One of the world's leading fashion retailers had identified a need to identify trends and issues faster based on observations and feedback from its global network of stores and customers. However, they faced challenges due to the unstructured nature of the data and the many languages involved.

To address these challenges, the fashion retailer turned to Dcipher Analytics and their multilingual text analytics platform. The platform was able to mine the large amount of data on a daily basis and identify emerging and growing trends and issues. 

Natural Language Processing techniques were employed to structure the unstructured text data, cluster the data into topical clusters, identify temporal patterns in the growth and decline of topics, and use generative AI to summarize trending topics.

By using Dcipher Analytics' multilingual text analytics platform, the fashion retailer was able to act faster on emerging trends and issues. 

The platform also created a feedback loop into their product development and marketing efforts. Overall, the use of the platform allowed the fashion retailer to more effectively identify trends and issues and make informed decisions based on unstructured Voice of Customer and Voice of Store data.