What Zendesk data can I export to Google Sheets?

You can export ticket details, customer interactions, and support metrics directly to Google Sheets using Kondado's pipelines. This includes active and deleted tickets with full comment histories, user profiles, organizational data, and satisfaction survey scores. The replication preserves field structures like timestamps, status codes, and custom tags for immediate analysis in spreadsheet format.

How do I connect Zendesk to Power BI for customer analytics?

Configure the Zendesk data source in Kondado to replicate selected data on a configurable schedule to Power BI or BigQuery for advanced visualization. The pipelines deliver ticket metrics, SLA events, and customer organization data that enable you to build custom dashboards tracking first response times and resolution rates. Your reports update automatically on your chosen schedule, ensuring your customer analytics reflect current operations.

What is the difference between Ticket History and Ticket Metrics pipelines?

Ticket History captures audit logs showing every status change, assignment shift, and channel transition with metadata about the source and actor responsible. Ticket Metrics focuses on quantifiable performance data like response times, resolution durations, and SLA target achievements. Together they provide both the narrative of ticket evolution and the statistical measurements needed for efficiency analysis.

Can I access Zendesk audit logs and deleted tickets for compliance?

Yes, the Ticket History pipeline captures comprehensive audit logs showing every status change, assignment, and channel transition with full metadata. The Closed and Deleted Tickets pipeline specifically preserves removed tickets with deleted_at timestamps and previous status records for complete historical tracking. These pipelines maintain actor_id information to track who initiated changes, supporting compliance requirements and internal auditing processes.

How often does Kondado update Zendesk data in my database?

Kondado updates Zendesk data on a configurable schedule ranging from every 5 minutes to daily intervals, depending on your operational needs. You can set different frequencies for different pipelines, such as near-real-time updates for active tickets and daily refreshes for historical satisfaction surveys. This automation eliminates manual exporting while keeping your PostgreSQL , MySQL, or Redshift databases updated with your support platform.

Which BI tools work with Zendesk data replicated through Kondado?

Replicated Zendesk data connects seamlessly with Power BI , Looker Studio , BigQuery , and other major analytics platforms. You can also send data to Google Sheets or Excel for ad-hoc analysis, or to PostgreSQL and SQL Server for enterprise data warehousing. The standardized pipeline output ensures compatibility across visualization tools and database systems.

How do I analyze Zendesk satisfaction survey scores alongside ticket data?

Combine the Satisfaction Surveys (Scores) pipeline with the Tickets and Users pipelines to correlate CSAT ratings with specific support interactions and agent performance. Link survey scores to ticket metrics like resolution time and comment count to identify factors driving customer satisfaction or dissatisfaction. This cross-pipeline analysis reveals patterns in your Looker Studio dashboards showing which ticket types and handling approaches generate the highest ratings.

Send Zendesk data to reports, spreadsheets and ETL

Get started for free

No credit card required | 14 days | 10 million records | 30 pipelines

or sign up with your email

By signing up, you agree to Kondado’s Terms of service and Privacy policy

Zendesk Data Replication for Analytics and Reports

Access comprehensive customer service data from your Zendesk account through Kondado’s direct connection. Replicate ticket information including status changes, comment threads, and satisfaction scores alongside user profiles and organizational hierarchies. Extract detailed audit trails showing ticket history and metric events to track SLA performance across phone, chat, email, and social channels. This Zendesk data source enables you to analyze customer interactions beyond the native reporting interface.

Kondado’s Zendesk data source offers 12 distinct pipelines encompassing 235 fields, covering everything from active tickets and deleted records to satisfaction survey scores and Jira-linked tasks.

Support managers leverage this data to calculate first response times and agent productivity trends by combining ticket metrics with user performance data. Marketing teams analyze customer satisfaction patterns and tag categorization to identify pain points in the buyer journey. Operations directors utilize organization-level reporting and group analytics to optimize team structures and resource allocation across global support centers.

The Kondado platform takes care of refreshing Zendesk data, allowing you to stop wasting time with manual work and complex workflows, and focus on analyzing Zendesk data in your report, spreadsheet, data warehouse, data lake, or database

Available Zendesk Pipelines

The following pipelines capture every aspect of your customer service operations, from initial contact through resolution. The Tickets pipeline tracks lifecycle data including creation timestamps and deletion records, while Ticket Comments captures the full conversation history with author attribution for sentiment analysis. Ticket Metrics Events and Ticket Metrics provide SLA tracking and response time calculations essential for performance management. Organizations and Users pipelines deliver customer profile data and contact information for building comprehensive customer lists, and Satisfaction Surveys (Scores) enables CSAT trend analysis across support channels. Combine Ticket History with Groups data to analyze escalation patterns by team, or merge Jira Links with Ticket Metrics to measure development task resolution impact on customer wait times. With automated updates running on a configurable schedule from every 5 minutes to daily, your support KPIs stay current for operational decision-making without manual data exports.

Try out all the features for free for 14 days

Available Zendesk data

available pipelines

235

extractable fields

Available integrations

Integration	Description
Closed and Deleted Tickets	Includes deleted tickets with fields like id, actor_id, and deleted_at, allowing analysis of previous status and ticket description.
Ticket Comments	Contains comments related to tickets, with fields like ticket_id, author_id, and created_at, along with the comment body.
Ticket Metrics Events	Records SLA metric events, including id, metric, and sla_target, allowing performance monitoring of tickets.
Groups	Lists groups with fields like id, name, and updated_at, along with information about the group's status and description.
Ticket History	Records ticket audits with fields like id, ticket_id, and created_at, along with metadata about the source and channel.
Jira Links	Information about links between tickets and Jira tasks, allowing integration and tracking of related tasks.
Tags	Contains information about tags associated with tickets, facilitating categorization and search of tickets by tag.
Ticket Metrics	Presents ticket performance metrics, including response time and resolution time, essential for efficiency analysis.
Organizations	Lists organizations with fields like id, name, and created_at, allowing management and categorization of tickets by organization.
Satisfaction Surveys (Scores)	Collects satisfaction survey results, including id, ticket_id, and score, essential for measuring customer satisfaction.
Tickets	Contains information about tickets, including id, status, and timestamps such as created_at and deleted_at.
Users	Stores data about users, including id, name, and contact information such as email and status.

Closed and Deleted Tickets

Includes deleted tickets with fields like id, actor_id, and deleted_at, allowing analysis of previous status and ticket description.

Ticket Comments

Contains comments related to tickets, with fields like ticket_id, author_id, and created_at, along with the comment body.

Ticket Metrics Events

Records SLA metric events, including id, metric, and sla_target, allowing performance monitoring of tickets.

Groups

Lists groups with fields like id, name, and updated_at, along with information about the group's status and description.

Ticket History

Records ticket audits with fields like id, ticket_id, and created_at, along with metadata about the source and channel.

Jira Links

Information about links between tickets and Jira tasks, allowing integration and tracking of related tasks.

How to visualize Zendesk data in 3 steps

Connect Zendesk to dashboards, spreadsheets, or databases — no code required.

Add Zendesk Data Source

Connect your Zendesk account to Kondado by entering your API credentials and selecting your account subdomain. The platform identifies available pipelines including tickets, users, and satisfaction surveys.

Select Pipelines and Destination

Choose which of the 12 pipelines to replicate, such as Ticket Comments for conversation analysis or Ticket Metrics for SLA tracking, then select your destination. Send your data to Power BI, Google Sheets, BigQuery, PostgreSQL, MySQL, Redshift, SQL Server, Amazon S3, or Excel.

Analyze in Dashboards and Databases

Build custom dashboards in Power BI or Looker Studio, analyze metrics within Google Sheets or Excel spreadsheets, or run SQL queries on your data in BigQuery, PostgreSQL, Redshift, and SQL Server databases. Your Zendesk analytics stay current with automated updates on your configured schedule.

Try out all the features for free for 14 days