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For high-growth companies like Zipify, scaling customer support operations without sacrificing quality or efficiency is a critical challenge. But what if your support agents had an AI-powered co-pilot, guiding them to the right answers, automating knowledge creation, and transforming every interaction into an opportunity for improvement? This is exactly what Master of Code Global helped Zipify to implement.
Discover how our custom developed solution streamlined their support workflows and unlocked valuable insights to drive continuous improvement.
Ezra Firestone
Founder of Zipify
At Zipify, we're all about efficiency – and Agent Assist is one of the smartest investments we've made to support our team. It helps our agents move faster, stay focused and deliver better service without burning out. This isn't just AI for the sake of AI – it's a tool that's saving us time, money and making our support team stronger.
Zipify’s support team was consistently handling large volumes of customer inquiries, many of which were repetitive or required detailed, context-specific answers. In addition, the team lacked a centralized way to analyze conversation trends, agent performance, or evolving customer needs. Relying on general-purpose AI solutions was not sufficient: they didn’t fully capture the unique processes, documentation, and decision-making patterns the support team followed. Therefore, a more specialized tool was needed—one that could not only streamline daily workflows but also provide deeper insights through analytics.
Master of Code Global took a bespoke approach, designing and developing a cutting-edge AI solution tailored to Zipify’s specific challenges and objectives. This project comprised two key components: an intelligent virtual assistant for agents and a comprehensive analytical dashboard. This way we helped Zipify scale its support operations without sacrificing quality or efficiency.
This custom-built digital helper serves as an invaluable resource for Zipify’s support team, providing real-time assistance and knowledge retrieval within their existing workflow.
Contextual Answers & Summaries: No more endless searching through documentation. The assistant rapidly analyzes past conversations and a curated help center to deliver concise, accurate answers to agent queries, ensuring swift resolution and consistent customer experiences.
Ready-to-Use Responses: The AI simultaneously searches help articles, previous chat conversations, and knowledge base to deliver concise, relevant responses with direct links to original sources—typically in under 3 seconds. Agents can copy complete AI-generated answers or select specific parts most relevant to the inquiry, ready to send to customers immediately.
AI-Driven Article Creation: This innovative feature automatically transforms weekly support conversations into valuable help articles, published directly to an internal knowledge center. This creates a constantly growing library of real-world solutions, reducing repetitive questions and equipping agents with readily available information.
Seamless Intercom Integration: No disruptive transitions or cumbersome workflows. The virtual assistant is embedded directly into Zipify’s Intercom interface, giving agents seamless access to critical insights without interrupting their natural flow.
Multi-Platform Compatibility: While natively integrated with Intercom and deployable within 24 hours, the solution supports custom integrations with Zendesk, Freshdesk, and other helpdesk platforms through dedicated implementation support.
Complementing the virtual assistant, Master of Code Global built a robust Analytical Dashboard to provide Zipify with unparalleled visibility into their support operations.
Performance Tracking & Goal Setting: This dashboard tracks crucial metrics such as average response time, issue resolution rates, and agent workload, enabling Zipify to set measurable goals, pinpoint areas for improvement, and optimize overall team performance.
Comprehensive Metrics Suite: The dashboard tracks 18+ performance metrics including response times, conversation quality, CSAT scores, customer sentiment, handling times, and productivity measures—all in one view.
Category-Based Leaderboards: Team rankings span five key categories: Productivity, Quality, Responsiveness, Efficiency, and overall scores, enabling nuanced performance recognition.
AI-Powered Quality & Sentiment Analysis: Going beyond basic metrics, the dashboard utilizes AI to evaluate agent responses for clarity, politeness, and relevance while simultaneously gauging customer sentiment. This allows Zipify to identify emerging trends, address potential challenges, and ensure consistently positive customer interactions.
Leaderboard & Agent Recognition: A bit of friendly competition can be a powerful motivator. The dashboard incorporates a leaderboard that ranks agents based on performance, fostering a culture of excellence and recognizing top performers who consistently deliver exceptional support.
The solution includes comprehensive performance insights for individuals and teams with detailed coaching recommendations and conversation analysis.
Individual Performance Analysis: Weekly reports showing what each agent did well, specific areas for improvement, and actionable coaching recommendations based on actual conversation data.
Manager Team Overview: Team summary reports with performance trends, budget insights, and individual agent coaching points for effective management decisions.
Conversation-Level Insights: Detailed analysis of specific customer interactions with improvement suggestions and example responses for better outcomes.
We designed an engaging, guided conversational flow for the virtual assistant using robust natural language processing (NLP). The bot connects to a specialized vector database of articles and conversation logs to provide relevant answers. Meanwhile, the Analytical Dashboard pulls live data from the AI bot and Intercom, turning complex support interactions into actionable insights. Key steps included:
1. Linking the AI assistant to Zipify’s internal help center and past conversation logs
2. Setting up a weekly pipeline to convert new conversations into help articles
3. Building a custom analytics layer in Power BI to track agent performance
4. Configuring real-time metrics for conversation quality, sentiment, and resolution speed
5. Collecting agent feedback through regular syncs and continuously refining features to address emerging needs
