As SEO priorities have shifted from a focus on keywords to a more content-centric approach over the years, the search intent topic has grown in popularity accordingly – and rightly so.
Nowadays, most SEO experts agree that content created for specific user intentions isn't just more useful to visitors. It is more likely to rank in search engines when it matters most.
Search engines (especially Google) have invested heavily in determining user intent for a given query and have found that users are happier when the content not only matches a keyword but also takes into account the intent of their search.
For example, better intent matching is an element of Google's BERT project (the AI natural language processing engine that detects the intent of a search query).
With BERT now affecting nearly 100% of searches, it's time to dig deeper into the topic of user search intent.
Traditional categories for user intent
While search intent has been an issue for SEO pros and content marketers, we've relied on some fairly broad categories of user intent.
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The list varies depending on who you ask, but these often include:
- Information: The user is looking for knowledge on a topic. These are usually who / what / when / where / why / how queries, although they don't need to contain these words.
- Navigation: The user wants to go to a specific site or page. Usually this user has a specific task in mind or knows / suspects the location of the information they are looking for.
- Transaction: The user wants to buy something even though the transaction doesn't have to be monetary. This user is ready to take action.
- Local: The user is looking for a resource that is geographically close to their current location (or a specified location).
These traditional categories have served us well as they nicely summarize (at least broadly) the top reasons someone goes to a search engine.
They help SEO experts and content managers plan and create content that is more useful to certain users and therefore more valuable to search engines.
From broad to small intentions
However, as with such broad categories, it can often be useful to break them down further.
For one thing, we can be pretty sure that search engines are using some form of the traditional user intent categories listed above, but it's likely that machine learning tools like BERT will allow them to go deeper and see what we might call micro-intentions.
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Google has talked about the usefulness of increasing the granularity of broad categories in other contexts. A good example is the concept of micro moments.
Micro moments are an enhancement of the traditional understanding of customer travel.
The concept goes beyond the traditional funnel categories. In the online arena, consumers often have many small steps on multiple devices that influence their final purchase decision. Studies on this subject underpinned Google's “zero moment of truth” concept, a complement to the traditional marketing journey.
The “Zero Moment of Truth” (ZMOT) consists of all interactions that a consumer can have over time with numerous devices, which together influence their final purchase decision.
We can use a similar model to develop what I call "micro-intentions" – the smaller, multiple search intentions that one might have within the larger traditional categories of user search intentions.
Why Micro Intentions
Remember, the "O" in SEO stands for "optimization".
Search optimization is about providing the most authoritative and relevant response to a query in the most user-friendly way possible.
Micro-intentions play a role in the middle of this triad of authority / relevance / usability: They improve the relevance of content for specific user requirements to a greater extent than is only possible with the “big four” traditional intention categories.
Winning Micro Intent Searches can lead to significant wins over time, much like how an SEO pro would increase authority by getting more targeted links or improve the usability by gradually changing the page speed.
Where micro-intentions come in handy
Admittedly, the benefits of micro-intentions are greater for some of the four big intentions than for others.
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For navigational and local user intentions, the number of microintentions equals the variety of queries.
The micro-intent is inherent in the query itself.
Someone searching for "Microsoft website" clearly wants to go to microsoft.com, while the person searching for "Pizza North New Jersey" is obviously looking for the best pizza on the planet.
My micro-intent concept is most useful for information and transactional queries. So let's see what this looks like in these categories.
Some suggested micro-intentions
Research data on what these micro-intentions are does not yet exist to my knowledge.
However, we can make some reasonable assumptions about the information and transaction categories.
I'll start with the tweet from Mordy Oberstein who inspired this article:
Something I've been thinking about.
"We" write things to "inform" – you know "information intention"
I hate that term.
I think we should write to educate – educational intent.
One focuses on the content, the other on how the reader will take that information! pic.twitter.com/SzXsJ4c09P
– Mordy Oberstein (@MordyOberstein) December 17, 2020
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I disagree with Mordy.
I don't think education is a substitute for informational intent. Rather, it is a microintention of the "information intent" category.
Educational content is also only one type, although this is probably the largest subgroup of that category.
What is the educational content like? a more specific type of information content?
I think educational content is the one that is very detailed on a subject. It satisfies the user who wants more than a quick answer or a specific fact.
Educational content is created for users who want to expand their knowledge on a subject. getting away to know a lot more about it than before they entered their request. It is therefore usually longer than most other forms of informational content.
What are other possible micro-intentions in the information category?
- In fact: The user wants to learn or verify a certain fact.
- Manual: The user wants to know how to do something.
- Expansional: The user wants related topics or expansion areas on a basic topic.
- Aggregational: The user wants to see a variety of thoughts or opinions on a topic.
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Can you see that each of this content requires a certain type of content?
This is a valuable context that "information" alone does not provide.
To become the most relevant answer for certain groups of users, you need to think beyond the four broad categories.
Many transactional queries are self-contained micro-intent, similar to how local and navigational intent queries work.
That is, they contain the micro-intention in them. An example would be "Buy a Nikon d5600 digital camera".
However, there are real micro-intentions for less specific transactional queries.
Here are some examples:
The user wants to buy something but doesn't necessarily care Which of this kind they will buy.
Users just want to see a display of the options and make their choices from there.
This may seem like an information query, but it isn't (for search purposes) as this user is ready to buy.
Finding additional information before purchasing is not a top priority.
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This is an excellent example of how the four great intentions can merge.
This user is ready to buy and just wants to know Where to buy it.
Although the “where” does not have to be a physical location, elements of informative and local intent play a role.
For that microintention, you want to be the best option in every way.
This user doesn't care what brand they buy. They only want to buy what they need.
Information on a landing page for this microintention needs to go beyond the brands available to focus on other differentiators (price, features, etc.).
Micro intentions & content strategy
The concept of micro-intent is most useful for SEO professionals and content strategists looking to increase traffic and website revenue by expanding the range of queries they are ranked for.
At some point, after all of the high-volume head terms have been optimized for your market, such growth can only be achieved by digging deeper into long-tail searches.
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This is where designing content for micro-intent is likely to produce better results than just relying on the traditional four big intentions.
Remember, Google is actively trying to improve its ability to match user requests with content that is exactly what they intended. And with BERT technology, it is very likely that they will do so on a level that is much more detailed than that of the big four.
This means that there is significant traffic to be gained on the sites where most content can be created for micro-intent.
How do you know which micro-intent categories are being searched for in your subject areas?
A great resource, at least for information requests, is Google's People Also Ask. The specific questions people ask can be clues about micro-intentions.
Another may be Google Question Hub (just opened to US publishers when I write this article).
Listening to your customers, speaking to your sales and customer service reps, and analyzing your internal site search analytics can also provide useful clues about micro-intentions in your marketplace.
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Screenshot by the author, January 2021