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In the SEO world, it’s easy to get preoccupied with our keywords, however it is important to understand that even though on a micro level the user might be interacting with the search engine through keywords, but on a macro level, the search query in its entirety comes to define the results that Google, or any other search engine, displays.

With search queries being the starting point for many users, it makes sense that we would want to understand search queries a little better in our pursuit of world (wide web) domination.

 

Types of search queries

Traditional search queries can be categorized into informational, navigational, and transactional queries. These categories were first introduced in 2002 by Andrei Broder in his paper “A taxonomy of web search”. Informational queries account for 80% of search queries whereas navigational and transactional queries account for roughly 10% each.

-With Informational search queries the intent is to get more information on a certain subject.
For example: The query might be a head term like “Kobe Bryant” where the user is trying to find out more information about Kobe Bryant; or a more specific query like “How tall is Kobe Bryant”.

-A Navigational query is when the user wants to go to a specific website or webpage.
For example: “youtube” with an intent to be directed to www.youtube.com.

-The intent behind Transactional queries is to complete a certain transaction, like making a purchase.
For example: The search query might be a head term like “iPhone 6” where the user gets directed to the product website where the user makes the transaction and buys said product ; or the query might be more specific like “Buy iPhone 6”.

In a post-Hummingbird ,RankBrain world, you’d think that these categories would have been updated since 2002.

And Google did!

 

Google search query categorization

After Andrei Broder first introduced the categories, Google, in their human rater guidelines, categorized search queries into

Do: User intent to do something
Know: User intent to know something
Go: User intent to go somewhere

With this Do-Know-Go framework, Google intended to encompass broader queries. And no matter how similar to  Broder’s,  this framework was designed for web-specific needs. But the fact is, with the advent of Intelligent Personal Assistants (IPA) like Siri and Google Now, not all search queries are typed into web based search boxes. Users can now simply ask their IPA’s queries, with an expectation to be presented with relevant results and answers for their query.

If you need further proof about the the impact of Intelligent Personal Assistants you need only look at what the major tech giants are doing.

 

Search query IPAs

 

Whether you consider Intelligent Personal Assistants to be the next big gimmick or you actually find them to be useful. The fact that these 5 tech giants decided to invest their time and money into creating their own IPA’s is a clear signal that you need to take IPA’s into consideration while creating any long term marketing plan for your business.

 

How will these intelligent assistants alter the way we search?

With IPA’s users are no longer having to type in their search queries, they can simply voice their queries and expect their phones/computers to deliver relevant answers.

Google’s language and contextual comprehension is continually improving. With updates such as Hummingbird, and more recently Rankbrain machine learning, it is enabling users to input search queries which are far more complex and specific, taking focus away from head keyword searches and moving towards more conversational search queries.

IPA’s are not only affecting search queries but also search results. With the introduction of the knowledge graph Google in its handling of a particular search query like “How old is Roger Federer” you’re likely to see a result like this

 

search query knowledge graph result

 

 

instead of the old Google SERP of 10 blue links which would further force you to click on a particular website like Wikipedia and scan the web page to find the answer to the query.

However in the age of IPAs such as Apple’s Siri, if a similar query such as the one used above were to be asked, it is likely that there isn’t even a web search conducted, and data driven answers provided within the app itself.

Further, with IPAs, you can now perform follow up search queries pertaining to the subject, without the need to re-provide context from the preliminary query. In this case you would maybe ask a follow up like “How many Grand slam titles has he won?”

These are complex compound queries.

For a more in-depth look at compound queries and data driven search, check out this post  by Tom Anthony on the Moz blog.

With the rise of IPAs and consequently, conversational queries; relying on the Do-Know-Go framework would be inadequate.

But don’t worry, Google’s got you covered!

 

Google’s updated search query categories

In November of 2015, Google officially released its 160 page Search Quality Rating Guidelines (further revising it into a 146 page document) in which it proposed a new framework to categorize search queries.

Here are the categories directly transposed from the document:

 

  • Know query, some of which are Know Simple queries
  • Do query, some of which are Device Action queries
  • Website query, when the user is looking for a specific website or webpage
  • Visit-in -person query, some of which are looking for a specific business or organization, some of which are looking for a category of businesses

 

 

Know Queries are queries where the user has an intent to know more about something

Know Simple Queries are a subtype of Know queries wherein the answer to the query is short and concise. If a majority of people agree on the answer and it can be answered in a couple of sentences we can classify the query as know simple

Do Queries are queries where the user has an intent to do something.  Whether that something is to download an app, to buy a product, interact with a web page etc., they can all be classified into do queries.

Device Action Queries are a type of ‘do queries’ where the user wants their device to do something for them.

Website Queries are queries where the user wants to be directed to a specific website. Google refers to this website as the target of the website query.

Visit-in-person queries are queries where the user wants to find a particular place, for instance “nearest pizza restaurant /bank/ movie theatre”.

It is also important to remember that a lot of these queries will overlap. A certain query might belong to more than one category. For example: a query like “facebook” might have a user intent of going to the website and then going to the about page to find out more info about the website. So you could categorize that query into a website query and a know query.

 

How does this affect SEO’s?

Now that we’ve got an up to date framework, we can categorize queries to better understand the user intent behind each query, and thereby create content specific to user intent.

At the core of search queries is user intent. From the point of view of a business, understanding the role of search queries and where they fit into the buying cycle will help us target certain queries, enabling us to optimize our strategy to fulfil the user’s exact need.

So let’s align this framework with the stages in the buying decision process

There are many versions of the buying process. But for the purpose of this post I’ll be using the 5 stage model developed by researchers Engel, Blackwell, and Kollat in 1968.

  1. Problem/Need recognition
  2. Information search
  3. Evaluation of alternatives
  4. Purchase decision
  5. Post-purchase behavior

Here’s a simple table I made, which should be helpful:

 

Search query type to buyer cycle alignement table

 

Basically I’ve assigned a number to every query type and filled out the possible query types associated with various stages in the buying cycle.

Let’s dive a bit deeper

 

Problem/Need recognition

At this stage of the buying process, the consumer recognizes that there is a problem and are on the lookout for a solution to that problem. They are asking themselves “What do I need?”

Search queries associated with this stage might be know queries to get more information about the problem. If you’ve built up a brand, consumers might think of your product as a possible solution without even typing in their query. So they might enter a website query to get directed to a trusted website/blog where the consumers might find out more about the problem and further, how to alleviate this problem.

What should you do?

You content strategy comes into play in this stage, posts which highlight common problems and solutions in your niche. A relatable post like “common SEO mistakes and how to solve them” highlighting common problems which consumers might be facing and will resonate with consumers and make them more likely to adopt your offered solution.

 

Information search

In this stage, consumers have a proper understanding of the problem they’re facing and are now looking to find out at much as possible about possible solutions. They are trying to figure out the “Best way to solve this problem?”

Consumers might in turn use know, and know simple queries to aid in their research process. They might also use website queries to be directed to a particular website/forum where problems in the relevant niche are being discussed (for eg. Quora, reddit).

What should you do?

This is where the tireless work you put into your SEO comes in handy. Basically ‘being found’ is the primary goal at this stage. So ranking highly on the SERP’s will help you get more visibility and make it more likely that a consumer will look at your product and further consider it as a possible solution.

Also leverage your content strategy to shift focus to solution oriented posts, rather than the problem centric posts from the previous stage.

 

Evaluation of alternatives

At this stage of the buying cycle, consumers have figured out a solution to their problem but are now taking a step back and looking at alternatives to figure out if indeed the selected solution is the best choice to solve their problem. The question in their minds is likely, “Which solution best fits my needs?”

Consumers turn to know and know simple queries to find alternatives and competitors to their selected solution.  They might also use website queries to navigate to review websites, or search for websites that do comparative studies/research (for eg. Cnet, Trustradius, Gsmarena). We might also see visit-in-person queries if the consumer would rather go to a brick and mortar store to inquire about the product. For instance asking sales reps/experts about alternatives, product sales info, trends etc.

What should you do?

This is may be the most important stage from the viewpoint of a business, since this is the decision making stage for the consumers. They’ll decide whether they should go with your product, or an alternative, or back out of the buying process altogether for lack of a proper solution fitting their needs. Pull out all the stops here.  Optimize your content so the consumer is fully aware of all your features and how it solves their problem. At the same time, also reassure and inform your consumers about post purchase features such as support and warranty. And make sure you’ve got your pricing on point.

Essentially this is the stage where you’re in a head to head with your competition. So make sure you do everything you can to end up on top.

 

Purchase Decision

Consumers in this stage have chosen their solution and made a decision to purchase that solution. They now ask themselves “How do I make this purchase?”

Do queries will be prevalent in this stage to buy their selected solution. Consumers might also use device action queries to make the purchase. Website queries to navigate to the official website of the solution where the consumer makes the purchase could also be a possibility. Visit-in-person queries might come into play if consumers are more comfortable making a purchase in person.

What should you do?

The consumer wants to buy your product. So make it a frictionless process for them to consume your product. Work on your ‘buy’ CTA’s (call to action) and streamline the buying process making it even easier for consumers to buy your product.  Also now that you’ve converted, don’t forget to look at your analytics/metrics to replicate this conversion and figure out where you can improve your marketing even further.

 

Post-purchase behavior

Consumers in this stage have made their purchase and are now evaluating the product to figure out whether the product solved their problem or not. They ask themselves “Have I made the right purchase?” “Am I satisfied with my purchase?”

Consumers might rely on know queries to find out more information about the product post purchase. Do Queries to get in touch with support. Website queries to navigate to the official website of the product, websites of online communities of users of the product.

Satisfaction levels in this stage will be paramount in a consumer’s decision to repurchase products from your business in the future. If a customer is satisfied it’ll lead to brand loyalty which could mean elimination of the ‘information search’ and ‘evaluation of alternatives’ stage for future purchases. BOOM!

What should you do?

Focus on your post purchase customer support and service. Make sure that if a consumer is having difficulty using your product, you’re ready and available to help them through this process. You could also do this through your content, by posting “How to’s” and guides on using your product.

 

Conclusion

Search Queries have evolved, and with Intelligent Personal Assistants, queries are getting more complex and specific. This will give rise to a need for more focused and targeted content.

While developing your inbound marketing strategy, make sure to keep search queries and where they fit into the buying cycle, in mind. You’ll be in a much better place to make a judgement on user intent and that will enable you to dominate every phase of the buying process, further making the conversion-acquisition process easier.

But the good news is that with the added complexity and specificity it will become easier to judge user intent.  How you leverage this will make or break your business!

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