Why Choose Self-Service BI in 2025?

Traditional BI Platforms

Tableau and Power BI typically require significant technical expertise, often creating data bottlenecks and delays in decision-making. These systems tend to restrict access to only a group of experts who have the necessary technical skills, which can prevent non-technical users from getting the insights they need on time.

Self-Service BI Platforms

On the other hand, regardless of their technical background, anyone can independently analyze data and create visualizations without needing assistance from IT teams. These platforms emphasize broad data accessibility, allowing more individuals across the organization to explore and interpret data independently. By providing easy access to data, self-service BI empowers everyone to make data-driven decisions with greater efficiency.

There are Two Groups of Self-Service BI Tools

Integrating your data warehouse with self-service BI tools allows you to independently access, analyze, and visualize your data, reducing reliance on technical teams. These tools can be  divided into two categories:

• Third-party product analytics tools
• Warehouse-native analytics tools

Warehouse-native tools have clear advantages over third-party applications, particularly for teams already using data warehouses. They allow direct access to first-party data, providing real-time insights without complex data pipelines. Because they leverage your existing infrastructure, they cut down on costs tied to duplicate storage and are easier to maintain. Keeping all data in one place improves governance, security, and compliance. These tools scale effectively with your data needs, using the warehouse's power for fast performance. Unlike third-party platforms, they eliminate silos and ensure everyone works from the same, reliable data source. While third-party tools might be quicker to get started with, warehouse-native tools offer better flexibility, control, and long-term cost savings for data-driven teams.

Below, I present six alternatives in a detailed table, comparing their features and pricing.

Warehouse-Native Self-Service BI Tools

Mitzu.io

Pricing

Mitzu.io uses a seat-based pricing model, charging based on the number of users accessing the platform rather than the volume of tracked events. This approach offers a cost-effective solution for growing businesses by removing the worry of escalating costs as event tracking increases. For companies with 10 product or marketing managers who need self-service analytics with unlimited events, the annual fee is approximately $12,000.

Key features

• Native Integration with Data Warehouses and Automated SQL Queries: Mitzu connects directly to your data warehouse (e.g., Snowflake, Clickhouse, etc..), quickly syncing product, marketing, and revenue data. With automated SQL generation, you can extract insights without needing advanced technical skills.
• User Journeys and Retention: Analyze how users interact with your product at every step, enabling you to enhance their experience and build strategies to boost retention.
• Cohort and User Behavior Analysis: Group users by similar attributes, like pricing tiers or locations, and examine their behaviors more deeply for actionable insights.
• Conversion rates: Gain visibility into your marketing performance by tracking user engagement and conversion rates for each campaign.
• Advanced Segmentation Tools: Effortlessly categorize users based on specific behaviors or characteristics, such as company size or region, to refine your analytics and strategies.
• Funnel Optimization: Pinpoint drop-off points in user workflows to address friction and improve conversion rates.
• Revenue analytics (e.g., MRR): Unlike most competitors, Mitzu includes tools for analyzing recurring revenue and subscription data, which makes it particularly useful for subscription-based businesses.

Netspring (Optimizely)

Pricing

Like Mitzu.io, Netspring also charges based on the number of users rather than the volume of events or data tracked. This is advantageous for businesses aiming to scale analytics capabilities without worrying about escalating fees, as data is critical.

Key features

• Warehouse-Native Analytics: It works directly within your data warehouse, ensuring accurate and trustworthy insights without moving data.
• Self-Service Capabilities: Users can access a wide range of report templates and ad-hoc exploration tools, making it easy to dig deeper into data without relying on technical teams.
• Customizable Analytics: With NetSpring, you can create custom metrics to reflect your specific business entities, such as accounts, projects, or tickets, offering a tailored analytics experience.
• Advanced Cohort Analysis: It supports cohort-specific tracking, enabling you to drill down into user behaviors and identify which segments drive retention, activation, and other critical KPIs.
• Product and Customer Insights: NetSpring offers insights into product and customer metrics, providing a 360-degree view of user behavior, operational trends, and business performance.
• Continuous KPI Monitoring: The platform also provides real-time KPI tracking, with alerts for any business shifts, such as customer experience degradation or opportunities for upselling. This keeps your team proactive in identifying and addressing potential issues.
• Acquisition of Netspring: Optimizely has acquired Netspring, which raises questions about the product's future. Netspring could be discontinued or integrated into Optimizely's offerings, leading to uncertainty regarding its continued existence as an independent tool.

Traditional self-service BI tools

Amplitude

Pricing

MTU-based: MTU-based pricing charges organizations based on the number of unique users actively engaging with the product within a given month.

Key features:

• Behavioral Graphs and Path Analysis: The platform includes advanced visualization tools, such as behavioral graphs and path analysis, which help you understand the flow of user interactions within your product.
• Predictive Analytics: Amplitude can predict user behaviors with machine learning capabilities, enabling proactive decision-making and strategy adjustments.
• Scalable for Enterprises: It is built to handle large datasets, making it suitable for startups and enterprise-level organizations with high data demands.
• Custom Dashboards and Reporting: You can create customized dashboards tailored to specific KPIs and export reports in various formats for easy sharing with stakeholders.
• Real-Time Collaboration Features: The platform allows collaboration effectively by sharing real-time insights, dashboards, and data annotations.
• Event-Based Tracking: Amplitude’s event-focused tracking provides detailed insights into specific user actions, enabling granular analysis of critical behaviors.
• Strong Community and Support: A vast knowledge base, active user community, and responsive customer support ensure that you can quickly resolve issues and optimize your analytics setup.
• Warehouse-native connection only to Snowflake: Amplitude's Snowflake-native integration marks the debut of its Warehouse-native Amplitude initiative. This innovative zero-copy solution empowers Snowflake users to conduct advanced product analysis directly within Snowflake, seamlessly bringing Amplitude’s capabilities to their existing data.

Pendo

Pricing

MAU-based: MAU-based pricing charges organizations based on the number of unique users actively engaging with the product within a month.

Key features

• AI-Powered Analytics: Pendo automatically highlights user trends and patterns, helping you quickly identify what’s driving retention or where users are dropping off.
• Granular Funnel Analysis: With advanced filtering options, you can group and analyze user flows based on event properties that matter to your product goals, such as device type or specific action
• Identity Mapping: You can track users throughout their journey, even connecting their pre-login activity with post-login behaviors.
• Embedded Content: It helps you tweak interfaces and insert content without relying on developers, saving you time and resources.
• Team Collaboration: Collaborate directly within Pendo by tagging team members, sharing insights, and commenting on reports.
• Interactive Guides: Deploy no-code onboarding flows and tooltips to help users adopt features seamlessly. You can also track their impact directly in conversion funnels to see what’s working.
• Journey Automation: Automate actions like sending reminders or showing guides based on how your users interact with your product. This keeps them engaged and helps you deliver personalized experiences.

Mixpanel

Pricing

MTU-based: MTU-based pricing (Monthly Tracked Users) is a model where organizations are charged based on the number of unique users actively engaging with their product during a given month.

Key features

• Event-Based Tracking: Track specific user interactions such as clicks, sign-ups, or purchases across your app or website. This allows you to understand precisely how users engage with your product.
• Funnel Analysis: Visualize user journeys and identify where users drop off, helping you optimize conversion rates at critical stages.
• Retention Analysis: Measure how frequently users return to your product after their first interaction, providing insights into customer loyalty and product value.
• User Segmentation: Group your users based on behaviors or demographics, enabling you to analyze different cohorts and deliver targeted improvements or campaigns.
• A/B Testing: Experiment with variations of features, designs, or workflows and compare their performance to make data-driven decisions that boost engagement.
• Predictive Analytics: Use historical data to forecast user actions, enabling proactive decision-making and strategy development.
• Interactive Data Visualization Tools: Turn raw data into clear, actionable visualizations. The user-friendly dashboard empowers you to explore your data without requiring advanced technical skills.

PostHog

Pricing

MTU-based: MTU-based pricing is a model where businesses are billed based on the number of unique users actively interacting with the product during a specific month.

Key features

• Autocapture: PostHog automatically captures events without requiring manual instrumentation, enabling non-technical users to track user actions across your site or app easily.
• Open Source: As an open-source tool, PostHog offers the flexibility to customize and extend the platform, as well as access to the community and continuous feature improvement.
• Funnels and Journey Mapping: You can track conversion rates, user paths, and overall journey maps, which allow you to visualize and optimize how users engage with your product.
• Session Replay: The platform includes session replays, enabling you to see exactly how users interact with your website or app, which is valuable for identifying friction points or bugs.
• Heatmaps: PostHog provides heatmaps that help you understand where users click and how far they scroll, giving you visual insights into user engagement.
• User Segmentation and Group Analytics: You can analyze user behavior and segment users based on specific properties or actions, offering a more granular view of engagement.
• A/B Testing: PostHog's built-in A/B testing features allow you to experiment with product changes and measure their impact, helping you optimize product features.

Conclusion

After evaluating six alternatives, I compared two distinct approaches to product analytics: traditional third-party solutions and warehouse-native tools. Each approach offers unique advantages in terms of scalability, data integration, and user engagement tracking.

Mitzu.io: It provides warehouse-native, self-service analytics directly connected to you data warehouse. Its seat-based pricing is cost-effective for growing teams needing powerful analytics.

Netspring (Optimizely): It is also a warehouse-native analytics tool with customizable reporting and real-time KPI tracking. It’s ideal for teams seeking deep product and user insights.

Amplitude: It offers scalable product analytics with a Snowflake-native integration for efficient, warehouse-driven insights. Its advanced segmentation and predictive analytics help optimize user engagement.

Pendo: It combines analytics with in-app guidance and feedback to enhance product experiences. Its AI-powered insights and journey automation features help boost user retention.

Mixpanel: It excels in event tracking, user segmentation, and funnel analysis to optimize conversions. Its predictive analytics and A/B testing enable continuous product improvement.

PostHog: Its open-source platform offers session replays and auto-capture for in-depth user tracking. Its heatmaps and A/B testing provide valuable insights into user interactions.