Stripe Metrics dbt Package (Docs)

🛑 Few things to keep in mind

These packages are under active development and are expected to change with dbt metrics as it evolves over time. As of now, dbt metrics requires users to define models to calculate metrics and these models are persisted on the warehouse. Keeping this in mind, we have currently modelled our packages such that metrics and the models calculating these metrics have a 1:1 mapping, which is why you will see multiple metrics for the same conceptual metric entity accounting for different time grains and dimensions. In future, with the roll out of dbt Server and evolution of dbt metrics, we expect to streamline our packages to remove these redundancies.

The metrics in these packages are transformed on top of source data ETL'd via Fivetran to your warehouse. Make sure you have connected your SaaS source with Fivetran for the packages to work properly.

📣 What does this dbt package do?

This package provides pre-built metrics for Stripe data from Fivetran's connector. It uses data in the format described by this ERD.

This package enables you to access commonly used metrics on top of Stripe transactions.

Metrics

This package contains transformed models built on top of Fivetran Stripe source package. A dependency on the source package is declared in this package's packages.yml file, so it will automatically download when you run dbt deps. The metrics offered by this package are described below

metric	description
stripe__monthly_bookings	Monthly revenue from all transactions.
stripe__monthly_churned_customer_revenue	Monthly revenue lost due to churned customers.
stripe__monthly_churned_customers	Monthly count of customers that churned.
stripe__mrr	Monthly recurring revenue.
stripe__monthly_new_customer_revenue	Monthly revenue due to customers that signed up for the first time.
stripe__monthly_new_customers	Monthly count of customers that signed up for the first time.
stripe__monthly_platform_fees	Monthly fees paid to Stripe.
stripe__monthly_recovered_customer_revenue	Monthly revenue due to recovery of previously churned customers.
stripe__monthly_recovered_customers	Monthly count of previously churned customers who signed up again.

🎯 How do I use the dbt package?

Step 1: Prerequisites

To use this dbt package, you must have the following:

• At least one Fivetran stripe connector syncing data into your destination.
• A BigQuery, Snowflake, Redshift, or PostgreSQL destination.

Step 2: Install the package

Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.

Include in your packages.yml

packages:
  - git: "https://github.com/HousewareHQ/dbt_stripe_metrics.git"
    revision: v0.1.1

Step 3: Define database and schema variables

By default, this package will look for your Stripe data in the stripe schema of your target database. If this is not where your Stripe data is, please add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
config-version: 2

vars:
  stripe_source:
    stripe_database: your_database_name
    stripe_schema: your_schema_name

For additional configurations for the source models, please visit the Stripe source package.

(Optional) Step 4: Change build schema

By default this package will build the Stripe staging models within a schema titled (<target_schema> + _stg_stripe) and the Stripe metrics within a schema titled (<target_schema> + _stripe_metrics) in your target database. If this is not where you would like your modeled Stripe data to be written to, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
models:
  stripe_metrics:
    +schema: my_new_schema_name # leave blank for just the target_schema
  stripe_source:
    +schema: my_new_schema_name # leave blank for just the target_schema

🗄 Which warehouses are supported?

This package has been tested on BigQuery, Snowflake.

🙌 Can I contribute?

Additional contributions to this package are very welcome! Please create issues or open PRs against main. Check out this post on the best workflow for contributing to a package.

🏪 Are there any resources available?

• Provide feedback on what you'd like to see next
• Have questions, feedback, or need help? Email us at nipun@houseware.io
• Check out Houseware's blog
• Learn more about dbt in the dbt docs
• Check out Discourse for commonly asked questions and answers
• Join the chat on Slack for live discussions and support
• Find dbt events near you
• Check out the dbt blog for the latest news on dbt's development and best practices