Predictive Analytics Case Study: Fashion Brand Personalized Experience

Our fashion retail client was struggling to pamper their customers when it really counted; during the holidays. As the holiday season generally represents 30% or more of annual sales for the typical retailer, the inability to meet customer demand for product recommendations, order management, and loyalty program management, was of growing concern. This led to a sharp decrease in customer satisfaction, and the inability to effectively increase sales during a critical time of year.

Our client was focused on improving contact resolutions, customer satisfaction, and sales conversion. Sutherland recruited, trained, and managed a team of fashion advisors to provide personalized experiences during both peak and off  season. We used predictive analytics to develop customer shopping profiles (consisting of likely apparel and accessory combinations) to train our fashion advisors to provide personalized shopping experiences. This resulted in increases in customer satisfaction, average basket size, and sales conversion.