Identifying millions of insights within a certain industry is pointless unless individual users can consume this insight. If you don’t understand how to contextualize this information for an end user to consume and solve their problem or answer their question, you inundate the user with a flood of insight that doesn’t align to their interest—and you likely lose them entirely.
Given the vast amount of knowledge out there, the question is: how do you foster an experience to empower the end user to consume what they need? This is where personalization is critical. In CognitiveScale's Cortex 5, the primary mechanism to drive personalization is the Profile-of-One, which provides enterprises a complete view of their users to best serve their needs.
Personalization is usually targeted at understanding system users (the enterprise’s clients or employees), but a Profile-of-One can also be defined for organizations, companies, or even mutual funds.
Basically, any critical entity of a use case can be modeled as a Profile-of-One. The data collected to build this profile can be combined through multiple data sets, derived through past clickstream behavior, application feedback, and app analytics, or derived through natural language processing to pull out critical traits to help understand additional profile attributes. By understanding all of this profile context around the profile, an application developed on Cortex 5 can deliver the right insights to the right users at the right time given the specific business climate while using the right channel to deliver those insights.
Cortex 5 provides reusable services in the platform to build profiles for all critical industry entities. The services can be configured to store the context for an industry entity and Cortex 5 skills can be used to identify and load the Profile-of-One service with the necessary context. This context can then be shared across a number of applications to power a number of different applications.
Let's take a financial services example: there are some investors who would view a drop in an energy index as a buying opportunity, while others would view it as a need to reduce exposure. Still, others may not care either way and view it as noise. It is the information in the Profile-of-One that allows us to put all of that industry knowledge in context and to inform the system what is relevant to the user to best augment their needs. Based on click history, a user could be viewing a number of different energy links in an equity research portal. Their existing portfolio may also be overweight in financial services and may need to diversify to other industries (like energy). For that user, an insight like, “Consider increasing your position in energy,” may help this specific user consider a buying opportunity in the energy sector when they should be diversifying a portfolio that is too heavy on financial services.
Interested in learning more about using AI to drive new levels of personalization? Reach out to one of our AI specialists here.