A technique used to select and classify a targeted audience based on the interpretation of content created by consumers (search queries, blogs, tweets, likes, etc.) or publishers (web pages, video content, images, etc.). By understanding the meaning behind their content, and then assigning to them distinct categories, advertisements can be matched to their audience by automated means.
Develops meaningful and optimized advertising through a semantic network of concepts and relationships that links ads to intent and people. Advertising concepts such as consumer intent, target, offer, products, services, branding, and location are converted into semantic object models and then machine learning algorithms are used to generate optimized ad campaigns.
Semantic data models shed light on the challenges of big data, which on its own is generally “dark” data. Incorporating the semantic relationships among entities enables a deeper and more meaningful analysis of data, which in turn can spark the delivery of the right ad message to the right consumer.