Insights

Insights are the primary way to create persistent visualizations and analyses in Altertable. They are saved analytics views that help you track key metrics, understand user behavior, and make data-driven decisions.

What are Insights?

Insights transform raw data into actionable visualizations by:

• Querying your lakehouse data using predefined logic
• Supporting multiple visualization types (charts, tables, metrics)
• Refreshing automatically or on-demand
• Being shareable with teams and embeddable in external tools

Prerequisites: Insights analyze data in your lakehouse. Start by tracking events and identifying users to capture the data you want to analyze.

Goals of Insights

• Track metrics over time: Monitor KPIs and business metrics continuously
• Understand behavior: Analyze user actions, conversions, and engagement
• Compare segments: Identify differences between user cohorts
• Inform decisions: Provide data-driven answers to business questions

Insight Types

Altertable provides insight types, each optimized for different analysis needs.

1. Funnel Insights

Track user progression through sequential events to measure conversion rates and identify drop-offs.

Best for:

• Signup and onboarding flows
• Checkout and purchase processes
• Feature adoption journeys
• Multi-step workflows

Key metrics:

• Step-by-step conversion rates
• Overall funnel completion
• Drop-off points and rates
• Time to convert between steps

Common examples:

• Signup funnel: Landing page → Signup form → Email verification → Profile completed
• Checkout funnel: Product viewed → Added to cart → Checkout started → Purchase completed
• Feature adoption: Feature discovered → Feature clicked → Feature configured → Feature used

2. Segmentation Insights

Group users into cohorts based on behavioral patterns and analyze differences between segments.

Best for:

• User cohort analysis
• Comparative behavior studies
• Engagement level tracking
• Retention analysis

Common segments:

• By activity level (power users, regular users, casual users)
• By feature usage (adopters, explorers, unaware)
• By purchase behavior (recent, repeat, one-time)
• By acquisition channel or demographics

Example segments:

• Engagement: Users segmented by sessions per month (20+, 10-20, 1-10, inactive)
• Feature adoption: Users who adopted vs explored vs never used a feature
• Revenue: High-value, medium-value, low-value customers based on spend

Learn more about segmentation →

3. Semantic Insights

Query structured data models using business-friendly metrics and dimensions without writing SQL.

Best for:

• Business metric reporting
• KPI dashboards
• Cross-functional analytics
• Model-based queries

Key features:

• Pre-defined metrics (revenue, DAU, conversion rate)
• Reusable dimensions (region, plan type, category)
• No SQL knowledge required
• Centralized business logic

Benefits:

• Consistency: Everyone uses the same metric definitions
• Accessibility: Business users can query without technical knowledge
• Governance: Centralized control over business logic
• Reusability: Define once, use across all dashboards and reports

Learn more about semantic insights →

4. SQL Insights

Execute custom SQL queries using DuckDB dialect for complete flexibility in data analysis.

Best for:

• Complex custom queries
• Ad-hoc analysis
• Advanced calculations (window functions, CTEs)

Capabilities:

• Full DuckDB SQL dialect support
• Cross-database federated queries
• Advanced analytics functions (window functions, CTEs, recursive queries)
• Complete query flexibility

Use cases:

• Custom retention calculations with specific business rules
• Complex multi-source joins (product events + CRM + revenue data)
• Advanced cohort analysis with custom time windows
• Performance analysis with moving averages and percentiles

Learn more about SQL insights →

Quick Decision Guide

Start with Funnels when:

• Tracking multi-step processes
• Measuring conversion rates
• Finding drop-off points

Use Segmentation when:

• Comparing user groups
• Analyzing cohort behavior
• Understanding engagement levels

Choose Semantic when:

• Reporting standard business metrics
• Building KPI dashboards
• Enabling non-technical users

Go with SQL when:

• Requiring custom calculations
• Joining multiple data sources
• Exploring data ad-hoc

Learn More

Ready to dive deeper? Explore the technical documentation:

• Funnel Insights: Track user progression through sequential events
• Segmentation Insights: Group users into cohorts based on behavior
• Semantic Insights: Query structured data models without SQL
• SQL Insights: Execute custom SQL queries for complete flexibility
• Product Analytics: Set up event tracking and user identification
• Analytical Database: Query your lakehouse with SQL
• Architecture: Understand Altertable's infrastructure
• AI Agents: Automate analytics with AI