Sync data from
Snowflake to Iterable

If Snowflake is your source of truth for your business, why would you not want all of that data in Iterable where your marketing team is creating messages to send to your customers? It makes sense on paper, but sending Snowflake data to Iterable can be challenging and complicated. Don't worry, this is our specialty. We've outlined the 5 main options to integrate and move data between Snowflake and Iterable (or any other SaaS tool).

Option 1: Reverse ETL with Hightouch

For fully automated data syncs from Snowflake to Iterable, Reverse ETL is the best option because it's not only the easiest to set up, it's also the easiest to use, monitor, and train new employees on. Instead of dealing with manual CSV files, third-party APIs, or custom code, Reverse ETL syncs data directly from your warehouse to your operational tools like Iterable.

The other great benefit of reverse etl is that Hightouch never stores your data. If you go with a CDP, like Segment, you are paying to have your data stored in Snowflake and then again in Segment. This also creates multiple sources of truth — thus a headache for everyone involved. Hightouch is a SaaS platform, which means you don't have to install anything locally on your computer. Also, your first destination with Hightouch is free, so this is also the most economical option.

With Hightouch, you can leverage all of your existing Snowflake tables and data models and sync that data directly to over 125 different destinations. You can run your data syncs manually or schedule them on a set cadence that you define (e.g., after your transformation jobs finish running in Snowflake.) 90% of all Hightouch syncs finish within 30 seconds, and this includes millions of records. There’s even a visual audience builder for non-technical users.

We've outlined the 5 easiest options you have to activate your Snowflake data and get it into Iterable for targeting, suppression, and conversion tracking.

Step 1: Connect to Your Data Source

Step 2: Connect Hightouch to Iterable

Step 3: Create a Data Model or Leverage an Existing One

You can use SQL to define your data directly in the Hightouch UI or even leverage your existing data models.

Step 4: Choose Your Primary Key

With Hightouch you can map on any unique key, not just users and accounts.

Step 5: Create Your Sync

Once you have created your sync, you simply have to choose the appropriate columns and map them to the fields in your end destination.

Step 6: Schedule Your Sync

Once your sync is created you can run it manually, define a set interval, or schedule it to run after a dbt job is completed.

The first integration with Hightouch is completely free so you can actually get started today. If you want to learn more about Reverse ETL, download our guide.

Option 2: Manual CSV Files

The easiest way to move data from Snowflake to Iterable is to simply download a manual CSV file. This poses two main challenges though. Firstly, it’s not a one-time data pull. Your data team has to download a new data set every time your marketing team wants to target a different audience or run a different experiment.

On top of this, data stored in a CSV file becomes stale and unusable really quickly. In almost every scenario your marketing team wants the real-time data or the closest thing to it, so they can iterate at a moment’s notice and make better business decisions. When your engineering team is forced to fulfill constant Adhoc requests it pulls away from the jobs they should actually be doing.

Option 3: Custom Integrations

In most cases moving data from Snowflake to Iterable requires you to build a custom in-house data pipeline. Like with any SaaS platform, the APIs for Snowflake and Iterable are constantly changing, so maintaining a homegrown data integration pipeline can be quite challenging, and even getting a modern data pipeline up and running takes a substantial amount of time and resources.

Depending on the size of your organization, this could be doable, but maintaining this at any sort of scale quickly becomes an impossible feat, especially if you need to build more pipelines to additional platforms in the future (ex: Tiktok, Facebook, Twitter, Salesforce, Amplitude, etc.).

Option 4: iPaaS (Integration Platform as a Service)

Another way to move data from Snowflake to Iterable is through the usage of iPaaS solutions. Tools like Workato and Tray provide you with a relatively simple platform where you can build custom workflows to move data from one tool to another.

The problem is, these tools are really designed to handle simple use cases and automate repetitive tasks, so if you go beyond simple use cases, you will be stuck building complicated workflows with numerous if/then branches, all with various dependencies within each step.

Option 5: CDPs (Customer Data Platform)

CDPs do a decent job at moving your data from point “A” to “B” because they are marketing platforms that consolidate all of your customer data into a centralized platform, where that same data can be ingested in various other tools like Iterable. There is a problem though, CDPs don’t necessarily play nicely with your existing technology stack and create another source of truth.

Additionally, CDPs own your data since it is no longer in your own cloud environment. Figuring out how to move your data into a CDP can be equally as challenging as building an in-house data pipeline. In addition to this, the typical implementation time for a CDP can take well over a year.