Freshchat + BigQuery
Freshchat is a messaging and live chat platform designed to streamline communication between businesses and customers. BigQuery, in turn, is a serverless Big Data solution developed by Google that offers robust large-scale data storage and analytics capabilities.
With Erathos, you can integrate Freshchat data into BigQuery in just a few minutes. Our platform handles the entire data movement process from Freshchat to your analytics environment and makes it easy to combine that data with other sources in your Data Warehouse. That way, your time goes toward what truly creates value — extracting actionable insights and making more data-driven decisions.
Which Freshchat data does Erathos sync with BigQuery?
The integration automatically syncs Freshchat's core objects:
Tickets — status, priority, assignee, and resolution time
Interactions — messages, replies, and conversation history
Agents — individual performance and support workload
SLAs — compliance, breaches, and metrics by category
CSAT — satisfaction ratings and customer comments
Tags and categories — contact reason taxonomy
Why sync Freshchat with BigQuery?
Freshchat data reveals what your customers need — but it lives separately from product, marketing, and finance data. In BigQuery, you can correlate ticket volume with churn, calculate the true cost of support by segment, and identify which features are driving the most support before they turn into critical issues.
How it works
Erathos connects to Freshchat via the official API and syncs data incrementally — only new or updated records are processed on each run, keeping pipelines fast and BigQuery costs predictable. You choose the sync frequency (from every 5 minutes to daily), which objects to sync, and the target dataset. Each run is fully observable: execution time, rows processed, contextual errors, and instant alerts via Slack or email if anything goes wrong.
No credit card required.
Why do data teams choose Erathos for Freshchat?
Freshchat connector ready to use
Connect Freshchat to BigQuery in minutes. Tickets, interactions, SLAs, and agent data are automatically synced—ready for analysis with no manual processing.
Total control over your Freshchat pipelines
Configure schedule, frequency, and sync type at the table level. Incremental synchronization processes only new or modified records—keeping BigQuery costs low and your analyses always up to date.
End-to-end observability
No more finding out about Freshchat failures when the business team complains. Every run is logged with execution time, processed rows, and error context. Automatic alerts via Slack, Discord, or email as soon as anything deviates from expected behavior — SLAs and satisfaction metrics always stay up to date.
Why companies are moving data from Freshchat to BigQuery with Erathos
Centralizing Freshchat data in BigQuery has never been easier.
Erathos is a data ingestion platform for support and data teams. With the Freshchat connector, you can automatically centralize tickets, interactions, SLAs, and support data in BigQuery—support data always available for analysis and dashboards.
Our Customers
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Simplified data ingestion
1
Select your data source
More than 80 plug-and-play connectors to consolidate data from multiple sources, eliminate time-consuming manual processes, and create a streamlined path forward.
2
Setup your pipeline
Manage your pipeline seemlessly. Select a sync hour, frequency and type at a table/endpoint level.
3
Select your data warehouse
Choose between Amazon S3, BigQuery, Databricks, Redshift and PosgreSQL to centrlize your data
FAQ
What is Erathos and how can it help my company?
Erathos is a data ingestion platform built for reliability, transparency, and control. We help data teams connect tools like Freshchat to their data warehouse—with full observability into every pipeline run, zero maintenance, and none of the black-box opacity of traditional market tools.
What Freshchat data does Erathos sync to BigQuery?
Erathos syncs Tickets, Interactions, Agents, SLAs, Tags, and Customer Satisfaction Ratings (CSAT) from Freshchat to BigQuery. Custom ticket fields and support categories are also exported automatically.
How often does Erathos synchronize data from Freshchat to BigQuery?
You can configure the sync frequency from every 5 minutes up to daily at the table level. Erathos uses incremental synchronization—only new or updated records are processed in each run, keeping the Freshchat pipeline efficient and BigQuery costs predictable.
What happens if a Freshchat synchronization fails?
Erathos automatically detects failures and sends alerts to your email, Slack, or Discord with full context—not just "job failed." Smart retries handle transient errors, and every execution is logged with run time, processed rows, and error context so your team can debug in minutes, not hours.
Is there a free trial period for the Freshchat connector?
Yes. Every Erathos connector includes a 14-day free trial. Connect Freshchat to BigQuery and start syncing immediately—no credit card required.