Contact Center: From Market Gap to Launch in 6 Months

The Challenge: The Fragmented Market

Plivo had voice APIs, messaging APIs, and phone number management, but no packaged product for teams who handle customer conversations. Support teams at mid-market B2C companies were stitching together separate tools for voice, chat, and messaging with no unified view of the customer.

The contact center market was split. Traditional players (Genesys, Avaya, Five9) were built for scripted outbound call centers. Modern SaaS tools (Zendesk, Freshdesk, Intercom) had solved ticketing but treated voice as an afterthought. B2C support teams, where customers reach out across WhatsApp, SMS, voice, and in-app chat, had no purpose-built solution that combined real-time communication with operational tooling. This was a 0-to-1 product, and the work was to find a defensible angle and ship a first version.

My Role

I defined the product vision and led design from discovery through delivery. I owned user research, competitive analysis, product strategy, and interaction design. Working alongside the PM and engineering leads, I scoped the MVP to hit an aggressive 6-month launch window and managed alignment across Plivo's executive leadership on our strategic market positioning.

Identifying the Product Gap

I analyzed 12+ platforms across the market spectrum. Enterprise contact centers were built for high-volume outbound operations with heavy implementation requirements. SaaS helpdesks had lightweight onboarding but lacked real-time operational tooling like live queue management, agent monitoring, and voice-first workflows. Neither category served B2C support teams that urgently needed both.

How Support Teams Actually Work

I interviewed support leaders at B2C companies across e-commerce (Bigbasket, Pepperfry), food delivery, health tech (HealthifyMe), and ride-hailing (Rapido). These conversations revealed operational patterns that no competitor was designing for:

• Channel specialization: Agents focus on either voice or non-voice, rarely both simultaneously. Non-voice agents handle 2–10 concurrent conversations depending on complexity.
• The 7-Agent Pod: Team leaders manage 7–8 agents maximum. They need live queue visibility and the ability to barge into conversations (invisible to the customer) to coach agents in real time.
• Quality monitoring: Audits happen frequently but are entirely manual. Leaders sample conversations and score them against spreadsheets, with no integrated tooling.
• Routing as one-time setup: Routing rules are configured once and rarely changed. The ongoing work is queue management and agent availability, not rule creation.

Strategic Positioning & The Integration Strategy

Based on the research, I framed the product strategy around three principles that dictated our engineering roadmap:

• Omnichannel by default: Agents see a unified conversation timeline across voice, messaging, and chat. No switching between tools or losing context when a customer moves channels.
• Built for resolution, not sales: The interaction model was designed purely around inbound resolution workflows, differentiating us from traditional contact centers built for outbound call scripts.
• The Integration Pivot: The initial business plan was to integrate exclusively with Salesforce. My user research proved that B2C support teams were already locked into Zendesk and Freshdesk. I convinced leadership that competing against these platforms was a losing battle, and that integrating with them was the only viable path forward. This positioned us to sit on top of, rather than compete against, established helpdesks, massively expanding our potential customer base.

Key Design Decisions

1. The Agent Workspace

This is the core screen where support agents spend their shifts. I designed this specifically to eliminate context-switching:

• Unified conversation timeline: Voice, chat, and SMS appear in a single chronological view. An agent can instantly see if a customer called yesterday about the same issue they are messaging about today.
• Quick actions & structured handoffs: One-click operations for common resolution patterns (transfer, hold, escalate). When a conversation transfers, the receiving agent gets full context, eliminating the need for the customer to repeat themselves.

2. The Team Leader Experience

Research showed that supervisors managing 7–8 agents need real-time operational visibility, not retroactive dashboards.

• Live queue & barge-in: Real-time view of queue depth and agent availability. Leaders can invisibly join an active conversation to coach an agent without interrupting the customer interaction.
• Quality audit integration: Scoring rubrics were built directly into the conversation review flow, replacing the manual sampling process teams were running in external spreadsheets.

3. Admin Configuration (Self-Serve Routing)

I designed the configuration layer around the finding that routing is a one-time setup task. The interface prioritized first-time clarity over power-user efficiency.

• Visual rule builder: Self-service routing rules for directing incoming communications based on channel, customer attributes, or time of day.
• Zero-engineering setup: Business hours, region-specific holiday calendars, and phone number assignment were designed so admins could complete full setup without touching the Plivo API console.

The Outcome

• 6-Month Delivery: Took the product from initial whiteboard discovery to an enterprise-ready launch in just 6 months.
• Market Expansion: The pivot to integrate with Zendesk/Freshdesk opened the product up to our actual B2C target market.
• Unified Omnichannel Experience: Successfully collapsed voice, messaging, and chat into a single, specialized agent workspace.

Reflection: Conviction in the 0→1 Phase

0-to-1 design is fundamentally different from optimization; you cannot A/B test your way to a new product. The most valuable design work here was not the UI. It was the research that gave the business the conviction to pivot our integration strategy and target a specific gap in the B2C market. Building the right foundations early (strict role separation, flexible configuration, channel-independent architecture) created the exact base that allowed this product to survive and become the core of Plivo's unified Voice AI platform years later.