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Open-source infrastructure
for product analytics modeling
Collect data designed for modeling and quickly build & run reusable models.
Built for those who like their data raw and models in code
Objectiv integrates data collection & modeling to give teams everything they need
to build and run state-of-the-art product analytics models in minutes.
DATA COLLECTION
Open Analytics Taxonomy
Give your datasets a generic & strict event structure designed for modeling.
Tracking SDKs
Collect error-free user behavior data with validated instrumention.
Data cloud agnostic
Run data models across data stores. Works with existing infra, no lock-in.
DATA MODELING
Open Model Hub
Take pre-built models & functions for fast & efficient modeling.
Bach (modeling library)
Create models on your full dataset and reuse them on any project.
Data cloud agnostic
Run data models across data stores. Works with existing infra, no lock-in.
Data Collection
Always the right data for your models
Objectiv is built around an open analytics taxonomy: a generic classification of common event types and the contexts in which they can happen. It is designed and tested with UIs and product analytics use cases of over 50 companies.
No more back and forth on tracking plans
The taxonomy prescribes how to instrument your tracking, ensuring your dataset covers every common analytics use case. It is extensible to cover any custom requirements you may have.
Work with data designed for modeling
Datasets that embrace the taxonomy are well-structured for modeling and contain the exact UI location for each event captured. You can work straight on the raw data without any prepwork.
Tracking that keeps working, even if your product changes
The taxonomy is used to validate data collection at multiple stages of the pipeline, and our Tracking SDKs enable you to test & debug your instrumentation every step of the way.
Docs - Open Analytics TaxonomyData Modeling
Take pre-built models and run them on the full dataset
Open your favorite notebook tool, import the open model hub, and use pre-built product analytics models & operations directly on the raw data to build your own analyses in minutes.
Reuse models between teams & platforms
Datasets that embrace the taxonomy are very consistent. As a result, models built on one dataset can be deployed and run on another without changing a single line of code.
Runs straight on your data store
Objectiv's pandas-like modeling library runs SQL straight on your data store. You can use models in production directly to simplify data debugging & delivery to BI tools, dbt, etc.
Docs - ModelingSupported platforms and technologies
Objectiv plays nice with most popular tools in the modern data stack.
FRONTEND
DATA STORES / BACKEND
NOTEBOOKS
OUTPUTS TO
See Objectiv in action
Integration between data collection & modeling enables you to build custom product analytics models in minutes. Check out these demo notebooks to see Objectiv in action.
Demo Notebooks