdx)
- Created the event types you need to analyze in Data Center
- Have view or analysis permissions for the project

## Next Steps

Now that you understand the basics of Insights, you can:

1. **[Quick Start](quick-start.mdx)**: Get started quickly with a complete example of data analysis
2. **[Choosing the Right Analysis Model](choosing-analysis-model.mdx)**: Learn how to select the appropriate analysis model
3. **[Event Analysis](event-analysis.mdx)**: Learn the most commonly used analysis model

If you encounter issues during use, check the [FAQ](faq.mdx) or refer to the [Best Practices](best-practices.mdx).

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**Last updated**: January 19, 2026