Leading Japanese Fashion Retailer Automates Voice of Customer Analysis with Dcipher Analytics

The Challenge

A leading Japanese fashion retailer sought to streamline its Voice of Customer (VoC) and Voice of Store (VoS) analysis. The company was dedicating significant resources—several full-time employees (FTEs)—to manually analyze feedback across two major data streams:

• Voice of Customer (VoC): Direct customer feedback and online reviews.
• Voice of Store (VoS): Feedback from store staff working in locations worldwide.

The retailer faced several key challenges:

• Manual effort: The analysis process was time-consuming and inefficient.
• Volume and multilingual data: Feedback came in multiple languages from various global markets.
• Extracting deeper insights: They wanted to identify not only major pain points and improvement areas, but also unexpected narratives and emerging use cases.
• Data security constraints: Due to internal security policies, the company required open-source large language models (LLMs) rather than third-party commercial models.

The Solution

The retailer implemented Dcipher Analytics as an AI-powered analytics engine to automate and enhance VoC and VoS analysis.

How It Worked

• Two tailored analytics pipelines were created—one for customer feedback and another for store staff feedback.
• Dcipher’s AI-driven text analytics identified:
  • Pain points and complaints
  • Product improvement suggestions
  • New use cases and surprising narratives
• Fine-tuned open-source LLMs – To meet strict data security policies, Dcipher fine-tuned open-source models specifically for the retailer’s unique data.
• Multilingual analysis – Customer and store feedback was processed in multiple languages to support global operations.

The Results

• Seamless API integration – Insights were delivered via API, allowing the retailer to incorporate them into internal IT systems.
• Enhanced decision-making – Insights were utilized across customer service, marketing, and product development.
• Thousands of hours saved annually – The retailer significantly reduced manual analysis time, improving efficiency and speed.
• Stronger competitive edge – The company gained faster, deeper insights to enhance product offerings and stay ahead in the market.

The Impact

By implementing Dcipher Analytics, the retailer automated and scaled its Voice of Customer and Voice of Store analysis, enabling smarter, faster decision-making across multiple business functions.

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