MeetRoxBigQuery

MeetRox + BigQuery

MeetRox is an AI platform for Sales and Customer Success (CS) that optimizes conversations, automatically fills in CRMs, and analyzes meetings to improve team productivity and drive revenue. MeetRox records, transcribes, and analyzes interactions (calls and meetings) to deliver insights into pitch quality, common objections, customer behavior, and team performance.

With Erathos, you can integrate MeetRox data into BigQuery in just a few minutes. Our platform handles the entire data movement process into your analytics environment and lets you combine that data with other sources in your data warehouse. That way, your time goes to what actually creates value — extracting actionable insights and making more data-driven decisions.

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Linus
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Auvo
Roqt
Xperiun
Tecnova
WePayments
Brick
CCM
Simplified extraction and ingestion

Move data in a few clicks

1

Connect your source

Authenticate your account and you're done. 100+ ready-made connectors, no code required.

2

Configure the sync

Pick the tables, the schedule and the update type: batch, cursor-based incremental or CDC.

3

Choose your destination

Load into BigQuery, Redshift, Databricks, PostgreSQL, ClickHouse, Amazon S3 and more.

Which MeetRox data does Erathos sync with BigQuery?

The integration automatically syncs MeetRox's core objects:

  • Tickets — status, priority, owner, 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 feedback
  • Tags and categories — taxonomy of contact reasons

Why sync MeetRox with BigQuery?

MeetRox data shows what your customers need — but it's isolated 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 generate the most support before they turn into critical issues.

How it works

Erathos connects to MeetRox via the official API and syncs your data incrementally — only new or updated records are processed in 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 destination dataset. Every run is logged with full observability: execution time, rows processed, context-rich errors, and instant alerts via Slack or email if anything goes wrong.

Why Companies Move Data from MeetRox to BigQuery with Erathos

Centralizing MeetRox data in BigQuery has never been easier

Erathos is a data ingestion platform for support and data teams. With the MeetRox connector, you can automatically centralize tickets, interactions, SLAs, and support data in BigQuery — keeping support data always available for analysis and dashboards.

Why do data teams choose Erathos for MeetRox?

Data in your data warehouse in minutes

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Building data-driven stories

Every new source implementation, if I had to do it myself, would take about two or three months. With Erathos, it's done in a few hours. I don't need the skills of a data engineer to generate real value from the company's data.

Bruno Rosso
Bruno RossoData Analyst, Brick Software

Erathos revolutionized data management at WE. By integrating multiple SaaS tools into a single DW, our technical team now focuses on the core business. We implemented dashboards with insights across every area, enriching our organizational culture and improving our decision-making.

Matheus Nunes
Matheus NunesCTO & co-founder, WePayments

We used to have a lot of rework, and now we don't. It's more efficient to work this way. If it's not your core business, hire Erathos. Spend your time modeling your own domain, not someone else's.

Carlos Schwabe
Carlos SchwabeCo-Founder & CDO, Brick

If I didn't have this infrastructure, I'd need three or four people to do what Erathos does today. I was able to generate real value from my data with a much leaner setup than I thought I'd need. That's the core of building a data-driven culture: the team only uses data when they can trust it.

Thiago Paz
Thiago PazCFO, Brick

Erathos brought a practical turnaround at CCM. We were able to integrate financial systems, CRM, and processes with BigQuery in just a few clicks, with no technical team required. That gave us a reliable data warehouse that powers automations, dashboards, and even our customer service bots.

Gustavo Loforte
Gustavo LoforteTechnology Manager, CCM Group

The robustness and efficiency of Erathos's connectors — whether for Meta, Google, RD Station, or ERPs like Bling and Conta Azul — make the whole process much faster and more reliable. The technical documentation is extremely well put together and intuitive, which makes implementation much easier.

Sayuri Valente
Sayuri ValenteProject Manager, Xperiun
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FAQ

Frequently Asked Questions

Erathos is a data ingestion platform built for reliability, transparency, and control. We help data teams connect tools like MeetRox to their data warehouse — with full observability into every run, zero maintenance, and none of the black-box opacity of traditional market tools.

Erathos syncs tickets, interactions, agents, SLAs, tags, and customer satisfaction ratings (CSAT) from MeetRox to BigQuery. Custom ticket fields and support categories are also exported automatically.

You can configure sync frequency anywhere from every 5 minutes to once a day, at the table level. Erathos uses incremental sync — only new or updated records are processed in each run, keeping the MeetRox pipeline efficient and BigQuery costs predictable.

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.

Yes. Every Erathos connector includes a 14-day free trial. Connect MeetRox to BigQuery and start syncing right away — no credit card required.

Data ingestion with control, observability and scale