Rakam

A warehouse-native product analytics tool to understand user behaviour and identify points of friction in the user journey.

Product Analytics

What need does Rakam fulfill?

Rakam addresses the need for a product analytics tool that natively integrates with a data warehouse. It allows data teams to build models on top of the data that is already available in the warehouse, enabling product, marketing, and growth teams to explore the modelled data using a visual interface.

The visual querying of data generates SQL that runs on your existing data warehouse without ever moving the data out of the warehouse. Rakam also supports CDI solutions like RudderStack, Segment Connections, and Snowplow, and offers reporting features similar to those offered by popular product analytics tools.

What are the benefits of using Rakam?

See how your product is used to understand user behaviour

Identify points of friction in the user journey

Find common usage patterns amongst the most engaged users

What are the core features of Rakam?

Funnel, Flow, and Retention Analysis

Segmentation and Cohort Analysis

Support for the Data Warehouse as a Data Source

Support for dbt as the Data Modelling Layer

Which teams does Rakam cater to?

Product
Growth
Marketing

Authored By

Emre Semercioglu

Product & Growth at Rakam

How does Rakam integrate with dbt?

Rakam connects to your GIT repository that has your dbt project and synchronizes all your models, seeds, and sources to create datasets.

How is Rakam different from popular BI tools like Tableau and Looker?

Rakam is purpose-built for product analytics and offers out-of-the-box reporting features to meet the analysis needs of product and growth teams.

How is Rakam different from popular product analytics tools like Mixpanel and Amplitude?

Unlike Product Analytics tools, Rakam connects to your warehouse and doesn't ingest or duplicate any data into its servers.

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