Sync data from
Snowflake to Google Ads
Connect your data from Snowflake to Google Ads with Hightouch. No APIs, no months-long implementations, and no CSV files. Just your data synced forever.
Trusted by data teams at
Trusted by data teams at







Integrate your data in 3 easy steps
01
Add your source and destination
Connect to 15+ data sources, like Snowflake, and 150+ destinations, like Google Ads.
Connect
Log in
02
Define your model
Use SQL or select an existing dbt or Looker model.
03
Sync your data
Define how fields from your model map to Google Ads, and start syncing.
email
email
name
name
total_orders
all_orders
last_login
last_login
Model your Snowflake data using any of these methods
dbt Model Selector
Sync directly with your dbt models saved in a git.
Looker
Query using looks. Hightouch turns your look into SQL and will pull from your source.
SQL Editor
Create and Edit SQL from your browser. Hightouch supports SQL native to Snowflake.
Table Selector
Select available tables and sheets from Snowflake and sync using existing views without having to write SQL.
Customer Studio
For less technical users, pass traits and audiences from Snowflake using our visual segmentation builder.
Where can you sync your Snowflake data in Google Ads
Customer Match (User) Lists
Customer Match lets you target ads to your customers using the data they share with you. You can upload it into Google Ads to incorporate this targeting into your campaigns.
Call Conversions
Phone call conversion tracking helps you track when your ads lead to different kinds of phone calls. By importing call conversion information into Google Ads, you can track when phone calls lead to sales or other valuable customer actions. To learn how to import phone call conversions, refer to Import phone call conversions.
Enhanced Conversions
Using the Google Ads API, you can leverage enhanced conversions by sending first-party customer data in the form of conversion adjustments. Google uses this additional data to improve the reporting of your online conversions driven by ad interactions.
Offline (Store) Conversions
Sometimes, an ad doesn't lead directly to an online sale, but instead starts a customer down a path that ultimately leads to a sale in the offline world, such as at your office or over the phone. By importing offline conversions, you can measure what happens in the offline world after your ad results in a click or call to your business.
Conversion Adjustments
A customer's typical conversion path ends after they convert, but this isn't always the case. Customers return retail purchases, cancel reservations, or perform actions that increase their value to your business. To account for these changes in conversion value, you can adjust the value of a conversion after it's reported in Google Ads.
Does this integration support in-warehouse planning?
Yes, if you integerate Snowflake and Google Ads using Hightouch, in-warehouse planning is supported.
Great, but what is in-warehouse planning?
Between every sync, Hightouch notices any and all changes in your data model. This allows you to only send updated results to your destination (in this case Google Ads). With the baseline setup, Hightouch picks out only the rows that need to be synced by querying every row in your data model before diffing using Hightouch’s infrastructure.
The issue here is this can be slow for large models.
Warehouse Planning allows Hightouch to do this diff directly in your warehouse. Read more on how this works here.
Why is it valuable to sync Snowflake data to Google Ads?
Thanks to Snowflake, it's easier than ever to access your customer data, run complex queries, and segment your customers/users into various categories or audiences.
However, to target users and send conversion data to Google Ads, you need access to all of the unique behavioral data (e.g., last-login date, items in cart, pages viewed, etc.) and core business metrics like lifetime value, workspaces, subscriptions, annual recurring revenue, etc. that lives in Snowflake. You then need to be able to package this data to send to Google Ads in the format expected. Plus, you want to do this in a real-time and automated way.
Google Ads is only as good as the data you give them, and if you truly want to optimize your ad spend, increase your match rates, and drive conversions, you need to provide custom data from Snowflake within your warehouse.
Maybe you want to retarget users who abandoned their shopping cart in the last seven days, or upload a list of high-value customers to identify potential lookalike audiences, or perhaps you want to upload offline conversion events to reduce your customer acquisition costs and increase your return on ad spend.
Why should you use reverse ETL to connect Snowflake and Google Ads data?
In the past, uploading customer data to Google Ads meant hopping back and forth between your various SaaS applications or asking your data team for CSV files. Neither of these options is preferable because marketing teams want to self-serve, and data teams don't enjoy constantly fulfilling one-off marketing requests.
Even worse, if you truly want to optimize your advertising campaigns, you need to be uploading fresh data consistently. Non-fresh data can be expensive for ads. If you're using CSVs to define who to exclude from paid ads and you're uploading that data weekly, that's potentially one week of irrelevant ads. As a workaround, engineering teams will integrate directly with the Google Ads API, and build and maintain custom in-house pipelines. The problem is that a single API change can break everything, and data engineers don't want to spend their time building and maintaining pipelines.
With Hightouch, you can leverage the existing data models and customer segments your engineering team has defined in your warehouse and sync that data directly to your ad platforms in real time. You can schedule your data syncs to run automatically, on a set cadence, or even for the exact duration of your marketing campaign. Hightouch lets your data teams establish the guardrails for your marketers to self-serve and build custom audiences through a drag-and-drop interface.
How to integrate Snowflake and Google Ads
We've outlined the 5 easiest options you have to activate your Snowflake data and get it into Google Ads for targeting, suppression, and conversion tracking.
Option 1: Reverse ETL (Hightouch)
Reverse ETL tools like Hightouch run on top of Snowflake. This means you can sync data directly from Snowflake to Google Ads in real-time, without having to worry about any data pipelines, CSV files, or complicated workflows. All you have to do is define your data using SQL or use your existing models and map that information to the appropriate columns in Google Ads.
Hightouch does not store any data, so you don’t have to worry about any compliance issues. Instead, you can solely focus on syncing your data from your cloud data warehouse to Google Ads. Hightouch also provides an intuitive interface for your non-technical users so they can create custom audiences directly within the platform using the data models your team has already built-in Snowflake. Reverse ETL is surprisingly simple and only takes a few minutes to set up if you follow these steps.
Step 1: Connect to Your Data Source

Step 2: Connect Hightouch to Your Destination

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 Google Ads is to simply download a manual CSV file. This poses two main challenges though. Firstly, it’s not a one-time data pull. Your engineering 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 Google Ads requires you to build a custom in-house data pipeline. The APIs for Snowflake and Google Ads are constantly changing though, 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 advertising platforms in the future (ex: Tiktok, Facebook, Twitter, etc.).
Option 4: iPaaS (Integration Platform as a Service)
Another way to move data from Snowflake to Google Ads 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 Google Ads. 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.
Upload lists to Google Ads to run ads based on certain attributes within your database, such as people who have visited your site
Run lookalike audiences on Google Ads using subsets of your users rather than all of them
Continuously fuel your Google Ads custom audiences with live data so that data never goes stale
Why sync data from
Snowflake to Google Ads?
Every company advertises through Google Ads regardless of size or industry. Advertising is expensive though, and figuring out how to increase ROAS, lower CAC, and improve campaign performance is extremely important. All of your unique customer data (e.g. product usage data, key events, custom audiences, etc.) lives in Snowflake. However, custom integrations are prone to failure and manual CSV files become stale really fast. To truly take your marketing campaigns to the next level, your marketing team needs to be able to self-serve and sync custom audiences to Google Ads at a moment’s notice.
About Snowflake
Snowflake is a managed cloud data warehouse that helps you consolidate and aggregate your data into a single, centralized platform to tackle analytics use cases. These workloads include data warehousing, data lakes, data engineering, application development, data sharing, and business intelligence.
Learn more about SnowflakeAbout Google Ads
Google Ads remarketing allows you to advertise to people who have previously visited your website, used your mobile app, or who are in your CRM databases, by showing them relevant ads when they visit other sites or search on Google. The user lists used in remarketing can also be used for other types of audience targeting, such as Customer Match.
Learn more about Google AdsOther Snowflake Integrations
Other Google Ads integrations
Hightouch Playbooks: Best practices to leverage reverse ETL
Read more about Google Ads
Read more about Hightouch
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This might be one of the greatest inventions for technical marketers since the advent of legacy CDPs back in 2015.
Austin Hay
Head of Marketing Technology
•
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Your data stays secure, available, and confidential. To see our report, .
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HIPAA compliant
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CCPA compliant
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52%
increase in return on ad spend
20%
improvement in email engagement
60%
lift in customer acquisition