Sync data from
Databricks to Facebook Product Catalog
Connect your data from Databricks to Facebook Product Catalog with Hightouch. No APIs, no months-long implementations, and no CSV files. Just your data synced forever.
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Integrate your data in 3 easy steps
Add your source and destination
Connect to 15+ data sources, like Databricks, and 140+ 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 Databricks data using any of these methods
dbt Model Selector
Sync directly with your dbt models saved in a git.
Create and Edit SQL from your browser. Hightouch supports SQL native to Databricks.
Select available tables and sheets from Databricks and sync using existing views without having to write SQL.
For less technical users, pass traits and audiences from Databricks using our visual segmentation builder.
Does this integration support in-warehouse planning?
Yes, if you integerate Databricks and Facebook Product Catalog 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 Facebook Product Catalog). 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 Databricks data to Facebook Product Catalog?
Thanks to Databricks, 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 Databricks. 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 Databricks 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 Databricks 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
Databricks is a data science and analytics platform built on top of Apache Spark. Databricks implement the Data Lakehouse concept in a single unified, cloud based platform.Learn more about Databricks
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 Databricks Integrations
Other Facebook Product Catalog integrations
Hightouch Playbooks: Best practices to leverage reverse ETL
Read more about Hightouch
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Activate data to any of your marketing and advertising tools
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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