In many of my previous articles, I've gone into great detail about the importance of understanding intent, taking advantage of intent signals, and optimizing for the user accordingly. With voice search, understanding intent becomes even more important and navigating nuance is critical to success. The rise of conversational search is one of the main reasons why voice search is on the rise. In fact, Google reports that 70% of queries Google Assistant receives consist of natural language
same way they would ask another person a question. This is very different from how they interact with a text search box. Compared to traditional text-based search Raster to Vector Conversion over the past 10 years – where marketers have focused on keywords and their implied meaning – voice search queries are more conversational in nature and can reveal new levels of intent . For example, when I search for a restaurant with text search, I can type "lunch in San Mateo".
"What restaurants are open in San Mateo?" or "Which restaurants are open now for lunch?" Voice search queries are longer than their text counterparts and typically focus on "who", "what", "where", "when", "why", and "how". Additionally, according to Google's Mariya Moeva, voice searches on Google are 30 times more likely than text searches to be action queries. Mobile, local and machine learning Voice, mobile and local search are on the way to convergence.