v0.1.0 dbt_stackadapt

This is the initial release of the dbt_stackadapt dbt package.

Initial Release

This package models data from Fivetran's StackAdapt connector and produces the following analytics-ready tables:

Table	Description
stackadapt__advertiser_report	Represents daily performance aggregated at the advertiser level, including impressions, clicks, spend, and conversions. Example Analytics Questions: How does performance compare across different advertisers? Which advertisers are driving the most spend or conversions?
stackadapt__campaign_group_report	Represents daily performance aggregated at the campaign group level, including impressions, clicks, spend, and conversions. Example Analytics Questions: Which campaign groups have the highest click-through rate or conversion rate? How does spend and performance compare across campaign groups within each advertiser?
stackadapt__campaign_report	Represents daily performance aggregated at the campaign level, including impressions, clicks, spend, and conversions. Example Analytics Questions: Which campaigns are most efficient in terms of cost per conversion? How does delivery performance vary by campaign channel type and status?
stackadapt__ad_report	Represents daily performance at the individual ad level, including impressions, clicks, spend, and conversions. Example Analytics Questions: Which ad creatives are driving the lowest cost per click? How do different ad sizes compare in performance? Which ads are top-performing within each campaign?
stackadapt__url_report	Represents daily performance aggregated at the landing URL level, with URL components and UTM parameters parsed from click_url. Includes impressions, clicks, spend, and conversions. Example Analytics Questions: Which landing pages are driving the most conversions? How does performance compare across UTM campaigns and sources? Which URL paths have the highest spend relative to conversions?