Voice search optimization

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OK Google … how do I optimize for voice search?

Ask that question and you’ll discover that even Google doesn’t know, but it’s trying to learn. For those of us in the SEO field who want to stay up-to-date however, waiting for Google to figure it out isn’t much help. We need to know what’s going on and we need to know it now, before our competitors get the jump on us.

Who uses voice search?

Before we dive into the approaches we need to take to optimize for voice search let’s take time to gain and understanding of who is using it.

Our friends over at Stone Temple Consulting published their findings after surveying 1,000 people on their use of voice commands, here are some highlights

  • People are becoming more comfortable using voice search in public.
  • The 35 to 44 age group is the largest segment using voice search.
  • The 25 to 34 age group is most comfortable using voice search in public.
  • The heaviest users of voice search have an income above $50,000 per year.

Add to this the Gartner research that predicts 75% of US homes will have a smart speaker by 2020:

It appears we will have a deep saturation of a technology with strong buying power.

You may be thinking, “Yes Dave, we know voice search is important and we know who is searching using voice, but what can we do to get our content in front of it all?

Excellent question, let’s take a look

Voice search ranking factor

Clearly, the environment is changing rapidly, it is difficult to predict specifically how users will interact with their devices using voice.

The winners in the voice space will be those who pay close attention to the various devices that launch and how they are used.

Understanding the new device capabilities and who is using them is step one.

Recently, Greg Sterling covered a study done by Backlinko on the exact subject we’re discussing here, known voice search ranking factors.

The study is based on 10,000 Google Home search results and is close to what I’ve experimented with on my own device, just on a much smaller scale.

In the findings, they note some results may be due to causality where others may well be coincidence or correlation, but understanding what’s at play is crucial to understanding what Google is looking at.

There are several key takeaways from the Backlinko study I feel are important to note:

  • The information drawn to produce an answer as 29 words on average.  When you’re structuring the data you want to become a voice “answer”, make sure it’s short and to the point.  This means formatting the page so an answer can be easily drawn from it and understood to be a complete answer to the question.

For example, ask Google what the Pythagorean theorem is and you’ll hear this 25-word reply:

  • The average writing level of a result was targeted to the 9th-grade reading level so keep it simple.
  • Presently voice search results need to serve a more generic audience. I don’t expect this to last long, ranking for the present requires writing to the masses.
  • Google may eventually cater the reading level to the individual searching and implied education level of the query.
  • The average word count of pages used to draw voice search results was 2,312 words, this implies Google wants to draw results from authoritative pages.

While there are specific metrics that apply today such as the 9th-grade reading level they surely won’t last indefinitely. With each page we create we need to keep in mind the entity we are discussing and the intent(s) we need to satisfy when trying to optimize for voice and general search.

Entities

For the uninitiated, an entity is basically a noun and those nouns are connected together by relationships.

If answering the question “who is Dave Davies” Google needs to search their database of entities for the various Dave Davies’ and determine the one most likely to satisfy the searchers intent. They will then compare that with the other entities related to it to determine its various traits.

When someone searches for Dave Davies, Google usually assumes they are looking for Dave Davies of The Kinks fame and not the author of this piece.

I will get to why in a minute but before we get into that let’s look briefly at how Google connects the various entities around the musician Dave Davies.

A very small connection structure to illustrate might look something like:

What we are seeing here are the entities (referenced in patents as nodes) and how they are connected.

So for example, the entity “Dave Davies” is connected to the entity “Ray Davies” by the relationship “Has Brother”.

He would also be connected to the entity “February 3, 1947” by the relationship “Has Birthday” and the entity “Kinks” by the relationship “has Band”.

Other people in the band will also share this entity point with Dave, enabling them to all appear for a query such as, “OK Google, who was in the Kinks” to which Google will reply:

The band members of the Kinks include Ray Davies, Dave Davies, Mick Avory and others.

To illustrate further the connected understanding Google applies to entities and their importance, they allow Google to respond to multiple questions without explicit direction and to understand the weight and prominence of specific entities to determine which to rank.

For example, Dave Davies of The Kinks is a more prominent entity than Dave Davies the SEO and so if I ask “who is Dave Davies” it will reference the Wikipedia page of the Kinks guitarist and provide that information.

Understanding the entity relationships and how they’re referenced on the web help Google determine this but it’s also the reason why we can follow up with the question, “OK Google, who is Dave Davies brother” and “Ray Davies” is given as the answer.

This is what will provide us the blueprint to creating the content that will rank in voice search.  Understanding how entities relate to each other and giving concise and easily digested information on as many related topics as possible will ensure that Google sees us as the authoritative answer.

And not just for the first questions but supplemental questions thus increasing the probability our content will satisfy the user intent.

 Circling Back …

This explains why the folks at Backlinko found that longer content tended to rank better. A longer piece of content (or a grouping of pages, well connected/linked and covering the same subject) is not just more likely to answer the user intent and potential followup questions but also eliminates any possibility that the entity selection is incorrect.

Let’s consider my own bio here on Search Engine Land. Why does Google not accidentally select this bio when answering the query “who is Dave Davies”?

The bio is on a strong site, is tied to entity relationships such as my position, my website and Twitter profile. That is a lot of information about me so why not select it?

Wikipedia has enough content on the Dave Davies from the Kinks page and enough supporting entity data to confirm he is the correct Dave Davies.

Intents

What we see here is that covering as many related entities and questions as possible in our content is critical to rank well for voice search. It extends beyond voice obviously but due to the absence of anything other than position zero, voice is far more greatly impacted.

Earlier I mentioned Google determines which entity the user is likely to be referencing when there are multiples to select from.

In the end it comes down to intent and Google determines intent based on a combination of related factors from previous queries.

If I simply ask “OK Google, who is his brother?” without first asking it about Dave Davies, Google will not be able to reply. Google uses a system of metrics related to authority and relevance to determine which would win in a generic environment.

While not all patents are used, some iteration of their patent “Ranking Search Results Based On Entity Metrics” undoubtedly is.  According to the patent, Google uses the following four metrics to determine which entity is strongest:

  • Relatedness. As Google sees relationships or entities appear relatedly on the web (ex – “Dave Davies” and “Ray Davies”) they will connect these entities.
  • Notability. Notability as outlined in the patent relates to notability in the field.  Basically … it takes into account the popularity of the entity in question and also the popularity of the field as a whole.  The music industry is a bit more notable than the SEO industry and the Kinks listed as one of the most influential bands of all times.
  • Contribution. Google will weight entities by reviews, fame rankings and similar information. Some might suggest the Kinks guy is a little more famous than I am.
  • Prizes. More weight will be added to an entity or aspect of that entity based on prizes and awards.  This isn’t referring to a lotto but rather something like a Grammy. Had I won a Nobel Prize for SEO I may have been selected but I don’t’ see that happening anytime soon.

There is more to determining the generic intent reply than a single patent, but this gives us a very good idea how it’s calculated.

The next step in ranking on voice search is to isolate which entities will have these metrics and cover them by writing targeted content well.

Cover the core answer but also consider all the various entities connected to that answer to reinforce you’re referring to the same entity and also have the authority and information to give the best answer.

Bottom line

If you want to rank in voice search you need three things:

  • A strong domain
  • Strong content
  • Content divided into logical and easily digested segments.

Out of the three,  I feel the easily digested content and weight are the most influential elements.

Of course, getting a site up to par with Wikipedia is a massive undertaking but I suspect we will see this weighting drop in importance as Google gains confidence in their capabilities to actually determine quality content and context.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

About The Author

Dave Davies founded Beanstalk Internet Marketing, Inc. in 2004 after working in the industry for 3 years and is its active CEO. He is a well-published author and has spoken on the subject of organic SEO at a number of conferences, including a favorite, SMX Advanced. Dave writes regularly on Beanstalk’s blog and is a monthly contributor here on Search Engine Land.

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