Join your Zendesk Chat and Klaviyo data
Stitch can replicate data from all your sources (including Zendesk Chat and Klaviyo) to a central warehouse. From there, it's easy to perform the in-depth analysis you need.
Integrate Zendesk Chat and Klaviyo to turn your data into actionable insights.
Zendesk Chat is user-friendly, reliable and feature-rich chat software
Stitch offers detailed documentation on how to sync your Zendesk Chat data.
Klaviyo provides ecommerce email marketing and analysis
The Stitch Klaviyo integration is maintained by the open source Singer community.
Since Stitch replicates data to a consistent schema, it works well with other tools in your stack. Once you have BLOCKNAME HERE data in your data warehouse you can use it in many ways. Modeling tools such as dbt and Looker Blocks can help you prepare your data for reporting, analytics, or machine learning.
We've developed a Looker Block for Zendesk Chat data provisioned by Stitch. This block includes prebuilt code to create dashboards and models that can help uncover insights from your Zendesk Chat data.
This Looker Block includes three dashboards that provide analysis on agent performance, ticket submissions, and overall customer support metrics. The LookML file shown here produces an overview dashboard that allows you to view understand ticket submission trends. Other dashboards included in this block are: Overview dashboard - View ticket submissions over time to understand the level at which your customers are leveraging your support team - See the breakdown of ticket submissions by channel to understand where most of your support requests are generated - See your top 20 all-time agents, requesters, and organizations by number of tickets to see identify the key players in customer support - See a ticket tag breakdown over time to understand how customer priorities have shifted Agent performance dashboard - Monitor your support team's all-time reply and resolution time to measure against SLAs - See how your team's response and reply time have fluctuated over time to identify trends and opportunities for improvement or celebration groups and more efficiently manage resources - Identify top performers in your organization Ticket submissions dashboard - Evaluate the volume at which organizations are submitting tickets to identify which organizations are requiring the most attention of your team - Identify how average tickets per organization changes over time to see whether documentation, tutorials, demos, and product changes or releases are taking a load off your team - See ticket submission volume by hour of the day and day of the week to more efficiently allocate resourcesView the source on GitHub →
Stitch delivers all your data to the leading data lakes, warehouses, and storage platforms.
Give your analysts, data scientists, and other team members the freedom to use the analytics tools of their choice.
Among the platforms we looked at, Stitch was the most cost-effective for us to connect to our five data sources: Mixpanel, Facebook Ads, Google Analytics, Google Ads, and Zendesk.
Stitch is a simple, powerful ETL service built for developers. Stitch connects to your first-party data sources – from databases like MongoDB and MySQL, to SaaS tools like Salesforce and Zendesk – and replicates that data to your warehouse. With Stitch, developers can provision data for their internal users in minutes, not weeks.Explore all of Stitch's features
Stitch integrates with leading databases and SaaS products. No API maintenance, ever, while you maintain full control over replication behavior.
Amazon Aurora MySQL
Amazon Aurora PostgreSQL
Amazon RDS for MariaDB
Amazon RDS for MySQL
Amazon RDS for Oracle Database
Amazon RDS for PostgreSQL
Amazon RDS for SQL Server
Amazon S3 CSV
Google Analytics 360
Google Cloud SQL MySQL
Google Cloud SQL MySQL
Google Cloud SQL PostgreSQL
Google Search Console
Microsoft Advertising (Bing Ads)
Microsoft Azure SQL Server Database
Microsoft SQL Server
Netsuite Suite Analytics
Oracle Netsuite Bronto Marketing Platform
Salesforce Marketing Cloud