Identifying what drives behaviour
Collecting data from hundred data sources to understand context and behavior
Customer data and data on past events contain valuable information about individual interests and motivations that led to the attendance of individual events.
Conventional customer databases and ticketing systems can meaningfully evaluate a maximum of 1-2% of this data potential.
Our platform decodes 100% of the data potential and thus creates unprecedented knowledge about the purchase intentions and behaviors of potential visitors. Collecting data from hundred data sources enables a one of a kind understanding of context. Competition events, artists' popularity and change in popularity over time, dancability or venue atmosphere - all play an important role in fans' decision making.
Relying on not only 10 features to undestand an event, but 1.000 is one important building block to develop custom AI models to predict future purchasing intentions of fans.
Identifying behavior to change it
Taste Cluster identify WHY fans are interested in specific concert and events.
Popular female conductors
- Mirga Gražinytė-Tyla
- Emmanuelle Haïm
Niche french composers
- Théodore Dubois
- Ambroise Thomas
- Zofia Neugebauer
- Leia Zhu
Popular english conductors
- Sir Simon Rattle
- Antonio Pappano
Learned patterns to find future customers
Gaining new customers
Leverage learned patterns to reach new customers
Our Taste Clusters are groups of people with the same interests. A Taste Cluster has followers all over the world and thus unites a very large group of people at its core. The limiting factor in events is the catchment area - but never the fact whether someone is already your customer. This fact leads to a remarkable percentage of new customers for our clients - up to 20% - especially at the beginning of a cooperation.