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How We Built WebRTC Telephony Inside a CRM

How We Built WebRTC Telephony Inside a CRM Modern sales teams often switch between several tools during a single customer conversation: a CRM, a softphone, call recordings, notes, scripts, and analytics. We wanted to reduce that fragmentation and bring telephony directly into the CRM interface. That is how we approached WebRTC telephony inside X10CRM . Why WebRTC? WebRTC allows users to make and…

Building WebRTC telephony within a customer relationship management (CRM) system streamlines workflows by integrating calls directly into the CRM interface. This approach reduces the fragmentation of tools used during customer conversations. WebRTC enables direct calls from a browser without a separate softphone, enhancing workflow efficiency.

Calls can be made, recorded, and analyzed directly within the CRM, providing real-time data and insights. The architecture consists of a browser communicating with a WebRTC server, which is then connected to Asterisk for SIP routing and call management. Asterisk handles call logic, recordings, and connections to external providers, while the CRM backend synchronizes call events with lead and customer records.

Secure WebSocket connections ensure secure communication, and the CRM stores event details such as direction, agent ID, lead ID, phone number, duration, status, and recording location. Call recordings are associated with CRM call records, enabling AI analysis for insights like customer objections, call outcomes, and sentiment. The integration of autodialers, call recording, and AI analysis allows for structured CRM data, improving the overall sales process.

While the basic architecture is straightforward, challenges like NAT networking, browser permissions, real-time synchronization, and scaling must be addressed to ensure a seamless experience. Integrating telephony into a CRM offers a unified workflow, making calls part of the structured data that enhances the sales process.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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