
When this happens...

Automatically do this!
Enable Integrations or automations with these events of Leadsquared and Microsoft Azure Functions
Create a new lead in LeadSquared
Find a lead by Lead ID, email, or phone.
Find leads that match one or more phone numbers and return either basic or full lead details.
Create an activity on a lead.
This action searches lead based on many criteria i.e. the fields in used in the leads. This include various types of ids, phone numbers, email and much more.
Retrieve leads modified between two dates and return selected fields with optional sorting and pagination.

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To start, connect both your Leadsquared and Microsoft Azure Functions accounts to viaSocket. Once connected, you can set up a workflow where an event in Leadsquared triggers actions in Microsoft Azure Functions (or vice versa).
Absolutely. You can customize how Leadsquared data is recorded in Microsoft Azure Functions. This includes choosing which data fields go into which fields of Microsoft Azure Functions, setting up custom formats, and filtering out unwanted information.
The data sync between Leadsquared and Microsoft Azure Functions 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 Leadsquared and Microsoft Azure Functions. 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.
Leadsquared is a comprehensive marketing automation and CRM platform designed to help businesses streamline their lead management, sales automation, and customer engagement processes.
Learn MoreMicrosoft Azure Functions is a serverless computing service that enables developers to run event-driven code without having to explicitly provision or manage infrastructure. It allows for the execution of code in response to various triggers, such as HTTP requests, database changes, or message queue events, making it ideal for building scalable and efficient applications.
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