Voice Assistants Are Going To Ruin SEO
- SEO |
Voice and Personal Assistants are quickly becoming a normal part of our daily lives, and completely transforming the way we search for things, and the way the search engines respond.
The most ironic part about this though, is that it appears that the searches from personal assistants may soon be bypassing the search engines altogether.
Who actually uses a Personal or Voice Assistant?
It turns out, most of us. According to this study published by Thrive Analytics, 71% of 18-29 year olds who use smartphones, use a mobile personal assistant. Surprisingly, they also report that 59% of 30-43 year olds and 39% of 44-53 year olds do the same. The most shocking number though, is that 38% of users older than 54 years of age are also using a mobile personal assistant. These numbers simply demonstrate how "normal" this technology has become, and it will no doubt be forcing companies to change along with it.
A study by Northstar Research (commissioned by Google) gave us information on what people are actually searching for with their voice assistants. Teens mostly use it for placing a phone call, asking for directions, getting help with homework or playing music. Adults use it most often to ask for directions, dictate test messages or place a phone call. The study found that 55% of teens and 41% of adults actually access their voice search more than once each day. This study also gives a lot more detailing, including where people are when they use it and what their wish list is for future searching and finding options.
So what does all this mean for search engines? It's mind boggling to think about how much search has changed over the last decade.
This video is of a talk by Will Critchlow, on how the future of search is changing dramatically -- it's close to 40 minutes long but absolutely riveting if you're into the evolvement of search engine results.
Some of Will's talking points really touch on how much voice assistants have changed and shaped the way Google now delivers search results, and I'll discuss what stuck out at me below.
Implicit Search
Explicit search has migrated to implicit search -- partly due to mobile devices. This means that the search engines are using history and other signals to determine what those explicit search terms actually mean. Consumers have to give less and less explicit information, due to the capabilities of implicit variables. For example, Google has stated they'd like to be able to deliver you the correct bus schedule, based on what side of the street you're standing on when you perform the search. The explicit information is your search "main street bus schedule" but the implicit variables are what Main Street you'r referring to, and what direction you intend to go in.
Compound Queries
In 2013, Google released their new algorithm update, which they called Hummingbird. It was an infrastructure update that allowed Google to start incorporating machine learning and natural conversations into their results. Queries are no longer independent from one another; answers are inputs along with additional inputs from your first query. They are no longer delivering a separate sets of results based on each question that you ask. Google understands the whole chain of things that you've done -- it also takes into account what you're seeing; it understands that your next query is often based on what you've just seen, and will pull results from that context. They are trying to push answers to you for questions you haven't even asked yet. We're giving them signals all the time through our actions online and even our conversations.
Keywords To Intents
By now, you've all heard of RankBrain, which is a major factor in the way Google determines it's ranking results. RankBrain is what we refer to as machine learning, or artificial intelligence. It is smart enough to understand the intent, rather than the keywords. It makes decisions based on history and previous experiences, and learns context as it's used. The point of it is to understand what people are looking for based on the searches, rather than trying to match the keywords to the content found on the websites. Theoretically, we can calculate that intent is derived from a mix of implicit signals, keywords and compound queries.
Web Search To Data Driven Search
We've shifted away from "web search" entities. When consumers search for something on Google now, the absolute last thing they want to see if a list of 10 blue hyperlinks. It's too much work -- they want answers now, and they expect Google to give them those answers. Google now aims to return a card, or something called the Knowledge Graph, when you ask for knowledge based data (factual information). It's a data base of facts and will include the information Google suspects you're the most interested in. Google is trying to return more than a bunch of links, they want to supply you with the answer. They don't want you to have to keep looking.
Knowledge graphs and data partnerships return massive portions of the results, but they're also taking in everything else -- figuring out facts from the instructed internet. They're building this knowledge graph from the unstructured content. This is where SEO comes in, but consumers are demonstrating to Google that they are no longer looking for web pages -- they're looking for answers and solutions.
This article here from Benedict Evans is interesting if you're smarter than I am, but he does nail down one important question -- if you could have an immediate, fluid and simple way to engage your customers through a conversational interface, rather than persuading them to download your app, why wouldn't you?
So what does all of this mean?
It means that voice assistants are completely changing the way SEO functions. It means that pretty soon, web results might be completely skipped over, in preference of delivering answers and solutions, rather than results, directly within the interface you're using to ask for assistance. It's going to completely change the way companies approach SEO.
Will SEO even exist in 10 years?
The most ironic part about this though, is that it appears that the searches from personal assistants may soon be bypassing the search engines altogether.
Who actually uses a Personal or Voice Assistant?
It turns out, most of us. According to this study published by Thrive Analytics, 71% of 18-29 year olds who use smartphones, use a mobile personal assistant. Surprisingly, they also report that 59% of 30-43 year olds and 39% of 44-53 year olds do the same. The most shocking number though, is that 38% of users older than 54 years of age are also using a mobile personal assistant. These numbers simply demonstrate how "normal" this technology has become, and it will no doubt be forcing companies to change along with it.
A study by Northstar Research (commissioned by Google) gave us information on what people are actually searching for with their voice assistants. Teens mostly use it for placing a phone call, asking for directions, getting help with homework or playing music. Adults use it most often to ask for directions, dictate test messages or place a phone call. The study found that 55% of teens and 41% of adults actually access their voice search more than once each day. This study also gives a lot more detailing, including where people are when they use it and what their wish list is for future searching and finding options.
So what does all this mean for search engines? It's mind boggling to think about how much search has changed over the last decade.
This video is of a talk by Will Critchlow, on how the future of search is changing dramatically -- it's close to 40 minutes long but absolutely riveting if you're into the evolvement of search engine results.
Some of Will's talking points really touch on how much voice assistants have changed and shaped the way Google now delivers search results, and I'll discuss what stuck out at me below.
Implicit Search
Explicit search has migrated to implicit search -- partly due to mobile devices. This means that the search engines are using history and other signals to determine what those explicit search terms actually mean. Consumers have to give less and less explicit information, due to the capabilities of implicit variables. For example, Google has stated they'd like to be able to deliver you the correct bus schedule, based on what side of the street you're standing on when you perform the search. The explicit information is your search "main street bus schedule" but the implicit variables are what Main Street you'r referring to, and what direction you intend to go in.
Compound Queries
In 2013, Google released their new algorithm update, which they called Hummingbird. It was an infrastructure update that allowed Google to start incorporating machine learning and natural conversations into their results. Queries are no longer independent from one another; answers are inputs along with additional inputs from your first query. They are no longer delivering a separate sets of results based on each question that you ask. Google understands the whole chain of things that you've done -- it also takes into account what you're seeing; it understands that your next query is often based on what you've just seen, and will pull results from that context. They are trying to push answers to you for questions you haven't even asked yet. We're giving them signals all the time through our actions online and even our conversations.
Keywords To Intents
By now, you've all heard of RankBrain, which is a major factor in the way Google determines it's ranking results. RankBrain is what we refer to as machine learning, or artificial intelligence. It is smart enough to understand the intent, rather than the keywords. It makes decisions based on history and previous experiences, and learns context as it's used. The point of it is to understand what people are looking for based on the searches, rather than trying to match the keywords to the content found on the websites. Theoretically, we can calculate that intent is derived from a mix of implicit signals, keywords and compound queries.
Web Search To Data Driven Search
We've shifted away from "web search" entities. When consumers search for something on Google now, the absolute last thing they want to see if a list of 10 blue hyperlinks. It's too much work -- they want answers now, and they expect Google to give them those answers. Google now aims to return a card, or something called the Knowledge Graph, when you ask for knowledge based data (factual information). It's a data base of facts and will include the information Google suspects you're the most interested in. Google is trying to return more than a bunch of links, they want to supply you with the answer. They don't want you to have to keep looking.
Knowledge graphs and data partnerships return massive portions of the results, but they're also taking in everything else -- figuring out facts from the instructed internet. They're building this knowledge graph from the unstructured content. This is where SEO comes in, but consumers are demonstrating to Google that they are no longer looking for web pages -- they're looking for answers and solutions.
This article here from Benedict Evans is interesting if you're smarter than I am, but he does nail down one important question -- if you could have an immediate, fluid and simple way to engage your customers through a conversational interface, rather than persuading them to download your app, why wouldn't you?
So what does all of this mean?
It means that voice assistants are completely changing the way SEO functions. It means that pretty soon, web results might be completely skipped over, in preference of delivering answers and solutions, rather than results, directly within the interface you're using to ask for assistance. It's going to completely change the way companies approach SEO.
Will SEO even exist in 10 years?
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