Voice Search allows customers to search for products and place orders in the online store by using only their voices and no physical keyboard input which enhances customer experience.
Voice search makes use of artificial intelligence (AI) speech recognition, which allows individuals to search for items without having to type. The AI recognizes a person's words and phrases and then converts the spoken words into a search term that is used to display the search results.
With voice search, customers can easily search the catalog of products with a simple voice query and don't have to look for keys or type.
Although the typical typing speed is roughly 30 words per minute, a voice search can handle up to 100 words per minute thus increasing the speed of search, saving time, and helping customers to multitask.
Voice Search increases the accessibility of a website for customers with physical, cognitive, and learning disabilities. As most of the traffic is through mobile devices it is more convenient for customers to use voice search.
Voice searches account for a third of all the searches done on the web. Around 36% of people who own smart speaker devices such as Google Home or Alexa use voice search to order online. Analysts predict that businesses adopting voice search may grow Ecommerce revenue by 30%.
As voice search makes the shopping process seamless and with the assistance of smart speakers, more search queries are converted into orders. With the implementation of voice search, visitors now complete the journey from landing page to checkout traveling down the funnel.
Google predominantly uses the mobile version of the content for indexing and ranking. As mobile users use voice search extensively, businesses should start focusing more on optimizing their site towards voice search to grab potential customers.
Voice queries are more natural language-based, users ask questions and give commands rather than searching keywords. Google uses an algorithm (Hummingbird) that places greater emphasis on natural language queries, considering context and meaning over individual keywords. Therefore optimize keywords to better detect natural language queries.
Voice queries are more like a conversation and are longer than a simple text. Long-tail keywords are longer and more specific keyword phrases. Using such keywords will attract precise customers who then end up purchasing products.
As speech recognition technologies advance, there is a change in search behaviors. According to research done by PricewaterhouseCoopers, it is estimated that approximately 7 out of 10 consumers prefer to use voice searches to conduct a query over the traditional method of typing.
With the increase of voice-activated intelligent assistants such as Microsoft’s Cortana, Amazon Echo, Google Home, or Apple’s Siri in households, this number is expected to increase. Online businesses are already adopting this trend.