Everyone knows that there are early conversations in social data that are forerunners of the next Hard Seltzer 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.
In this session, presented with our partner in this work, Converseon.AI, we will share a breakthrough approach that takes social data and transforms it into structured, research-grade data. From here, we build predictive models of what will be the next “it” ingredient, color, flavor or pack size. Our r&d in this area allows us to now deliver:
- Rankings of key trends that go beyond simple frequency counts
- Cross category trend migrations
- Trend flocking – do trends of a feather flock together?
Finally, these valuable signals, long hidden in massive, unstructured data sets, can be unlocked using the newest AI technologies + advanced analytics
Unilever, known for its commitment to purpose-based brand building and innovation, is using this kind of predictive modeling of social data, to inform innovation strategies. Tony Cece, Senior Data Science Manager, joins our webinar to share his perspective on the role this work can play in product development.
We will also offer you a sneak peek into a real-world validation case of a sales decline predicted by our Signal Spotting Trend Prediction (SSTP℠) engine.