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Zendesk Chat to BigQuery – Made Easy

5 minutes read

Modified on July 31, 2022

eCommerce

Replicate Zendesk Chat to BigQuery in minutes

Zendesk Chat is the fastest way to engage your customers with live chat software. Companies want to move this data to a single location or warehouse for easy access and seamless analysis. Replicating Zendesk Chat data to Google BigQuery ensures the data in your warehouse is always up to date and accessible by analysts and engineers. By moving Zendesk Chat data to BigQuery, you can consolidate this data next to marketing, sales, support, and other data sources and turn your data into valuable and actionable insights.

Why integrate Zendesk Chat with BigQuery

Businesses today generate huge amounts of data and this data is scattered across different systems and applications. Companies using chat support platforms like Zendesk Chat typically feed this data and data from other sources like advertising, sales, and service to a cloud data warehouse for easier and faster analytics. Integrating your Zendesk Chat to BigQuery will significantly simplify and accelerate the time it takes to build automated reporting. Integrate your chat data and explore it in the context of other business insights to figure out what’s driving leads, prospects, sales, and customer engagement.

Zendesk Chat Overview

Zendesk Chat is an online marketing, live chat support, and web analytics product offered as a SaaS model. The product enables companies to chat with visitors in real-time on their websites. The Zendesk Chat app will let you answer your customer’s questions in real-time and ease them into a purchase.

Google BigQuery Overview

BigQuery is a serverless, highly scalable, and cost-effective cloud data warehouse designed for business agility. This cloud-based enterprise data warehouse offers rapid SQL queries and interactive analysis of massive datasets. It is a powerful tool for business intelligence and it offers analytics capabilities to organizations of all sizes. BigQuery leverages Google’s existing cloud architecture, as well as different data, ingest models that allow for more dynamic data storage and warehousing.

How to replicate Zendesk Chat to BigQuery

Here are two approaches you can use to replicate Zendesk Chat data to BigQuery. This will allow you to evaluate the pros and cons of both and choose the one that best suits your requirement.

Build your own data pipeline

This process needs a lot of experience and consumes a lot of time and manpower. The chances of errors are more due to the multiple integrated steps one after the other. You need to extract data using Zendesk Chat APIs & then connect it properly with the BigQuery data warehouse. This whole process to build a custom data pipeline requires regular intervention that makes it cumbersome.

Use Daton to integrate Zendesk Chat to BigQuery

Integrating Zendesk Chat to BigQuery with Daton is the fastest & easiest way to save your time and efforts. Leveraging a cloud data pipeline like Daton significantly simplifies and accelerates the time it takes to build automated reporting.

Configuring data replication on Daton only takes a few minutes and a few clicks. Your analysts do not have to write any code or manage any infrastructure, yet you can get access to Zendesk Chat data in a few hours.

Daton’s simple and easy-to-use interface allows analysts and developers to use UI elements to configure data replication from Zendesk Chat to BigQuery.

Daton takes care of:

Authentication
Rate limits
Sampling
Historical data load
Incremental data load
Table creation, deletion, and reloads
Refreshing access tokens
Notifications

and many more important functions that are required to enable analysts to focus on analysis rather than worrying about the data that is delivered for analysis.

Steps to integrate Zendesk Chat with Daton

Sign in to Daton
Select Zendesk Chat from the integrations page
Provide Integration Name, Replication Frequency, and History. Integration name would be used in creating tables for the integration and cannot be changed later
You will be redirected to Zendesk Chat log in for authorizing Daton to extract data periodically
Post successful authentication, you will be prompted to choose from the list of available Zendesk Chat accounts
Select required tables from the available list of tables
Then select all required fields for each table
Submit the integration

For more information on Zendesk Chat Data Connector, you can visit the linked article.

Here are more reasons to explore Daton for Zendesk Chat to BigQuery Integration

Faster integration – Zendesk Chat to BigQuery is one of the integrations Daton can handle very conveniently and seamlessly. By following a few steps you can easily connect Zendesk Chat to BigQuery.
Low Effort & Zero Maintenance – Daton automatically takes care of all the data replication processes and infrastructure once you sign up for a Daton account and configure the data sources. No need to manage infrastructure or write manual code.
Data consistency guarantee and an incredibly friendly customer support team ensure you can leave the data engineering to Daton and focus on analysis and insights!
Enterprise-grade data pipeline at an unbeatable price to help every business become data-driven. Get started with a single integration today for just $10 and scale up as your data needs grow.
Robust Scheduling Options: allows you to schedule jobs based on their requirements using a simple configuration step.
Support for all major cloud data warehouses including Google BigQuery, Snowflake, Amazon Redshift, Oracle Autonomous Data Warehouse, PostgreSQL, and more.
Flexible loading options allow you to optimize data loading behavior to maximize storage utilization and ease of querying.
Enterprise-grade encryption gives your peace of mind
Support for 100+ data sources – In addition to Zendesk Chat, Daton can extract data from a varied range of sources such as Sales and Marketing applications, Databases, Analytics platforms, Payment platforms, and much more.

Daton automates the entire data migration securely and reliably for you. You can now load Zendesk Chat data to any data warehouse such as Redshift, Snowflake, or a destination of your choice without writing code in just a few minutes with Daton.

Customers can have a one-on-one conversation with an agent on your website in real time using live chat, which is session-based and synchronous. Conversations through messaging can be carried on in real time and between channels as needed, with no loss of context or history when picked up later. For accounts using the standard agent interface for Zendesk Support and Chat, the Zendesk Chat app allows customer service representatives to serve chats in a chat window without leaving the Support UI.

We found the free version of Zendesk Chat to be of limited use because it only allows for one agent and one active chat at a time. Each of the three premium plans costs $19 per month per agent and grows in price and features as more agents join. Zendesk's APIs adhere to the REST architecture. Our APIs adhere to industry standards by making use of standard HTTP response codes, authentication, providing dependable resource-oriented URLs, accepting form-encoded request bodies and returning JSON-encoded replies.

Google BigQuery's scalable architecture allows users to increase or decrease the size of the system by the petabyte as needed. Google BigQuery's scalable architecture allows it to process petabytes of data in the allotted time, making it faster than many traditional systems. BigQuery does not require you to manage servers in order to conduct queries. Analyses that require processing aggregations across the full dataset can now be performed in a matter of minutes or seconds.

Using BigQuery, You Decide Who Can See Your Data and How It Is Used for Encryption and Security. BigQuery makes it simple to keep your data safe by encrypting it at rest and in transit and providing fine-grained identity and access management with Cloud Identity and Access Management. It is a serverless architecture that uses a large number of machines to process data in parallel. BigQuery's serverless paradigm allows DBAs and data engineers to spend less time worrying about maintaining servers and more time analyzing data. Both the GoogleSQL dialect and standard SQL are supported in BigQuery. If you're just getting started with BigQuery, we recommend using GoogleSQL because it has the most features. For instance, only GoogleSQL supports capabilities like DDL and DML statements.

According to Zendesk, a SLA is an agreement between you and your customers on how quickly your support team will respond to their inquiries and resolve their issues. Delivering support according to predetermined service levels guarantees a consistent, measurable experience for customers. The 4.6 million daily customer interactions are managed using Zendesk's customer database software. Learn from the successes of over 50,000 companies, many of which are in your industry, by browsing our free library of customer experience materials.