This package enables you to better understand your Marketo email performance and how your leads change over time. The output includes models with enriched email metrics for leads, programs, email templates, and campaigns. It also includes a lead history table that shows the state of leads on every day, for a set of columns that you define.
This package contains transformation models, designed to work simultaneously with our Marketo 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 primary outputs of this package are described below. Intermediate models are used to create these output models.
|marketo__campaigns||Each record represents a Marketo campaign, enriched with metrics about email performance.|
|marketo__email_sends||Each record represents the send of a Marketo email, enriched with metrics about email performance.|
|marketo__email_templates||Each record represents a Marketo email template, enriched with metrics about email performance.|
|marketo__lead_history||Each record represents the state of a lead on a specific day. The columns in this model are specified with the
|marketo__leads||Each record represents a Marketo lead, enriched with metrics about email performance.|
|marketo__programs||Each record represents a Marketo program, enriched with metrics about email performance.|
Include in your
packages: - package: fivetran/marketo version: [">=0.7.0", "<0.8.0"]
By default, this package will look for your Marketo data in the
marketo schema of your target database. If this is not where your Marketo data is , please add the following configuration to your
... config-version: 2 vars: marketo_source: marketo_database: your_database_name marketo_schema: your_schema_name
For additional configurations for the source models, please visit the Marketo source package.
Tracking Different Lead History Columnslink
marketo__lead_history model generates historical data for the columns specified by the
lead_history_columns variable. By default, the columns tracked are
behavior_score_marketing. If you would like to change these columns, add the following configuration to your
dbt_project.yml file. After adding the columns to your
dbt_project.yml file, run the
dbt run --full-refresh command to fully refresh any existing models.
... config-version: 2 vars: marketo: lead_history_columns: ['the','list','of','column','names']
Changing the Build Schemalink
By default this package will build the Marketo staging models within a schema titled (<target_schema> +
_stg_marketo) and Marketo final models within a schema titled (<target_schema> +
marketo) in your target database. If this is not where you would like your modeled Marketo data to be written to, add the following configuration to your
... models: marketo: +schema: my_new_schema_name # leave blank for just the target_schema marketo_source: +schema: my_new_schema_name # leave blank for just the target_schema
This package takes into consideration tables that may not be synced due to slowness caused by the Marketo API. By default the
program related-models are disabled. If you sync these tables, enable the modeling done by adding the following to your
... vars: marketo__enable_campaigns: True #Enable if Fivetran is syncing the campaign table marketo__enable_programs: True #Enable if Fivetran is syncing the program table
Additional contributions to this package are very welcome! Please create issues
or open PRs against
main. Check out
on the best workflow for contributing to a package.
This package has been tested on BigQuery, Snowflake and Redshift.
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