Voice Search Optimization
How voice search was developed?
The Google voice search was released in 2011. Initially, it was only available for Google.com and only in English. In October 2012, an App was released for mobile Apple devices. Google strived to compete with Apple’s Siri with voice search for smartphones and tablets.
In November 2013 Google introduced the option to use voice search on desktop PCs with “Google Voice Search Hotword.” To be able to utilize it you need to install an extension for Google Chrome. Voice search otherwise does not work in other Browsers. Google introduced German in their voice search at about the same time. The Google video titled “Search Out Loud with Voice Search” shows examples of how Google’s voice search is used.
Digital assistants: The agents of voice search
Siri. Cortana. Google Now. Alexa. Google Assistant. These are only the names of the most well-known digital assistants from the major technology companies; a search for “digital assistant” on the iOS or Android app store shows just how many different varieties of these voice-controlled AIs there are.
The figures show just how recent much of this uptake of voice search is. Late last year, MindMeld published a study of smartphone users in the U.S. and their use of voice search and voice commands. It found that 60% of smartphone users who used voice search had begun using it within the past year, with 41% of survey respondents having only begun to use voice search in the past 6 months. Given the growth of voice search, it has great potential to affect how local businesses are found. ComScore even estimates that by 2020, a full 50 percent of all searches will be by voice. While it won’t likely replace existing screen-based search, voice search will soon be enough of a factor that businesses need to understand strategies for being found by voice search.
With the growth of voice search, we can expect to see more and more long-tail search keywords and natural language queries, which give increasing amounts of contextual information and useful data about searcher intent.
Voice Search Optimization (structure data,long-tail and local search)
Voice search is operated differently than the regular search. While people usually want to reduce the typing effort by using as few search terms as possible, full questions or whole sentences can be stated with voice search in seconds. Therefore, it can be assumed that the proportion of Long Tail search queries will increase affecting the search engine optimization area. This usually happens at the expense of the generic Keywords and hitherto typical money keywords. The newest generation of digital assistants, including Google Assistant and Viv, a new AI from the creators of Siri, are capable of interpreting and responding to long, multi-part and highly specific queries. For example, during a public demonstration in New York, Viv showed off its ability to accurately respond to queries like, “Was it raining in Seattle three Thursdays ago?” and “Will it be warmer than 70 degrees near the Golden Gate Bridge after 5PM the day after tomorrow?” If you’ve ever used Voice Search to get directions to somewhere, imagine the potential for even greater Voice Search integration with local search listings. We can already literally “ask” Google to help us find stores selling goods we want to buy, as well as check important information such as opening hours, parking availability, and even coupons.
For voice search users, they want a list that’s easy to digest and quick to implement.
Currently, Google Home and Google Assistant read snippets from sites that are ranked in “position zero” and have been granted a featured snippet. This is why more people than ever are talking about how to optimize for featured snippets. If you look at the articles published on the topic (according to what Google has indexed), you’ll see that the number of articles about how to optimize for featured snippets has grown 178 percent in the past year: understanding voice search queries could help us better understand the types of queries that surface featured snippets.
As marketers, we could then devote time and resources to providing the best answer for the most common featured snippets in hopes of getting promoted to position zero. This helps marketers drive credibility to their brand when Google reads their best answer to the searcher, potentially driving traffic to the site from the Google Home app.
Moreover, search engine optimizers are faced with two other trends, local and personal search results. User-defined search results, where the SERPs are re-weighted according to local significance for the user have been around for some time. Google takes into account specific criteria which are determined by means of vocal analyses for personal search results. For example, if a user searches for the keyword “jeans,” the voice analysis determines whether the user is a female or male user depending on the pitch. Subsequently, the search engine does not output search results for the search word “jeans,” but for “woman’s jeans” or “men’s jeans.” In the context of voice search, the semantic search also plays a major role, making it easier for Google to understand what the user wants to find.
Voice search engines rely on structured data to provide rich results like hours, addresses, or photos. So you need to ensure your site’s content is structured in a way these services understand. Make sure you implement the schema markup and optimize for your content.
In 2018, we will see more and more voice search tactics and I will continue sharing these with you! Please follow me and comment on my blog. We can share the ideas and knowledge!
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