AI-powered Saas platform

Enhancing CX Teams Efficiency with AI

COMPANY

Lang.ai

ROLE

Product Designer

EXPERTISE

UX/UI Design

YEAR

2022 - 2024

30%

Enhanced Decision-Making

30%

Enhanced Decision-Making

30%

Enhanced Decision-Making

20%

Reduced Response Times

20%

Reduced Response Times

20%

Reduced Response Times

20%

Customer Satisfaction Increase

20%

Customer Satisfaction Increase

20%

Customer Satisfaction Increase

Project description

Project description

Project description

This project focuses on integrating AI-driven insights into a ticketing SaaS platform to enhance customer experience (CX) decision-making through actionable data derived from customer interactions.

Timeline

From 2022 to 2024, this ongoing project involves completing small tasks within a larger project while managing several other initiatives at the same time.

Background

Lang.ai specializes in automating the understanding of customer interactions by leveraging natural language processing to extract valuable insights from unstructured data.

This approach transforms traditional customer support, which often relies on manual analysis and categorization, into a more efficient and streamlined process, saving time and improving the overall effectiveness of customer engagement.

Problem

Customer experience agents often face challenges in managing high volumes of inquiries, manually retrieving information, and handling repetitive tasks.

These inefficiencies slow down response times, affect customer satisfaction, and lead to agent fatigue.

The platform lacked intelligent tools that could support agents in making fast, informed decisions, leaving them overwhelmed by routine tasks and customer data overload.

Process

Process

Process

This category details the step-by-step approach taken during the project, including research, planning, design, development, testing, and optimization phases.

Research & Planning

Utilized user personas, empathy maps, interviews, session viewing tools, mixpanel… to understand user needs and pain points effectively.

Design & Prototyping

Created both low and high-fidelity prototypes in Figma, iterating based on user feedback to refine the design.

Implementation

Worked closely with developers to ensure the final product aligned with the initial vision, providing support for missing assets and addressing any questions.

Testing & Optimization

Conducted usability testing to identify areas for improvement, ensuring the final design met user expectations and enhanced the overall experience.

Solution

Solution

Solution

The resulting AI-driven CX platform provides a seamless user experience, enabling organizations to harness insights for improved customer engagement and satisfaction.

Summary of AI Insights

Provides users with a clear overview of actionable insights derived from data, enabling informed decision-making.

Automated Reporting

Suggests automated actions and optimally routes tasks based on user-defined criteria to enhance efficiency.

Sentiment Analysis

Analyzes customer feedback and interactions to gauge sentiment, helping teams understand user emotions and improve responses.

Outcomes

Outcomes

Outcomes

Here, the outcomes and achievements of the project are highlighted.

Enhanced Decision-Making

The implementation of AI-driven insights led to a 30% increase in data-driven decisions by customer support teams, measured through analytics on decision logs and follow-up reports.

Improved Efficiency

Automation recommendations streamlined workflows, reducing response times by 20%, measured by tracking average response times before and after implementation.

Deepened Customer Understanding

Sentiment analysis provided valuable insights into customer emotions, enabling the team to tailor responses and strategies, resulting in a 20% increase in customer satisfaction ratings, measured through post-interaction surveys and feedback analysis.