They can tailor the recommendation base on my preferences. Scaling that level of insight requires significant natural language processing power. Along with the information retrieval technology to sift through billions of results and locate the right one. Smartphones provide more contextual information than desktop computers. But a search engine still nees a reliable way to process and utilize so much data. The image below highlights the levels of difficulty for a search engine and the technology require in each case: prepare for the future of voice search this matters when we consider voice search strategy.
Making use of the google knowlege graph
People adapt their behaviors base on the possibilities at their disposal. As marketers. Understanding those behaviors is new database essential if we want to cut through the noise and connect. Brands create the content that leads a consumer from question to answer. A search engine is the interlocutor that makes the connection. Google’s hummingbird algorithm ushere in the age of semantic search. Making use of the google knowlege graph to understand the relationship between entities and deliver something approaching conversational search. Ask google “who is the king of spain?”. And it will respond “king felipe vi”. Next. Ask “who is his wife?
People adapt their behaviors base on the possibilities at their disposal.
And it will respond “letizia of spain”. Google infers that ‘his’ refers to king felipe. This is a subtle but significant shift that affects how we DM Databases should create and promote content through search. We can now have conversations through search engine optimization (seo). Rather than one-off exchanges. Semantic search is changing how people find information and it is heightening their expectations. As the search engine’s capabilities change. So should ours as marketers. In essence. This development is a natural and vital component of voice search’s rise.