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Add your source and destination
Connect to 15+ data sources, like Firebolt, and 125+ destinations, like Pipedrive.
Define your model
Use SQL or select an existing dbt or Looker model.
Sync your data
Define how fields from your model map to Pipedrive, and start syncing.
Model your Firebolt 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 Firebolt.
Select available tables and sheets from Firebolt and sync using existing views without having to write SQL.
Why is it valuable to sync Firebolt data to Pipedrive?
Pipedrive 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 Pipedrive data, in addition to the rich behavioral data captured through your app/website already, exists in Firebolt. 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 Pipedrive, and that means enriching your CRM with data directly from your warehouse.
Why should you use reverse ETL to connect Firebolt and Pipedrive data?
Conventionally moving data from Snowflake to Pipedrive meant downloading ad hoc CSV files and uploading them manually or forcing your data team to integrate with the Pipedrive 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 Pipedrive. 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 Pipedrive. 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.
Push lead info from your warehouse into Pipedrive to enable executives to go after the right accounts
Push product data to enable account managers to know what actions are being taken in the app
Enable account executives to create more relevant and timely outbound campaigns
Deliver production grade data applications & analytics with Firebolt - the cloud data warehouse for modern data engineering & dev teamsLearn more about Firebolt
Founded in 2010, Pipedrive is the first CRM platform developed from the salesperson’s POV.Learn more about Pipedrive
Other Firebolt Integrations
Other Pipedrive 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.
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
improvement in email engagement
lift in customer acquisition