Connect Freshchat Classic and TimescaleDB to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Freshchat Classic
Choose an Action
Automatically do this!
- Request a new Action for TimescaleDB
Enable Integrations or automations with these events of Freshchat Classic and TimescaleDB
Enable Integrations or automations with these events of Freshchat Classic and TimescaleDB
Actions
Create a User
Add a new user to Freshchat.
Search Users
Find users by email, name, phone number, or reference ID and return matching user records. Supports pagination and sorting.
Create a conversation
Creates a new conversation.
Search User
Search a user.
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Frequently Asked Questions
To start, connect both your Freshchat Classic and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in Freshchat Classic triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how Freshchat Classic data is recorded in TimescaleDB. This includes choosing which data fields go into which fields of TimescaleDB, setting up custom formats, and filtering out unwanted information.
The data sync between Freshchat Classic and TimescaleDB 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 Freshchat Classic and TimescaleDB. 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.
About Freshchat Classic
Freshchat is a modern messaging software designed to help businesses engage with their customers through various communication channels. It offers features like live chat, chatbots, and in-app messaging to enhance customer support and improve customer experience.
Learn MoreAbout TimescaleDB
TimescaleDB is a powerful time-series database designed for fast ingest and complex queries, making it ideal for handling time-series data efficiently. It extends PostgreSQL, providing scalability and performance enhancements specifically for time-series workloads.
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