
When this happens...
New Chat
Finished Chat
Chat Changed

Automatically do this!
Delete Rows
Run SQL Query
Insert Rows
Update Rows
Create Table
List BigQuery Projects
List Datasets in Project
List Tables In Dataset
When this happensTriggers
A trigger is an event that starts a workflow.
Triggers when the chat is started.
Triggers when the chat is ended.
Triggers when the tag list for a chat was changed.
Action is the task that follows automatically within your LiveChat integrations.
Deletes rows in a Google BigQuery table that match the condition you provide.
Run a SQL query on Google BigQuery and return the results.
Adds one or more rows to a BigQuery table.
Change specific fields for rows in a BigQuery table that match the rules you provide.
Creates a new, empty table in a BigQuery dataset.
Lists the BigQuery projects you have access to.

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To start, connect both your LiveChat and Google Bigquery accounts to viaSocket. Once connected, you can set up a workflow where an event in LiveChat triggers actions in Google Bigquery (or vice versa).
Absolutely. You can customize how LiveChat data is recorded in Google Bigquery. This includes choosing which data fields go into which fields of Google Bigquery, setting up custom formats, and filtering out unwanted information.
The data sync between LiveChat and Google Bigquery typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between LiveChat and Google Bigquery. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
LiveChat is the faster way to contact your customers. It is a web-based chat tool that lets you chat with your website visitors.
Learn MoreBigQuery is Google's serverless and highly scalable enterprise data warehouse, designed to make all your data analysts productive.
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