High value transactional events from social signals

Abstract

Aspects of the present disclosure identify social media conversational signals and deliver prospects of potential opportunities to conduct a sale in an automated fashion. Individuals, or groups of people, are identified who are in decision making mode, and the communications are presented to businesses and/or organizations to help complete the transaction. Unlike social listening platforms, which use keyword matching and sentiment analysis, in some embodiments this platform leverages machine learning (ML), natural language processing (NLP) and the Universal Human Relevance System (UHRS) to identity relevant results by classifying them into a domain specific taxonomy. These transactional events may be defined by the date and time stamp, what the potential customer is looking for, the time-frame for consideration of the purchase, and the geographic location of the individual at the time of the signal's publication. In addition, these transactional events can be customized to suit the context of a domain.

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