Introducing the Fivetran dbt package for Marketo

Enrich your Marketo objects with email metrics and track slowly changing dimensions for leads.
June 10, 2020

For an overview of how dbt powers advanced transformations and information about our other dbt packages, take a look at this recent blog post.

The Fivetran dbt package for Marketo delivers aggregated tables that tie activity and metrics to your Marketo objects. It starts with the normalized tables created by the Fivetran Marketo automated connector that navigates Marketo’s complex API.

More specifically, multiple reporting tables are generated that enable:

  • Marketo campaign, email sends, leads and programs to be enriched with metrics about email performance, such as opens, clicks and unsubscribes
  • Tracking slowly changing dimensions for leads to create a historical record of daily changes for better lead tracking over time

Tying these metrics to related objects and providing a lead history table make it easy to identify the success of campaigns and programs. Success is measured both by email interactions as well as with how leads progress through the funnel. This allows you to easily optimize future Marketo programs and campaigns for better lead generation.

Challenges of the Marketo API

Extracting data from Marketo is notoriously difficult. Marketo provides two different APIs, Bulk and REST, which serve different purposes. Those differences pose challenges as to how to use each most effectively. In addition, each of those API types has its own account-level limit for daily API quota.

Marketo also offers many options for tracking user activity, which leads to a large amount of data and associated endpoints available, where object lineage needs to be traced to map out the complex one-to-many relationships. Case in point: every single activity generates its own “row” in the activity endpoint, which makes it a challenge to aggregate activities to a parent object like a campaign.

How Fivetran helps

Our Marketo connector requires a few fields to be pulled from the Marketo UI to set up. From there, we automatically determine which API to use and when to best apply those APIs.

This results in normalized tables presented in a neat entity relationship diagram that highlights where tables can be joined so that it’s easy for analysts to begin querying Marketo data.

Fivetran pulls updates automatically in a self-configured schedule so that your data is always fresh. API limits can be set within our UI to ensure essential business processes are not affected by data integration. In addition to the tables generated by the final models of the package, the source package also conveniently creates a standardized data dictionary for your analysts to reference for future projects.

How can I get started with dbt and marketo?

Get the dbt Package for Marketo

Kostenlos starten

Schließen auch Sie sich den Tausenden von Unternehmen an, die ihre Daten mithilfe von Fivetran zentralisieren und transformieren.

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Introducing the Fivetran dbt package for Marketo

Introducing the Fivetran dbt package for Marketo

June 10, 2020
June 10, 2020
Introducing the Fivetran dbt package for Marketo
Enrich your Marketo objects with email metrics and track slowly changing dimensions for leads.

For an overview of how dbt powers advanced transformations and information about our other dbt packages, take a look at this recent blog post.

The Fivetran dbt package for Marketo delivers aggregated tables that tie activity and metrics to your Marketo objects. It starts with the normalized tables created by the Fivetran Marketo automated connector that navigates Marketo’s complex API.

More specifically, multiple reporting tables are generated that enable:

  • Marketo campaign, email sends, leads and programs to be enriched with metrics about email performance, such as opens, clicks and unsubscribes
  • Tracking slowly changing dimensions for leads to create a historical record of daily changes for better lead tracking over time

Tying these metrics to related objects and providing a lead history table make it easy to identify the success of campaigns and programs. Success is measured both by email interactions as well as with how leads progress through the funnel. This allows you to easily optimize future Marketo programs and campaigns for better lead generation.

Challenges of the Marketo API

Extracting data from Marketo is notoriously difficult. Marketo provides two different APIs, Bulk and REST, which serve different purposes. Those differences pose challenges as to how to use each most effectively. In addition, each of those API types has its own account-level limit for daily API quota.

Marketo also offers many options for tracking user activity, which leads to a large amount of data and associated endpoints available, where object lineage needs to be traced to map out the complex one-to-many relationships. Case in point: every single activity generates its own “row” in the activity endpoint, which makes it a challenge to aggregate activities to a parent object like a campaign.

How Fivetran helps

Our Marketo connector requires a few fields to be pulled from the Marketo UI to set up. From there, we automatically determine which API to use and when to best apply those APIs.

This results in normalized tables presented in a neat entity relationship diagram that highlights where tables can be joined so that it’s easy for analysts to begin querying Marketo data.

Fivetran pulls updates automatically in a self-configured schedule so that your data is always fresh. API limits can be set within our UI to ensure essential business processes are not affected by data integration. In addition to the tables generated by the final models of the package, the source package also conveniently creates a standardized data dictionary for your analysts to reference for future projects.

How can I get started with dbt and marketo?

Get the dbt Package for Marketo

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Schließen auch Sie sich den Tausenden von Unternehmen an, die ihre Daten mithilfe von Fivetran zentralisieren und transformieren.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.