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Sync data from
Amazon Redshift to Google Ads

Connect your data from Amazon Redshift to Google Ads with Hightouch. No APIs, no months-long implementations, and no CSV files. Just your data synced forever.

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Amazon Redshift.
Hightouch sync.
Google Ads.

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Integrate your data in 3 easy steps

  1. 01

    Add your source and destination

    Connect to 15+ data sources, like Amazon Redshift, and 140+ destinations, like Google Ads.

    Amazon Redshift.


    Connector beam.
    Google Ads.

    Log in

  2. 02

    Define your model

    Use SQL or select an existing dbt or Looker model.

    Define your model
  3. 03

    Sync your data

    Define how fields from your model map to Google Ads, and start syncing.

    Amazon Redshift.
    Connector beam.
    Google Ads.
    Amazon Redshift.


    Connector beam.
    Google Ads.


    Amazon Redshift.


    Connector beam.
    Google Ads.


    Amazon Redshift.


    Connector beam.
    Google Ads.


    Amazon Redshift.


    Connector beam.
    Google Ads.


Model your Amazon Redshift data using any of these methods

  • dbt Model Selector

    Semi-opaque, open dropdown with three example dbt model names such as ''.

    Sync directly with your dbt models saved in a git.

  • Looker

    Semi-opaque open dropdown with three example Look names such as 'look.1'.

    Query using looks. Hightouch turns your look into SQL and will pull from your source.

  • SQL Editor

    Empty SQL editor.

    Create and Edit SQL from your browser. Hightouch supports SQL native to Amazon Redshift.

  • Table Selector

    Semi-opaque open dropdown with three example table names such as ''.

    Select available tables and sheets from Amazon Redshift and sync using existing views without having to write SQL.

  • Customer Studio

    Visual query builder reading 'All rows that...' with a button labeled 'select a property'.

    For less technical users, pass traits and audiences from Amazon Redshift using our visual segmentation builder.

Where can you sync your Amazon Redshift 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.

    Hightouch docsGoogle Ads APIGoogle Ads support
  • 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 Amazon Redshift 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 Amazon Redshift data to Google Ads?

Thanks to Amazon Redshift, 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 Amazon Redshift. 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 Amazon Redshift 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 Amazon Redshift 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 Redshift and Google Ads

You have a few options on how to sync your data models, product usage data, event data, and audiences to Google Ads. Some options are more manual than others so we've outlined the 5 most common routes people take below:

Option 1: Reverse ETL (Hightouch)

With Reverse ETL solutions like Hightouch, you can easily sync data directly from your warehouse to Google Ads and any of your SaaS applications. Hightouch never stores your data either, so you don’t have to worry about any compliance issues. All you have to do is define your data in Redshift using SQL or your own custom data models and map the appropriate columns to Google Ads.

On top of this, your marketing team can even build custom audiences directly in the Hightouch UI using a simple drag and drop interface leveraging the data models your team has built within Redshift. Getting started is relatively simple and all you have to do is follow these steps:

Step 1: Connect to Your Data Source

Data Source.png

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.

Data Model.png

Step 4: Choose Your Primary Key

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

primary key.png

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.

column mappings.png

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

An easy way to move data from Redshift is simply by downloading specific a data set in the form of a CSV file and then uploading that file directly to Google Ads. This way of moving data creates several challenges though. Firstly, data stored in a CSV file becomes stale relatively quickly. In reality, Marketers want to test different audiences within Google Ads at a moment's notice.

This means that downloading specific data sets will not be a one-time ordeal. Every time your marketing team wants to test a new audience or campaign in Google Ads, you will be forced to download a specific data set. In an ideal world, you want your marketing team to be able to grab the customer data they need without ever having to go through your data team.

Option 3: Custom Integrations

Building a custom data pipeline from Redshift directly to Google Ads is one of the most efficient ways to move data into the platform. However, in-house data pipelines are extremely time-consuming to build and require heavy engineering resources. The APIs for Redshift and Google Ads are also constantly changing, which means you have to be on the lookout for upstream or downstream changes.

Depending on the amount of data that you are syncing to Google Ads, this could work for you, but scaling up this approach in the future is nearly impossible and building/maintaining more pipelines for additional Ad platforms like Twitter, Tiktok, etc., is nearly impossible.

Option 4: iPaaS (Integration Platform as a Service)

Point-to-point tools like Workato and Tray make it really easy to send data from one tool to another by enabling you to build custom workflows. However, these tools are better suited for automating tasks and processes between different SaaS applications. If your use case is simple, a tool like this could be a great option for moving data from Redshift to Google Ads because there is a relatively low barrier to entry.

However, if your needs are at all complex, you will find yourself writing custom code, and creating numerous if/then statements with tons of different dependencies in each intricate step of your workflow. Maintaining a workflow for all of your target destinations can be equally as challenging as building your own data pipeline in-house.

Option 5: CDPs (Customer Data Platform)

One of the most well-known options for moving data are CDPs. CDPs let you consolidate all of your customer data into a centralized platform where it can then be sent directly to Google Ads and other SaaS applications. The problem with CDPs is that they create another source of truth and they take your data out of your cloud environment, meaning that you no longer own it.

This can sometimes lead to compliance problems. CDPs can be a good option for some companies, but it's important to note that the average implementation time for a CDP is anywhere from six months to a year, so it can take a substantial amount of time to see any tangible results from your investment.

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
Amazon Redshift 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 Redshift. 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.

Amazon Redshift.

About Amazon Redshift

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is built on Amazon Web Services

Learn more about Amazon Redshift
Google Ads.

About 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 Ads

Other Amazon Redshift Integrations

Amazon Redshift to Zendesk

Hightouch Playbooks: Best practices to leverage reverse ETL

  • Manage Omnichannel Split Testing across Facebook and SFMC.

    Manage Omnichannel Split Testing across Facebook and SFMC

    This playbook will show you how to manage multivariate testing across Facebook and Salesforce Marketing Cloud with Hightouch Audiences.

  • Create Facebook Lookalike Audiences from High Value Users.

    Create Facebook Lookalike Audiences from High Value Users

    In this playbook, you will learn how to use Hightouch to sync an audience of high-value customers to Facebook to generate lookalike audiences.

  • Sync Nested Object Data to Braze.

    Sync Nested Object Data to Braze

    This playbook will help you understand how and why you should be leveraging nested object arrays in Braze to deeply personalize your omnichannel marketing campaigns.

Read more about Google Ads

  • The Marketers Guide to TikTok Conversion Tracking.

    The Marketers Guide to TikTok Conversion Tracking

    Maximizing TikTok ROI through a best-in-class integration strategy

  • The Definitive Guide to Conversion APIs & Web Pixels.

    The Definitive Guide to Conversion APIs & Web Pixels

    Facebook, Google, Snapchat, and Tiktok are adopting conversion APIs to capture data that web pixels and cookies can no longer collect. Here's an overview on how to adopt these new server-side advertising APIs.

  • How to Send Data from BigQuery to Google Ads.

    How to Send Data from BigQuery to Google Ads

    Learn how you can move data from BigQuery to Google Ads in 6 easy steps

  • How to send data from Snowflake to Google Ads.

    How to send data from Snowflake to Google Ads

    Learn how you can move data from Snowflake to Google Ads in 6 easy steps

Read more about Hightouch

  • What is Reverse ETL? The Definitive Guide .

    What is Reverse ETL? The Definitive Guide

    Learn everything there is to know about Reverse ETL, how it fits into the modern data stack, and why it's different than ETL.

  • What is Operational Analytics & Why You Should Use It.

    What is Operational Analytics & Why You Should Use It

    Operational Analytics shifts the focus from simply understanding data to taking action on it in the tools that run business processes. Instead of using dashboards to make decisions, Operational Analytics is focused on turning insights into action – automatically.

  • dbt Cloud: 4 Reasons for Data Teams to Embrace it.

    dbt Cloud: 4 Reasons for Data Teams to Embrace it

    The biggest benefit that dbt Cloud offers to data teams and analytics engineers? Freedom from distractions, and the ability to focus where you can add unique value making sense of your company's data.

Activate data to any of your marketing and advertising tools

See all integrations
Facebook Custom Audiences
Salesforce Marketing Cloud File Drop (Legacy)
Retention Science
Adobe Target
Salesforce Pardot (Sandbox)
Amazon Ads
Zoho CRM
Facebook Product Catalog
Austin Hay.
Ramp logo.

This might be one of the greatest inventions for technical marketers since the advent of legacy CDPs back in 2015.

Austin Hay

Austin Hay

Head of Marketing Technology



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Your data is always secure

Unlike other SaaS tools, Hightouch never stores any of your data.
SOC 2 Type 2 compliant.

SOC 2 Type 2 compliant

Your data stays secure, available, and confidential. To see our report, .

GDPR compliant.

GDPR compliant

If you’re in the EU, your data is only processed on EU data centers.

HIPAA compliant.

HIPAA compliant

Healthcare companies like ThirtyMadison, Chapter Health, and Headway trust Hightouch.

CCPA compliant.

CCPA compliant

To see our DPA (Data Processing Addendum), .


increase in return on ad spend


improvement in email engagement


lift in customer acquisition

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