Customer Journey Bot

CASE STUDY

We conducted a comprehensive evaluation and optimization of a leading fashion and lifestyle retailer’s chatbot experience.

Company Overview

A global retail company specializing in fashion, home décor, and lifestyle products, it operates multiple brands that blend creativity, digital innovation, and sustainability to deliver unique shopping experiences across physical and online channels. 

Objective

To enhance customer engagement, streamline operations, and drive business value through intelligent automation and improved conversational experiences.

Key Issues

Brand & Customer Retention

Our chatbot creates a negative perception of our brand, making us appear unresponsive and outdated. This erodes customer trust, increases negative feedback, and drives shoppers toward competitors with more effective AI-powered solutions, impacting customer retention and long-term loyalty.

Customer Experience

Our chatbot is unable to handle most customer inquiries effectively, leading to frustration and abandonment. Customers expect fast and relevant responses, but frequent misunderstandings and generic replies negatively impact their shopping experience, resulting in lost sales and decreased satisfaction

Operational Efficiency

Due to the chatbot’s limited capabilities, a high volume of inquiries is escalated to human agents, increasing support costs and overwhelming our customer service team. This inefficiency leads to longer wait times, reduced productivity, and prevents agents from focusing on high-value interactions.

Approach

In this initiative, we conducted a comprehensive evaluation of the retailer’s chatbot capabilities.

User Experience (UX) Discovery

Goal: Understand how users interact with the chatbot and identify pain points.

• User Journey Mapping: Analyze how users engage with the chatbot from start to finish.
• Conversation Flow Review: Identify where users drop off, repeat queries, or express frustration.
• Usability Testing: Conduct tests with real users to assess ease of use and effectiveness.
• Sentiment Analysis: Review user feedback and chatbot logs for tone, satisfaction, and frustration levels.
• Accessibility Audit: Ensure the chatbot is usable across different devices and by users with disabilities.

Technology & Architecture Discovery

Goal: Evaluate the bot’s backend, integrations, and scalability.

• NLP & AI Model Assessment: Review the chatbot’s Natural Language Processing (NLP) capabilities and accuracy.
• Intent Recognition Audit: Analyze how well the chatbot understands user intents and handles ambiguity.
• Integration & API Review: Assess how the chatbot connects to CRM, OMS, ERP, and other business systems.
• Performance & Scalability Testing: Examine response times, uptime, and ability to handle high traffic.
• Security & Compliance Check: Ensure data privacy, encryption, and compliance with industry regulations (e.g., GDPR, CCPA).

Business Impact Discovery

Goal: Measure the bot’s contribution to business goals and ROI.

• Usage Analytics & KPIs: Track metrics such as engagement rate, resolution time, and conversion impact.
• Cost vs. Value Analysis: Compare chatbot maintenance costs to efficiency gains and revenue impact.
• Customer Satisfaction (CSAT) & Net Promoter Score (NPS): Assess how users perceive the chatbot’s effectiveness.
• Escalation & Deflection Rate: Measure how often users escalate to a human agent versus resolving their query via chatbot.
• Competitive Benchmarking: Compare the chatbot’s capabilities to industry standards and competitors.