How To Optimize Your Product Page For Voice Search

How To Optimize Your Product Page For Voice Search

What is voice search? Voice search, or Conversational Search, is the state-of-the-art human/machine interaction wherein voice search-enabled devices can answer spoken search queries. Google: Google Voice Search relies on Google search engine algorithms. Voice search ranking factors In February 2018, Backlinko, a go-to source for SEO and content marketing advice, published a research study where they gathered and analyzed 10,000 Google Home (a voice search enabled virtual assistant device) search results. Readability: Easy-to-read content can help with voice search SEO. Add product Q & A Another voice search SEO practice is optimizing content for the 5W + H questions, or who, what, when, where, why and how. Add product schema While keeping SEO simple is still a good idea, search engines could always use some help in understanding your pages better. Voice search results are tightly connected to mobile search results: Whatever you are seeing ranking #1 or being featured on mobile will likely be read to a user in response to a voice search query. This makes mobile rankings even more important. For best voice search SEO, you have to develop a conversational format and take a guess at what search engine users will ask to land on your page.

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How To Optimize Your Product Page For Voice Search

Voice search is taking the search industry by storm

While we are watching the breath-taking adoption of smart voice assistance and subsequent growth of searching-by-voice popularity, marketers still don’t have the fundamental question figured out:

With half of search queries predicted to soon be spoken (and hence half of the search results being spoken), where will the clicks come from?

In other words, does voice search mean the death of search referral traffic?

To some extent, it may… but this is by no means going to cause the death of digital marketing.

What is voice search?

Voice search, or Conversational Search, is the state-of-the-art human/machine interaction wherein voice search-enabled devices can answer spoken search queries.

Conversational search platforms analyze spoken words and reply with responses in a computerized voice that resembles natural language. Voice search is currently integrated into a plethora of devices including mobile phones, tablets, streaming device remotes, and home assistants.

Speaking of the latter, currently, the four main voice search platforms are:

Platform Name of the assistant Search engine being used
Amazon Alexa Bing
Apple Siri Google
Google Google Google
Windows Cortana Bing

To sum up:

  • Amazon: Amazon’s Alexa Voice Search uses the Bing search engine to pull information.
  • Apple: Apple developed Siri in 2011 and initially used Bing but has now transitioned to Google.
  • Google: Google Voice Search relies on Google search engine algorithms.
  • Windows: With Windows 10 came the built-in assistant, Cortana, who uses Bing.

To give you a bit of background before we get into tactics here, here’s how the search algorithms are changing to accommodate the growing voice searching trend:

How the search players are keeping up

With the rise of voice search came changes to old-school search engine platforms. Search engines like Bing and Google are slowly moving from a keyword-centric format to analyzing semantics and natural language processing which produces search results more on par with voice search.

In the Fall of 2003, the Google Hummingbird algorithm created an environment where SERPs are populated more with search results that use context clues like the type of device used, geolocation of the search, time of day, and previous searches of the user. To maximize the search result potential, Google uses a machine learning technology called RankBrain.

RankBrain is mainly used as a middle-man, interpreting the search to identify web pages that match the search criteria but don’t necessarily use the exact words of the search phrase. RankBrain relies heavily on semantics, going beyond keywords and diving into the contextual meaning of the search phrase. Voice search is a new reason for content creators to focus on the structure of their content and analyze each web page and article to answer specific personas.

Voice search ranking factors

In February 2018, Backlinko, a go-to source for SEO and content marketing advice, published a research study where they gathered and analyzed 10,000 Google Home (a voice search enabled virtual assistant device) search results. Backlinko examined 11 ranking factors and six content-focused factors.

  • Length: Google Voice Search favors shorter answers equaling an average of 29 words per result.
  • Readability: Easy-to-read content can help with voice search SEO. Average results are written at the 9th-grade level.
  • Word count: Google tends to extract voice search results from long-form content with an average page word count of 2,312.
  • Featured snippet: Web pages that appear in Google’s featured snippets are more likely to be sourced for voice searches. 40.7% of results come from featured snippets.
  • org: 36.4% of results originate from pages that use Schema.org.

How to optimize your product pages for voice search

Now that we all generally understand where we are coming from, let’s get to tactics here:

1. Optimize product description for related terms and concepts

Remember how I mentioned above that search engines understand context much better now. No keyword is isolated: Google uses machine learning and semantic…

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