One of the world’s leading beauty conglomerates sought to radically update their understanding of the anti-aging themes, opinions and pain points of female consumers.
We created a dataset with text data from 60,000 skincare enthusiasts. Then, we used three complementary AI techniques: Topic Clustering, Emotion Recognition, and Trend Forecasting. By leveraging multiple approaches, we are able to obtain a more comprehensive understanding of the topic at hand.
Our study yielded valuable insights into the emotional journey that consumers undergo during the aging process. Additionally, we pinpointed two specific ingredients that were causing confusion for consumers in anti-aging skincare products.
