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Add your source and destination
Connect to 15+ data sources, like ClickHouse, and 125+ destinations, like Facebook Product Catalog.
Define your model
Use SQL or select an existing dbt or Looker model.
Sync your data
Define how fields from your model map to Facebook Product Catalog, and start syncing.
Model your ClickHouse data using any of these methods
Create and Edit SQL from your browser. Hightouch supports SQL native to ClickHouse.
Why is it valuable to sync ClickHouse data to Facebook Product Catalog?
Thanks to ClickHouse, 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 Facebook Product Catalog, 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 ClickHouse. You then need to be able to package this data to send to Facebook Product Catalog in the format expected. Plus, you want to do this in a real-time and automated way.
Facebook Product Catalog 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 ClickHouse 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 ClickHouse and Facebook Product Catalog data?
In the past, uploading customer data to Facebook Product Catalog 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 Facebook Product Catalog 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.
Insert products into your product catalog directly from your data warehouse
Keep your product data up to date and delete products automatically when they leave your warehouse
ClickHouse is a fast open-source column-oriented database management system that allows generating analytical data reports in real-time using SQL queries.Learn more about ClickHouse
About Facebook Product Catalog
Use the Facebook Product Catalog API to send product information and keep your catalogs in Facebook up to date.Learn more about Facebook Product Catalog
Other ClickHouse Integrations
Other Facebook Product Catalog Integrations
Hightouch Playbooks: Best practices to leverage reverse ETL
Read more about Hightouch
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.
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This might be one of the greatest inventions for technical marketers since the advent of legacy CDPs back in 2015.
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increase in return on ad spend
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