Taste Profiles of each shopper

A summary of the taste of an individual shopper


A Taste Profile summarizes the taste of an individual shopper, what clothes she has in her closet, and what are the drivers behind her purchases.


We build a Taste Profile for each of your shoppers, as part of your Taste Graph. Taste Profiles include:

  • 1. We summarize taste. We register taste-related data of each shopper, and assign clean, structured and correlated descriptors to her profile. These descriptors are generated by our interpretation of their activity in your site. We use our ontology, graph and Smart Virtual Closet Technology.
  • 2. We connect the Taste Profiles to our own interpretation of your products and to all the elements of your Taste Graph.
  • 3. We offer an API and Dashboard. Our Dashboard helps business teams to fully understand Taste Profiles and have a sense of control. With the Dashboard, business teams end up working hand-by-hand with tech, with the same understanding.
  • 4. Taste KPIs. Whether you are capturing taste data or not, each shopper is telling you what motivates her purchases. KPIs tell you the % of shoppers for which you capture clean data, broken down into types of data.


Spotify and Netflix also build Taste Profiles for each of their users.

  • Spotify registers the music you listen to, and builds a Taste Profile with their interpretation of what each song means. As you listen to more music, your Taste Profile reflects pretty accurately what are the true motivations of you listening to a song. On top of this data, they automate several internal processes, detect early adopters of future trends, and offer personalized content.
  • Netflix follows a similar approach. Netflix ontology plays a crucial role in their interpretation of what a movie means, and how that defines the person watching it. Our fashion ontology, although very different in structure, plays a similar role.
  • In fashion, building the infrastructure to create Taste Profiles is way more complex that in music or movies. But once it is done, the richness and cleanness of the data is extremely eye-opening.


Taste Profiles mostly contain data related to Products, Occasions, Influencers, Brands and Trends:

  • Products. Products contain properties. One shopper might find relevant one or more properties of a product, or even none of the product properties.
  • Occasions. A shopper will most likely have different purchase drivers for each occasion they dress for, special moment or everyday occasions.
  • Influencers. Sometimes purchases are driven by an influencer. At the Fashion Taste API, we care about this data and register it.
  • Brands. The brands someone has in her closet are not always easy to capture, but there are approaches to obtain this data depending on your needs. Brands are definitely an element that might predict what someone is going to buy in the future.
  • Trends. The Fashion Taste API pays attention to the likelihood of someone buying a trend. We want to know if a given shopper is a heavy shopper of trends. The information provided by this cohort of shoppers is interesting in terms to revenue generation, but also in terms of data collection.