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Fixing data quality in product analytics.
Avo fixes data quality in product analytics. Avo helps teams like Ikea, Wolt, Fender, Sixt and Condé Nast to plan, implement and monitor analytics, so they don't fly blind and fail to build great user experiences Start your step-by-step path to settle your analytics debt: Step 1: Better tracking plan management. Avo is a better alternative to the "tracking plan spreadsheet", keeping your data quality high and your schema sync'd with all downstream tools. Import your tracking plan for an instant audit, then design more scalable data for every feature release, even before you're an expert. Step 2: Better data validation. Avo is ongoing observability of actual tracking compared with tracking plan. One-time install the Avo Inspector SDK to see what's wrong with your tracking today so you can start making it better. Step 3: Better analytics release workflow. Avo is the self-serve analytics governance, changing how PMs, devs and data scientists collaborate to plan, implement and verify their product analytics. What used to take Patreon 1-4 days for every feature release, now takes 30-60 minutes.
Avo provides a platform to guarantee data quality for product analytics by governing event data definitions, implementation, and observability upstream. It offers schema management, design workflows, implementation tools, and monitoring to prevent data quality issues before they reach production.
Avo offers a unified tracking design framework with: 1) design governance to define tracking across teams, 2) review workflows to enforce stakeholder approvals, 3) implementation and validation with real-time checks for accurate tracking, and 4) observability to alert in real time about tracking drift. The product includes Inspector for monitoring production data and integrates with downstream schema registries to ensure alignment across the stack. Pricing pages describe tiers with editors, stakeholder domains, and schema sync across registries, plus access to Implementer seats and enterprise security features.
Who it’s for: Product teams, data governance/analytics teams, and data-driven organizations seeking centralized control over event data definitions and upstream quality.
Pricing page indicates multiple product tiers (Team, Enterprise) and trial/free options; case studies referenced; emphasis on book a demo and sandbox suggests go-to-market activity and customer engagement.
Mathematician & philosopher. Deep passion for understanding people and things. Always choose the adventure. Make stuff happen. One day be able to do a pull-up. Drink coffee. Eat ice cream. Find me in San Francisco, Iceland, and as @stefaniabje on the internets.
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