Tramontina is a 100 years-old brand from Brazil and one of the biggest stain steel cookware manufacturers of the world. Stain steel pans are no longer trendy, so the brand needed a refresh, to inspire people to cook again. Especially, young people. We needed to show that a pan is more than just a pan. It’s a world of possibilities. And the way we figured out how to do it, was through music and technology.

To show a pan is a world of possibilities, we decided to open millions of new ones: transforming the songs of the Spotify platform catalogue into flavors.

If music had a taste, what it would be? To answer this question, we used the concepts of synesthesia. Correlated musical parameters of the biggest music platform of the world with cooking ones. Created a huge ingredients database with information in all of these parameters that, combined, generate unique recipes for each song. A digital experience where music fans can discover a different recipe for each of the songs they like to listen to. At last, indicating what’s the best pan to cook all these recipes.

After selecting Spotify musical parameters that made more sense with synesthesia and correlating them to cooking parameters, it was time to transform that into recipes. As duration became the number of ingredients, we set a basic configuration to the dishes: one main ingredient and 1 to 3 complements according to the length of the song.

Main ingredients would be, for example, filet mignon, grilled chicken or pulp rice. Complements would be, for example, baked potato, salmon roe or Moroccan couscous.

Hundreds of main ingredients and hundreds of complements were combined one, two, or three times and gathered according to the graduations developed in each one of the parameters set before.

That data is what allowed us to make millions of recipe combinations, that could represent each of the million songs that are available in Spotify.

The Flavor of Songs project took more than 6 months of study and tests before going live. It counted with the help of a neuroscientist, a music conductor, a cuisine chef and Casion, a technology production company which is an official partner of Spotify.

Step 1: Filtering Spotify’s musical parameters, choosing the ones that made more sense with synesthesia.

Step 2: Correlating those parameters with cooking ones.

Step 3: Creating a huge ingredient database, with a scale note on the parameters for each of them.

Step 4: Crossing all these data, using algorithms and A.I, in a way that it could generate a recipe for each of the Spotify songs.

All that became a website. In this website, users could login with their Spotify account, type the name of a song or artist and discover what flavor represents it.

The result was a digital experience capable of offering our target more than 44 million combinations of recipes. The whole Spotify catalogue turned into cooking recipes. We didn’t just show, we proved that a pan, in fact, is not just a pan. It’s a world of possibilities.