Sync data from
MongoDB to Google Ads
Connect your data from MongoDB 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
Add your source and destination
Connect to 15+ data sources, like MongoDB, and 150+ destinations, like Google Ads.
Define your model
Use SQL or select an existing dbt or Looker model.
Sync your data
Define how fields from your model map to Google Ads, and start syncing.
Where can you sync your MongoDB 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.
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.
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.
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.
Why is it valuable to sync MongoDB data to Google Ads?
Thanks to MongoDB, 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 MongoDB. 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 MongoDB 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 MongoDB 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.
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
MongoDB is a document database with the scalability and flexibility that you want with the querying and indexing that you needLearn more about MongoDB
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 MongoDB Integrations
Other Google Ads integrations
Hightouch Playbooks: Best practices to leverage reverse ETL
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increase in return on ad spend
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lift in customer acquisition