A mid-sized Australian fashion company specializing in contemporary womenswear, offering a diverse portfolio of brands. The company emphasizes ethical practices and environmental consciousness in its operations.
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To enhance product quality and customer satisfaction, our client sought to analyze vast volumes of customer reviews. We implemented NLP and sentiment analysis techniques to pinpoint key themes and sentiment trends.
Thousands of reviews across multiple products lacked structure
Product teams had no visibility into recurring negative feedback
Manual review analysis was time-consuming and error-prone
Integrated Jupyter Workspaces inside DOMO for Python-based text analysis
Applied NLP sentiment scoring and uni-gram, bi-gram, tri-gram techniques
Automatically flagged top positive and negative aspects per product
Enabled real-time visibility into product issues like fit, fabric, or pricing
Accelerated decision-making for product and marketing teams
Achieved 40% faster resolution time for customer-reported product issues
