How to Use AI & Machine Learning for Customer Experience | Robert Half
A luxury apparel company used artificial intelligence (AI) and machine learning (ML) to gather insights that would enhance its processes and improve the customer experience.  The organization needed to quickly understand the nature and magnitude of customer sentiments and formalize a process to address them.  The Protiviti team used AI and machine learning tools to analyze customer sentiments, and to identify and categorize key issues.

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A luxury apparel company sought to improve customer satisfaction by understanding the nature and magnitude of shopper sentiments received on a daily basis. It also needed to devise a process for categorizing customer issues so they could be easily addressed. The company requested the Protiviti team’s guidance to complete the customer issue analysis project within its short time frame.

Opportunity

The company recognized the value of mining its vast customer information for valuable insights, such as consumer behavior patterns, that can be used to enhance the organization’s digital transformation journey and overall customer experience. The organization needed technical experience and tools to quickly and efficiently complete this critical project before the start of its peak sales season. 

Strategic approach

Protiviti’s team quickly built a proprietary AI and ML tool to analyze customer emails and Instagram chats. With the ability to identify and group concerns into categories, the tools enabled the company to identify and address root causes of persistent or common issues.

Solutions

Extracted and analyzed more than 100,000 emails and Instagram chats received from customers, using newly developed AI and ML tools  Identified and flagged key issues related to shipping, tracking, open payments, loyalty programs and website challenges, and sorted them across 34 different categories Conducted a root cause analysis to understand the frequency of specific issues, which were determined to fit into three broad categories: website features, inventory management, and delivery and logistics

Technology-driven innovation

Proprietary AI and ML tools to extract and analyze customer messages

Results

The apparel company used insights from the analysis to enhance critical processes and improve inventory planning to ensure proper delivery, reduced costs and more personalized services for its customers.
Retailers increasingly rely on customers’ digital sentiments to make operational decisions around market expansion, product development, brand enhancements, risk mitigation, fraud detection and inventory management. Using tools developed by the Protiviti team, the organization has a better understanding of its customers’ views on its products. This knowledge has allowed the company to develop more personalized services and forge deeper customer connections.  Finally, the process of analyzing customer feedback data has improved the algorithms used, which means they can be recalibrated to perform more effectively in the future.

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