Objectiv provides an open-source product analytics infrastructure that enables users to collect and analyze super-structured user behavior data directly from their preferred data stores using Python notebooks. The platform offers pre-built models for product analytics and tools for validated tracking, ensuring accurate data insights without the complexity of traditional analytics setups.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional product analytics setups are complex, requiring significant effort to collect, validate, and analyze user behavior data. Existing solutions often lack the flexibility to model data directly from raw sources, leading to inaccurate insights and delayed decision-making.
Solution
Objectiv provides an open-source product analytics infrastructure that allows users to collect and analyze super-structured user behavior data directly from their data stores using Python notebooks. The platform offers pre-built models designed for product analytics, enabling users to work directly on raw data without extensive preprocessing. Objectiv integrates seamlessly with existing data stacks, connecting to preferred data stores and BI tools. It also provides tooling to test, validate, and debug tracking setups, ensuring data accuracy throughout the analytics pipeline.
Target Audience
Objectiv is designed for data scientists, product managers, and analysts who want to control their product analytics, work directly with raw data, and ensure data accuracy.
Features
- Open-source product analytics infrastructure
- Collects super-structured user behavior data
- Enables data modeling directly from Python notebooks
- Offers pre-built models for product analytics
- Integrates with SQL data stores like BigQuery, Snowflake, and Redshift
- Compatible with BI tools such as Metabase and Looker
- Provides validated tracking and debugging tools
- Supports self-hosting or fully managed cloud deployment
- Includes an open model hub with example notebooks for various analytics use cases, such as user intent analysis, funnel discovery, and logistic regression