Understanding personal color preferences is critical for AI to properly perform the role of a “personal shopper.” This requires deep machine learning and a universal color language model that is teachable to the AI. That does not currently exist. But, why?

The reason is simple. AI is missing a critical component, the “common denominator” that makes this all work. This component needs to be integrated throughout the entire product ecosystem in order to “prep” the data and deliver the promise of hyper-personalization through AI. The zenColor data mapping language model delivers this component, along with the tools to make it work.

Aligning the product color data with the image color data will ignite the transformation of retail using AI powered search, data analytics, data marketing, and hyper-personalized shopping services.

The zenColor data mapping language model provides a means to “homogenize” thousands of subjective color descriptions on an eCommerce platform into one objective color language. The platform can now be searched to identify personal color preferences and the data can be properly collected. This provides a method by which to index all digital and non-digital color data points for transformational new AI powered retail services. Welcome to the future of retail..