Extract Call Data & Trigger Automations with Dapta Post Call Analysis

Описание: Your AI agent shouldn’t just handle calls — it should turn every conversation into structured data and automated action.

In this video, we explore how the Call Analysis feature inside Dapta transforms raw conversations into powerful business intelligence.

Every call your agent handles can automatically generate:

Structured data fields (phone number, service requested, appointment date, etc.)

Smart summaries

Success indicators

Intent-based classifications

Automated post-call workflows

Instead of manually reviewing transcripts or copying notes into your CRM, Dapta allows you to extract exactly what matters from each conversation and store it in dynamic variables.

These variables can then trigger workflows after the call ends such as:

Saving data into your CRM

Updating Google Sheets

Sending follow-up emails

Creating calendar events

Launching internal notifications

Triggering advanced automations in Flow Studio

This is where AI stops being just a call assistant and becomes an operational engine.

You can define custom data types including text fields, numeric values, dropdown selectors, or boolean (yes/no) conditions. That means your agents don’t just talk — they classify, extract, and prepare your data for action.

For example:

Capture the caller’s phone number automatically

Detect what service they’re interested in

Extract appointment dates

Determine whether a lead is qualified

Identify if a call resulted in a booking

Once structured, this data can flow directly into external systems, creating seamless automation between conversations and execution.

If you’re running appointment-based businesses, sales qualification funnels, or customer support workflows, Call Analysis becomes one of the most powerful tools in your automation stack.

Your calls become searchable, measurable, and actionable instantly.

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