The Social Genes in a user’s social profile define that user’s personality, but these genes aren't static. Like in biology, Social Genes may become “infected” — in other words, distributed and attributed to other objects.
In nature, genes are constantly being transferred between species — humans, animals, virus particles, bacteria, plants, and so on. Social Genes follow the same pattern. They can “infect” web “species” by transferring a social genome onto any web object — a piece of content, a photo, a music file, a location or another person, giving that item or user a characteristic such as “geeky,” “humorous,” “intellectual”, “edgy” or “spontaneous.” It’s like the web object or user inherits these characteristics.
Our SCR engine monitors infection distribution, particularly in cases where different Social Genes have infected the same object, and applies powerful statistical tools to find the affinity between the object and various personality types. The object is assigned its own Social Genes based on the collective infection by the users who have consumed it. This “infection” of an item’s Social Genes does two important things:
- It enables marketers to put a face on a product and target it to customers based on the psychographic traits of the people who like it;
- It makes personalization easier. The task of matching the right product to the right person is done seamlessly, based on that person's personality traits.
This approach has three advantages:
- It incorporates personality aspects into the personalization system. Since personality is a critical factor that influences how people make decisions, incorporating personality aspects into the personalization system improves both the quality of the recommendation and the user experience. Unlike statistics-driven prediction, understanding users’ personality traits and applying them to the matching process improves the accuracy and robustness of a personalization system’s predictive ability.
- It provides transparent personalization. Social Genes define psychographic traits, and everyone can understand what they are. Every person, group of people, piece of content or product (that has been “infected” with Social Genes) possesses a social genome that can be shown and explained. Unlike other algorithmic correlations, personalization with Social Genes can be understood easily. The rationale behind the item recommendations is clear and transparent. Also, in certain scenarios the users themselves can tweak their social genome by turning the genes on or off, augmenting the engine’s understanding of their intent and generating recommendations that are even more fine-tuned.
- It tackles some of the current difficulties of personalization.
Today, personalization is far from perfect. In some cases it cannot even be applied — for example, in a “cold start,” which involves new users who have no purchase history, or new items that have no usage patterns. Correlor solves this problem by harnessing data signals from users’ social profiles and offering recommendations based on their Social Genes. In the case of a new item, Correlor uses infection by Social Genes to attribute personalization logic.
Another problem is the personalization of “indecipherable” or uncategorized content — for example, user-generated content such as videos, talkbacks, social interactions and photos as well as visual concepts, humor and dating experiences. Correlor’s SCR extracts the genetic attributes of each uncategorized item and matches them with users’ genomes.