Basic information

1. Name Mitzu
2. Type Warehouse-native product & marketing analytics
3. Launch September 2022
4. Founder Istvan Meszaros
5. Website mitzu.io
6. Category Product Analytics / Customer Journey Analytics / Business Intelligence

Background

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Mitzu was founded around 2022 to help product, marketing, and growth teams perform analytics directly on their data warehouses. It was created after the founder, István Mészáros, noticed teams struggling with inconsistent metrics, data silos, and high analytics costs. The platform solves the problem of traditional analytics tools that require copying data into separate systems, ensuring accuracy, governance, and cost-efficiency.

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Core services

1. Warehouse-Native Product Analytics – Analytics run directly on your existing data warehouse (Snowflake, BigQuery, Databricks, etc.) without duplicating data.
2. Funnels & Customer Journeys – Track how users move through your product and identify drop-off points.
3. Retention & Cohort Analysis – Measure user retention and segment users by behavior, time, or attributes.
4. Segmentation & Behavioral Analysis – Create dynamic cohort & segments based on user actions or properties for targeted analysis.
5. Marketing & Campaign Analytics – Measure conversion, acquisition, and campaign effectiveness.
6. Self-Service Dashboards – Non-technical teams can build reports and dashboards without SQL.
7. Subscription & Revenue Analytics – Monitor recurring revenue, churn, and monetization metrics for SaaS businesses.
8. Data Governance & Security – Full control of your data remains in your warehouse; Mitzu does not duplicate or store it externally.
9. SQL Transparency & Advanced Queries – For technical users, SQL queries are generated or can be customized for deep analysis.

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Clients & Case studies

1. 52 Entertainment: Saved 60+ hours/month for the data team; achieved 2× faster data‑source integration and 100% control over product analytics. Mitzu
2. Shapr3D: Achieved 3× faster decision‑making, 90% fewer data mismatches, 50% faster ad‑hoc reporting, and a 25% boost in product optimization. Mitzu
3. Suunto: Reduced analytics costs by over 80%, consolidated 5+ major data sources (app telemetry, devices, SAP), and built their own data‑model in Databricks while enabling self‑service access. Mitzu
4. Prezi: Achieved 100% accuracy and trust in reports, cut reporting time from 2 days to 2 hours and reduced data support tickets by ~50%.
5. Khatabook: Handled over 4 billion monthly event‑captures by replacing its analytics tool with Mitzu — resulting in a ~90% reduction in product analytics costs and faster query performance. Mitzu
6. Colossyan: With Mitzu they realised 50% faster ad‑hoc reporting, improved their onboarding funnel by 20‑30% and gave non‑tech teams self‑service access to insights previously locked in SQL.

Competitive advantages (measureable differentatiors)

1. Warehouse‑native architecture: Mitzu runs analytics directly on your existing data warehouse (Snowflake, BigQuery, Databricks, etc.) rather than forcing you to move or replicate data into a separate system.
2. Full data control & governance: Because data remains in your own warehouse, Mitzu offers stronger data privacy, ownership and compliance than many cloud‑hosted analytics tools.
3. Cost predictability and scalability: Unlike many event‑volume or MTU‑based pricing models, Mitzu uses a seat‑based or usage‑independent pricing model and avoids exponential cost growth as you scale events.
4. Advanced analytics for B2B/SaaS contexts: It supports subscription‑analytics (MRR/ARR), user‑journey, funnel, retention, cohort analyses in the data warehouse context, catering well to SaaS/product teams.
5. No‑code UI + SQL transparency: While users can access analytics without writing SQL, Mitzu also allows SQL‑level access for analysts — bridging the gap between non‑technical and technical users.
6. Unlimited event/usage scale (subject to warehouse capacity): There are no inherent event‑tracking limits built into Mitzu’s analytics tool (only limited by your warehouse infrastructure), which many classic tools impose.

Ideal for

1. Mid-market and large companies with high-volume datasets
2. e‑Commerce, Media, Travel, B2B/B2C SaaS, Gaming, Edtech
3. Product teams tracking user behavior and feature adoption
4. Marketing teams measuring campaigns and conversion performance
5. Data teams needing governed warehouse-native analytics
6. Companies prioritizing full data control and security

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Third-party reviews

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G2 reviews

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Attila K., Analytics Engineer (Mid‑Market): “When companies lacked the tech stack … the best thing about Mitzu is that it sits on top of your stored data, what you own and control. It took like 5 minutes to setup, and the insights are quite straight forward!” - Rated 5/5.

Sakshi, Head of Analytics (Large): "Mitzu provides consistent data across analytics platforms with cost-effective pricing not based on event volume. Its insights-driven approach enables self-service for product and business teams, helping resolve issues like user dropout and retention via funnels and user journeys. Native warehouse support and seamless Snowflake integration allow ad-hoc analysis without data transfers, while the Mitzu team offers responsive, empathetic support and continuously improves the platform." - Rated 4.5/5

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Last updated: November 2025

More information: mitzu.io