No-code pipeline · Huggy → BigQuery

Send data from Huggy to BigQuery

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From Huggy to BigQuery: managed, scheduled, no code.

Kondado automatically replicates data from Huggy to BigQuery on a configurable schedule, offering four pipelines including Agents, Contacts, Chats, and Chat Satisfaction Surveys with 33 total fields, enabling comprehensive analytics of your omnichannel communication data.

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Huggy to BigQuery: Automated Data Replication

To send Huggy data to BigQuery, connect your Huggy account as a data source and select BigQuery as your destination. Kondado provides a direct integration that replicates your customer communication data without requiring any coding or manual exports. The platform handles the data extraction and loading automatically, allowing you to focus on analysis rather than data engineering. Once connected, your Huggy data flows into BigQuery on your chosen schedule, making it immediately available for SQL queries and business intelligence tools.

With your Huggy data in BigQuery, you can combine communication metrics with other business data sources to create unified reports. This allows marketing teams and support managers to track lead engagement, agent performance, and customer satisfaction trends using familiar SQL-based analytics workflows.

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The Agents and Contacts pipelines deliver essential workforce and customer data directly into your BigQuery warehouse. Analyze agent productivity metrics alongside contact engagement histories to identify your highest-performing team members and most valuable leads. With the Chats pipeline, you can build custom SQL queries to track conversation volumes, response times, and resolution patterns across all your omnichannel touchpoints. Combine these datasets with the Chat Satisfaction Surveys pipeline to create comprehensive performance dashboards that reveal correlations between agent assignments, customer feedback scores, and conversion rates.

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Replicated to BigQuery

Huggy data available for BigQuery

Tables Kondado writes into your BigQuery, on a schedule you control.

available pipelines

extractable fields

BigQuery

Destination

Available integrations

Agents

Table contains information about agents, including fields such as id, name, and department.

Contacts

Table presents contacts with fields such as id, name, phone, and email, enabling efficient lead management.

Chats

Table records chat details, including id, contactid, agentid, and timestamps such as createdat and closedat.

Chat Satisfaction Surveys

Table contains chat feedback, with fields such as chat_id, feedback_score, and feedback_text, allowing satisfaction analysis.

See all available data → Send Huggy to BigQuery →

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How to send Huggy data to BigQuery

Sync data automatically — no code, no manual exports.

Connect Huggy as Data Source

Authenticate your Huggy account through Kondado's interface to establish the initial connection and enable data extraction from your omnichannel communication platform.

Configure BigQuery Destination

Set up BigQuery as your target warehouse by providing your Google Cloud project details, ensuring your Huggy data has a dedicated destination for storage and analysis.

Select Pipelines and Schedule

Choose which Huggy pipelines to replicate, such as Agents, Contacts, or Chats, and define your preferred update frequency to automate the data flow into BigQuery.

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Send data from Huggy to other destinations

Huggy > Looker Studio

Huggy > Power BI

Other visualizations

Huggy > Amazon S3

Huggy > BigQuery

Huggy > Excel

Huggy > Google Sheets

Huggy > MySQL

Huggy > PostgreSQL

Huggy > Redshift

Huggy > SQL Server

Choose a tool to visualize your Huggy data

If the software you need is not listed, drop us a messagem. You can use almost every tool

Huggy > Airtable

Huggy > Alteryx

Huggy > Amazon Quicksight

Huggy > BIMachine

Huggy > Cortex

Huggy > Data Studio

Huggy > Geckoboard

Huggy > Grafana

Huggy > IBM Cognos Analytics

Huggy > Klipfolio

Huggy > Looker Studio

Huggy > Looker

Huggy > Looqbox

Huggy > Metabase

Huggy > Microstrategy

Huggy > Pentaho

Huggy > Power BI

Huggy > Qlik Cloud Analytics

Huggy > Qlik Sense

Huggy > Qlik

Huggy > QlikView

Huggy > Redash

Huggy > Superset

Huggy > Tableau

Huggy > BI TOTVS

Huggy > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending Huggy data to BigQuery automatically

How often does Huggy data update in BigQuery? ▼

Kondado updates your Huggy data on a configurable schedule that you control, with options ranging from every 5 minutes to daily intervals. This automated approach ensures your BigQuery warehouse contains current information for time-sensitive analytics without manual intervention. You can adjust the frequency based on your reporting needs and data volume requirements.

What specific Huggy data can I replicate to BigQuery? ▼

Kondado offers four distinct pipelines that replicate 33 fields from your Huggy account, including agent profiles, contact details, chat transcripts, and satisfaction survey responses. This covers your complete omnichannel communication dataset, enabling comprehensive analysis of both customer interactions and team performance metrics within your data warehouse.

Can I combine Huggy data with other marketing tools in BigQuery? ▼

Yes, BigQuery serves as a central repository where Huggy communication data can be joined with information from additional sources such as your CRM, advertising platforms, or e-commerce systems. This unified approach enables cross-channel analysis that correlates customer support interactions with marketing campaigns and sales conversions.

How is Huggy data structured when it arrives in BigQuery? ▼

Each Huggy pipeline creates structured datasets in BigQuery with predefined schemas that include fields like agent IDs, contact information, chat timestamps, and satisfaction scores. The data arrives in a query-ready format that supports immediate SQL analysis and can be connected to visualization tools such as Looker Studio or Power BI.

Do I need technical skills to set up Huggy to BigQuery replication? ▼

No coding is required to configure the Huggy data source and begin replication to BigQuery. The setup process uses a visual interface where you authenticate your Huggy account, select your desired pipelines, and define your update schedule. This no-code approach makes advanced data warehousing accessible to marketing analysts and business users without engineering resources.

Can I analyze Huggy chat satisfaction scores alongside agent performance in BigQuery? ▼

Yes, the Chat Satisfaction Surveys pipeline delivers feedback scores and text responses that can be joined with the Agents pipeline data using standard SQL queries. This combination allows you to calculate satisfaction metrics per agent, identify training opportunities, and correlate customer sentiment with specific conversation characteristics or resolution times.

Try out all the features for free for 14 days

Related on Kondado

Try out all the features for free for 14 days