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Add your source and destination
Connect to 15+ data sources, like ClickHouse, and 125+ destinations, like Zoho CRM.
Define your model
Use SQL or select an existing dbt or Looker model.
Sync your data
Define how fields from your model map to Zoho CRM, 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 Zoho CRM?
Zoho CRM 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 Zoho CRM data, in addition to the rich behavioral data captured through your app/website already, exists in ClickHouse. 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 Zoho CRM, and that means enriching your CRM with data directly from your warehouse.
Why should you use reverse ETL to connect ClickHouse and Zoho CRM data?
Conventionally moving data from Snowflake to Zoho CRM meant downloading ad hoc CSV files and uploading them manually or forcing your data team to integrate with the Zoho CRM 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 Zoho CRM. 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 Zoho CRM. 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 Zoho CRM 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
Sync your sales data to Zoho CRM to give your decision makers accurate data from across your organization using analytics and reports so they can react to market trends with better decisions
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 Zoho CRM
Zoho CRM is an online Sales CRM software that acts as a single repository to bring your sales, marketing, and customer support activities together, and streamline your process, policy, and people in one platform.Learn more about Zoho CRM
Other ClickHouse Integrations
Other Zoho CRM 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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