Freshchat + BigQuery
Freshchat is a messaging and live chat platform designed to make communication between businesses and customers easier.
With Erathos, you can integrate Freshchat data into BigQuery in just a few minutes. Our platform handles the entire data movement process to your serverless data warehouse and lets you join that data with other sources. That way, your time goes where it really creates value — extracting insights and making data-driven decisions.
What Freshchat data does Erathos sync to BigQuery?
The integration automatically syncs Freshchat’s main objects:
Tickets and support cases — status, priority, channel, and response time
Contacts and customers — interaction history and account details
Agents — workload, SLA, and performance metrics
Categories and tags — classifications and opening reasons
Satisfaction (CSAT) — scores, comments, and timestamps
SLA and metrics — resolution time, first response time, and escalations
Why sync Freshchat with BigQuery?
In BigQuery, you can combine this data with product, revenue, and customer satisfaction metrics — joining sources with standard SQL and pay-per-query billing. Native integration with Looker Studio, Vertex AI, and BQML enables advanced analytics without extra infrastructure.
How it works
Erathos connects to Freshchat via the official API and syncs your data incrementally — only new or updated records are processed on each run. You choose the sync frequency (from every 5 minutes to daily), the objects to sync, and the destination in BigQuery. The sync uses incremental processing so only new or updated records are handled — keeping BigQuery costs predictable. You choose the sync frequency, the objects to sync, and the target dataset. Each run is logged with full observability: runtime, rows processed, and alerts via Slack or email.
No credit card required.
Why do data teams choose Erathos for Freshchat?
Ready-to-use Freshchat connector
Connect Freshchat to BigQuery and automatically export data. Centralize customer support data for analysis — no spreadsheets and no scripts.
Full control over your Freshchat pipelines
Configure sync schedule, frequency, and sync type at the table level. Configure sync schedule, frequency, and sync type at the table level. Incremental sync processes only new or changed records, keeping BigQuery costs low and your analytics always up to date.
End-to-end observability
No more finding Freshchat issues only after the business team complains. Every run is logged with run time, processed rows, and error context. Automatic alerts via Slack, Discord, or email as soon as something goes off expected — so your data stays fresh for analysis.
Why companies move data from Freshchat to BigQuery with Erathos
Centralizing Freshchat data in BigQuery has never been this easy
Erathos is a data ingestion platform built for support and data teams. With the Freshchat connector, you automatically centralize conversations, tickets, and support metrics in BigQuery — always up-to-date data, full observability into every run, and zero maintenance.
Our Customers
Trusted by data-driven companies
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 business?
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 run, zero maintenance, and none of the black-box behavior you get with traditional market tools.
What Freshchat data does Erathos sync to BigQuery?
Erathos syncs Freshchat tickets, conversations, agents, response times, SLAs, and customer satisfaction with your Data Warehouse, enabling comprehensive support analytics.
How often does Erathos sync data from Freshchat to BigQuery?
You can configure sync frequency from every 5 minutes up to daily, at the table level. Erathos uses incremental sync — only new or updated records are processed in each run, keeping the Freshchat pipeline efficient and BigQuery costs predictable.
What happens if a Freshchat sync 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 run is logged with runtime, rows processed, 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 right away — no credit card required.