Em português aqui.
Application developed to present and process the data collected through the TAGalera application. The TAGalera app was created in the Shawee Hackathon: Megahack3 in the Ambev challenge.
You can explore the Dashboard interactively Clicking Here
Beverage manufacturers in general usually negotiate their products with distributors, and they pass it on to the final consumer. For this reason, manufacturers keep a certain distance from consumers, making it difficult to monitor their profile.
With this in mind, through the data collected from the TAGalera application, this interactive dashboard was created, with which the manufacturer can monitor the profile of consumers of a particular product and predict which will be their favorite drinks.
In the option "Ver perfil dos consumidores de cada bebida", or "See Consumer's profile for each drink", the manufacturer can observe the profile of consumers of a certain product, through several graphs, and with that, direct its future marketing campaigns.
Na opção "Prever Bebida Preferida do Consumidor", or "Predict Consumer's Preferred Drink" option, through a Machine Learning algorithm based on Logistic regression, it is possible to predict drinks that the user has a high chance of approving based on their profile.
Important: The TAGalera mobile application was developed by Everson Motta, Jhonata Araújo, Juan Penas and Rafael Bleidi at Hackathon Megahack3. The application has been completed, but has not yet been launched, for this reason, a database was created to demonstrate its features. Where your data was collected from a Google Forms form, and the Drink and Favorite Music fields were randomly generated, just for demonstrations. You can find more information about the TAGalera app Clicking Here.