How AI is Transforming Contextual Targeting

Executive Summary:

• At the onset of contextual targeting, the human-led analysis of keywords was mired with campaign scaling issues and imprecise targeting due to the lack of semantic signals resulting in engagement with users in an irrelevant context. (source)
• With advancements in AI technology, namely natural language processing, contextual targeting has become a precise and privacy-centric targeting solution.
• Identity deprecation has driven users to not only want, but expect personalized brand engagement. Contextual targeting can create a tailored one-to-one experience by seamlessly integrating brand messaging with the content users are actively engaging with.
• Contextual 2.0 enables content analysis beyond text-based signals – AI can now efficiently analyze the content and context of video, audio, and images, and metadata in real-time. Advancements in natural language processing improve the accuracy of contextual targeting through improvements in sentiment, semantics, and theme analysis.
• The future of contextual will see continuous improvements in semantic analysis accuracy and unprecedented scalability, especially as marketers increasingly incorporate contextual targeting as a core element of their brand strategies amidst cookie deprecation.