Campaign Monitor is a SaaS email marketing platform that enables businesses to create, send, and manage branded email. The product includes a drag-and-drop builder, visual journey designer, and real-time performance metrics. It offers list management tools to help organizations build segmented lists based on their own criteria, and optimization tools to help users track the effectiveness of their campaigns.

Google BigQuery is a data warehouse that delivers super-fast results from SQL queries, which it accomplishes using a powerful engine dubbed Dremel. With BigQuery, there's no spinning up (and down) clusters of machines as you work with your data. With that said, it's clear why some claim that BigQuery prioritizes querying over administration. It's super fast, and that's the reason why most folks use it.

You can use Campaign Monitor's RESTful API to get data about clients, campaigns, lists, and more into your data warehouse. For example, to get a campaign summary, you could GET GET /campaigns/{campaignid}/summary.{xml|json}. The final parameter specifies whether the data is to be returned in XML or JSON format.

Here's an example of the kind of response you might see when querying a campaign summary and specifying that the data returned should be in JSON format.

{
    "Recipients": 1000,
    "TotalOpened": 345,
    "Clicks": 132,
    "Unsubscribed": 43,
    "Bounced": 15,
    "UniqueOpened": 298,
    "SpamComplaints": 23,
    "WebVersionURL": "http://createsend.com/t/y-A1A1A1A1A1A1A1A1A1A1A1A1/",
    "WebVersionTextURL": "http://createsend.com/t/y-A1A1A1A1A1A1A1A1A1A1A1A1/t",
    "WorldviewURL": "http://myclient.createsend.com/reports/wv/y/8WY898U9U98U9U9",
    "Forwards": 18,
    "Likes": 25,
    "Mentions": 11
}

Google Cloud Platform offers a helpful guide for loading data into BigQuery. You can use the bq command-line tool to upload the files to your awaiting datasets, adding the correct schema and data type information along the way. The bq load command is your friend here. You can find the syntax in the bq command-line tool quickstart guide. Iterate through this process as many times as it takes to load all of your tables into BigQuery.

Now what? You've built a script that pulls data from Campaign Monitor and loads it into your data warehouse, but what happens tomorrow when you have new campaigns?

The key is to build your script in such a way that it can identify incremental updates to your data. Thankfully, Campaign Monitor's API results include fields like Date that allow you to identify records that are new since your last update (or since the newest record you've copied). Once you've take new data into account, you can set your script up as a cron job or continuous loop to keep pulling down new data as it appears.

BigQuery is great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Amazon Redshift, PostgreSQL, Snowflake, or Microsoft Azure Synapse Analytics, which are RDBMSes that use similar SQL syntax, or Panoply, which works with Redshift instances. Others choose a data lake, like Amazon S3 or Delta Lake on Databricks. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To Postgres, To Snowflake, To Panoply, To Azure Synapse Analytics, To S3, and To Delta Lake.