Sync data from
Palantir Foundry to Apollo.io
Connect your data from Palantir Foundry to Apollo.io 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 Palantir Foundry, and 150+ destinations, like Apollo.io.
Define your model
Use SQL or select an existing dbt or Looker model.
Sync your data
Define how fields from your model map to Apollo.io, and start syncing.
Why is it valuable to sync Palantir Foundry data to Apollo.io?
Apollo.io is the backbone of your sales org. It's where you manage all of your contacts, accounts, and deals. The problem is that most of your CRM data has to be manually input by individual sales reps, so it doesn't show you an accurate 360-degree view of your customer. You only have access to basic information and historical interactions.
All of your Apollo.io data, in addition to the rich behavioral data captured through your app/website already, exists in Palantir Foundry. Most of the time, this includes core metrics your data team has defined around lifetime value, workspaces, subscriptions, playlists, average order value, last login date, etc. There's a high chance you're probably even consuming this data in a dashboard, and your sales reps can't answer key questions like:
- Which accounts have the highest lifetime value?
- Which users have the highest utilization in our product?
- When did user X last log in to the app?
- Which leads/accounts should I be prioritizing?
- Which accounts are at risk of churning?
- What is the average order value of account X?
Your sales team doesn't want to hop back and forth between your various SaaS tools to answer these questions. They want to take action in Apollo.io, and that means enriching your CRM with data directly from your warehouse.
Why should you use reverse ETL to connect Palantir Foundry and Apollo.io data?
Conventionally moving data from Snowflake to Apollo.io meant downloading ad hoc CSV files and uploading them manually or forcing your data team to integrate with the Apollo.io API and build and maintain custom pipelines. In reality, CSVs are not scalable, and in-house data pipelines and custom scripts break constantly.
Other point-to-point solutions create a weave complex web of pipelines to and from various SaaS applications and customer data platforms (CDPs), forcing you to pay for another layer of storage in addition to your data warehouses.
Reverse ETL solutions like Hightouch query against Snowflake and sync that data directly to Apollo.io. You don't have to worry about CSVs or APIs. You can leverage your existing tables, data models, and audience segments. All you have to do is define your data and map it to the appropriate columns in Apollo.io. You can schedule your syncs to run manually or even trigger them to run sequentially based on criteria that you define.
Hightouch automatically diffs data between syncs to ensure your only ever syncing the freshest data, and if any rows fail, Hightouch will automatically retry them later. A live debugger lets you analyze your API payload requests/responses and failed runs in real-time.
Sync to contacts to have an up-to-date contact list backed by your warehouse
Sync warehouse data to account to have the latest leads
About Palantir Foundry
Foundry was built and tested in crises when time matters most. It offers everything from data integration to applications that power decision-making, in hours.Learn more about Palantir Foundry
Search, engage, and convert over 265 million contacts at over 70 million companies with Apollo's sales intelligence and engagement platform.Learn more about Apollo.io
Other Palantir Foundry Integrations
Other Apollo.io 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.Read
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