Genesys Pulse

Industry
Telecommunications

Type of project
Designing Pulse application for real-time analytics in contact centers

Tools
Figma, Miro & Illustrator

My role
End-to-end product design

Timeline
6 months

Overview

Genesys Pulse is a real-time analytics application built to provide contact center managers with insights into key performance metrics. It allows users to monitor various KPIs such as service levels, agent performance, call queues, and more—ensuring they can respond to customer needs in real-time. My role was to design the interface and ensure that users could access and interpret data quickly, whether they were monitoring performance across global teams or drilling down into specific issues.

The Challenge

Complexity of Data

Genesys Pulse needs to present large amounts of data from multiple communication channels (voice, email, chat) in a way that’s easy to understand and act upon.

Real-Time Data

Managers need real-time data to make quick decisions, so the interface needs to be fast, responsive, and intuitive

Diverse User Needs

Different users (e.g., global managers, regional supervisors, team leads) needed tailored experiences with varying levels of data complexity

Research & Understanding Needs

We started by conducting user interviews with contact center managers, supervisors, and agents.

I sought to understand:

  1. Their pain points with existing analytics tools.

  2. What metrics were most important to them.

  3. How they would use the data to make real-time decisions.

~ User interviews ~

I learned that the users typically needed:

  1. High-level overviews (global performance metrics).

  2. Granular insights (specific performance by agent or team).

  3. Real-time updates on KPIs like service level, wait time, and queue length.

  4. Actionable alerts that triggered notifications when performance thresholds were breached.

A customizable interface to tailor the dashboard according to their role and priorities.

Needs Statement

As a supervisor, I need real-time alerts when KPIs breach a threshold, so I can take action immediately.

Wireframing & Prototyping

I started by designing low-fidelity wireframes for the main dashboard, focusing on layout and data hierarchy. These wireframes aimed to create a clean, modular interface that would be easy to customize and adapt for different user needs.

~ low-fidelity wireframe ~

Dashboard - High-Level Overview

  • Key Sections: The dashboard included sections for service levels, agent availability, call queue lengths, and customer satisfaction scores. Each section displayed data using simple line graphs, bar charts, and KPI counters.

  • Real-Time Data: The real-time data refreshes every 30 seconds, with a color-coded status to indicate whether KPIs were within acceptable thresholds (green = good, yellow = warning, red = critical).

  • Widgets: Each data set was represented as a modular widget, with users able to move, add, or remove widgets according to their preferences.

Final Design & Launch

After multiple rounds of testing and refinement, we finalized the product. The design of Genesys Pulse focused on simplicity and effectiveness, delivering a dashboard that provided clarity without overwhelming the user with information.

~ Hi-fidelity dashboard mock up ~ 
~ Pulse dashboard real-time demo ~

Results & Impact

Improvement in user satisfaction

Supervisors and managers reported a significant improvement in their ability to monitor and act on performance data in real-time.

75%

Increment in operational efficiency

With real-time alerts, customized views, and drill-down capabilities, the contact center teams were able to resolve issues faster, improving service levels and customer satisfaction.

35%

Reduction in agent’s training time.

The intuitive design led to faster adoption among users across various levels of the organization, reducing the training time by 30%

30%

Final Thought

As a product designer, working on Genesys Pulse was an exciting challenge because it required not just designing an interface, but also deeply understanding the needs of contact center managers and how they interact with data. By focusing on clarity, speed, and usability, we were able to create a tool that empowered users to make data-driven decisions quickly and effectively.

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