IV
Telephony & IVR Automation
2016–2021 IVR Case Study
Telephony/IVR • 2021
● Telephony • IVR • Customer Support

Designing a Twilio + Asterisk IVR to Automate Inbound Call Routing & Self-Service

Designed and implemented an IVR system using Twilio APIs and Asterisk, automating inbound call routing and self-service flows, reducing manual call handling and improving customer support efficiency.

Experience Senior Software Engineer (Telephony/IVR)
Stack Twilio APIs • Asterisk • Web Backends
Industry Telephony & Contact Center

The goal was to move inbound support from “every call goes to a human” to a scalable model where an IVR handles routing, authentication, and common self-service requests before an agent is ever involved. My focus: design the call flows, implement them using Twilio and Asterisk, and make the system robust enough to run in production for years.

Problem → Solution → Impact

Problem

  • Every inbound call required a human, even for simple tasks.
  • Routing was inconsistent; callers landed on the wrong queues.
  • Support teams were overloaded during peaks.

Solution

  • Designed IVR call flows with authentication and self-service steps.
  • Built on Twilio Voice APIs and Asterisk with webhook-driven logic.
  • Routing, prioritisation, and fallbacks codified instead of ad-hoc.

Impact

  • Higher call deflection for routine requests.
  • More consistent queueing and faster time-to-agent for priority calls.
  • Support teams focus on complex issues; caller experience improves.
Agent load
Before: every call live After: IVR deflection
Routing accuracy
Before: uneven queueing After: intent-based routing
Caller experience
Before: longer waits After: faster self-service/agent
Map intents

Identify common call reasons and the data needed to resolve them.

Build IVR + routing

Twilio/Asterisk flows with auth, self-service, and clear queue logic.

Harden & monitor

Fallbacks, error handling, and monitoring to keep voice reliable.

Impact spotlight
  • Callers get faster answers without always needing an agent.
  • Agents spend time on the cases that truly need them.
  • Telephony stack is predictable and easier to maintain.
Overview

Introduction

Over the span of several years working in telephony/IVR, I designed and implemented an inbound IVR platform backed by Twilio Voice APIs and Asterisk. The system replaced ad-hoc call handling with structured menus, call queues, and self-service options.

My responsibility covered end-to-end design: call flow diagrams, Twilio integration, Asterisk configuration, back-end webhooks, and the small UX details that make phone menus feel “fast and clear” rather than frustrating.

Background

Context

Before the IVR, inbound calls typically landed in a small support team’s queue:

  • No automated routing based on customer type or intent.
  • Agents handled many simple, repetitive tasks (status checks, basic FAQs).
  • Spikes in call volume quickly overwhelmed the team.

Modern telephony platforms like Twilio and Asterisk made it possible to introduce smarter routing, self-service, and basic prioritisation — if we could design the right flows and implement them reliably.

Challenge

Problem

The core questions we needed the IVR to answer were:

  • How do we route callers to the right place (or self-service) as quickly as possible?
  • Which calls truly need an agent, and which can be resolved via automated menus or callbacks?
  • How do we integrate the phone system cleanly with existing back-end systems?

The IVR had to reduce agent workload without making the call experience worse for customers — a balance between efficiency and clarity.

Operating Environment

Constraints & Requirements

  • Always-on: the IVR needed high uptime; outages directly impacted support accessibility.
  • Legacy connections: integration with Asterisk and existing PBX setups, not a greenfield environment.
  • Simple for callers: limited menu depth, clear prompts, option to reach a human when needed.
  • Measurable: design had to support tracking call volumes, paths, and deflection rates.
Execution

Implementation Highlights

1) Call flow design

  • Created diagrams for entry menus, language selection, authentication steps, and routing by intent (support, billing, other).
  • Defined self-service options for common tasks (e.g., checking status, simple account information) to reduce agent load.
  • Included safety paths (reaching an agent, callback options) to avoid trapping callers in menus.

2) Twilio & Asterisk integration

  • Implemented Twilio webhooks to handle inbound calls, DTMF input, and branching logic, returning TwiML responses from a web backend.
  • Configured Asterisk dialplans and SIP connections so calls could flow between external numbers, IVR menus, and on-premise endpoints.
  • Set up call queues and ring strategies (round-robin, skills-based groups) for calls that did require agents.

3) Self-service & backend integration

  • Connected IVR options to back-end systems via APIs to fetch account information and status data in real time.
  • Implemented simple “speak out” flows using text-to-speech for dynamic responses.
  • Designed error-handling and retry logic for backend timeouts to keep calls from failing hard.

4) Monitoring & tuning

  • Logged call paths, menu selections, and drop-off points to identify confusing prompts or unused options.
  • Tuned prompt wording, order of options, and timeouts based on real usage patterns.
  • Worked with support teams to adjust queues and priorities as call patterns evolved.
The result was an IVR that felt like a “front door” to support: fast greeting, routing based on intent, and useful self-service — rather than a barrier between callers and humans.
Outcomes

Impact & Outcomes

The IVR system changed how inbound calls were handled and measured:

  • A meaningful share of calls were resolved in self-service without agent involvement (status checks, basic account info).
  • Agents saw fewer “wrong-queue” calls thanks to clearer menu branching and routing.
  • Peak-time load on support teams smoothed out as the IVR absorbed repetitive tasks.
  • Call data became easier to analyse (volumes, intents, abandonment), informing staffing and process improvements.
Reflection

Key Learnings

  • IVR design is part UX, part systems engineering: menu structure matters as much as infrastructure reliability.
  • Twilio + Asterisk is a powerful combo, but observability (logs, call traces) is essential to debug real-world issues.
  • Giving callers easy escape routes to humans makes them more tolerant of automation.
  • A well-designed IVR can materially improve support efficiency without feeling like a “robot wall” to customers.