No-code pipeline · Huggy → MySQL

Send data from Huggy to MySQL

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

Creating a pipeline that sends data from Huggy to MySQL databases takes only a few minutes with Kondado. And the whole integration from Huggy to MySQL is managed and executed by our platform. With Kondado, you can focus on extracting value from Huggy data and combining it with other data in your MySQL database

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Send Huggy Data to MySQL Automatically

How to send Huggy data to MySQL? Kondado provides a direct connection that replicates your customer communication data from Huggy to MySQL without requiring any coding or manual exports. Simply connect your Huggy account as a data source, configure your MySQL database as the destination, and select which pipelines you want to replicate on your preferred schedule.

With automated updates running every 5 minutes, 15 minutes, hourly, or daily, your MySQL database stays current with the latest customer interactions, agent performance metrics, and satisfaction scores. This enables analysts to run complex SQL queries, build custom dashboards, and combine Huggy data with other business information for comprehensive reporting. Teams gain immediate access to structured conversation history and agent productivity data for enhanced operational intelligence.

Kondado replicates Huggy data to MySQL automatically on a configurable schedule, connecting four pipelines including Agents, Contacts, Chats, and Chat Satisfaction Surveys without requiring code or manual exports.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

The Contacts and Chats pipelines deliver essential customer interaction data directly into your MySQL instance, allowing you to analyze conversation volumes, response times, and lead conversion patterns using standard SQL. By querying agent performance alongside chat satisfaction scores from the Chat Satisfaction Surveys pipeline, you can identify top performers, optimize staffing schedules, and correlate service quality with customer retention metrics.

Agencies managing multiple Huggy accounts can consolidate all client communication data into centralized MySQL instances, enabling cross-account benchmarking and unified reporting through Power BI, Looker Studio, or direct SQL analysis. This setup supports automated client reporting and performance tracking without manual data manipulation.

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Replicated to MySQL

Huggy data available for MySQL

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

available pipelines

extractable fields

MySQL

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 MySQL →

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How to send Huggy data to MySQL

Sync data automatically — no code, no manual exports.

Connect your Huggy account

Authenticate Huggy in Kondado by entering your API credentials to access the four available pipelines including Agents, Contacts, and Chats data.

Configure MySQL destination

Enter your database host, port, and credentials to establish MySQL as the target, with the option to also replicate this data to BigQuery or PostgreSQL for additional analysis workflows.

Select pipelines and schedule

Choose which Huggy pipelines to enable and set your update frequency from 5 minutes to daily intervals, then connect Power BI or Looker Studio to your MySQL database for visualization.

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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 MySQL automatically

How does Kondado replicate Huggy data to MySQL without coding? ▼

Kondado uses a direct connection that extracts data from the Huggy API and loads it into your MySQL database automatically. You authenticate your Huggy account through the Kondado interface, provide your MySQL connection details, and select which pipelines to enable. The platform handles schema creation and data type mapping, delivering structured datasets ready for SQL analysis.

What specific Huggy data fields are available in MySQL after replication? ▼

The four available pipelines include 33 distinct fields covering agent details like name and department, contact information including phone and email, chat metadata with timestamps and participant IDs, and satisfaction survey responses with scores and feedback text. Each pipeline creates a separate table in MySQL with columns matching the Huggy API structure.

How frequently can I schedule Huggy data updates in MySQL? ▼

Kondado supports automated updates on a configurable schedule ranging from every 5 minutes to daily intervals, allowing you to balance data freshness with database load. You can set different frequencies for each pipeline, such as updating Chats every 15 minutes while refreshing Chat Satisfaction Surveys hourly based on your analytical needs.

Can I combine Huggy data with other marketing sources in the same MySQL database? ▼

Yes, Kondado enables you to replicate data from multiple sources into a single MySQL instance, creating a unified data warehouse. You can join Huggy conversation data with information from CRMs and advertising platforms, then visualize combined metrics in Google Sheets or BigQuery for comprehensive customer journey analysis.

How do I build custom dashboards from Huggy data stored in MySQL? ▼

Once your data resides in MySQL, you can connect business intelligence tools like Power BI or Looker Studio to create tailored visualizations. Write SQL queries to calculate agent response times, customer satisfaction trends, or lead conversion rates, then publish interactive dashboards that update automatically with each scheduled replication.

Can I filter which Huggy agents or contacts get replicated to MySQL? ▼

While Kondado replicates complete pipelines by default, you can apply selection criteria during configuration to limit which records sync to your MySQL database. This allows you to focus on specific departments, date ranges, or active contacts, ensuring your MySQL instance contains only relevant data for your analysis and reporting workflows.

Can I send Huggy data to MySQL and BigQuery simultaneously? ▼

Yes, Kondado allows you to configure multiple destinations for the same Huggy data source, replicating your pipelines to both MySQL and BigQuery on independent schedules. This enables you to maintain a MySQL database for operational reporting while archiving historical data in BigQuery for long-term trend analysis.

Try out all the features for free for 14 days

Related on Kondado

Try out all the features for free for 14 days