Everyone knows that there are early conversations in social media that are forerunners of the next Rosé trend or the move to avocado showing up as an ingredient in your hand cream. However, using this data in a way that predicts which of these early trends will grow versus those that will fizzle away, has been elusive.
Because these valuable signals are hidden deep in massive, messy, noisy, unstructured data sets. To unlock this “goldmine” of insights for brands, they need to utilize the newest AI technologies + advanced analytics to separate these valuable signals from the noise and peer into the future today.
This webinar will provide a clear approach on how to apply machine learning language technology to these massive, unstructured data sets in order to create predictive models of what may be the next “it” ingredient, color, flavor or pack size. We will share specific case examples of how some of the largest CPG brands are using this technology to understand ingredient trends and deepen category understanding.
We are now building models for clients that unlock if an ingredient trend is starting in food or going from personal care to food, as it builds momentum. These and many other key components to predictive “trend spotting” will be shared in this innovative knowledge sharing session.