User intent

User intent, otherwise known as query intent or search intent, is the identification and categorization of what a user online intended or wanted to find when they typed their search terms into an online web search engine for the purpose of search engine optimisation or conversion rate optimisation.[1] Examples of user intent are fact-checking, comparison shopping or navigating to other websites.

## Optimizing For User Intent

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To increase ranking on search engines, marketers need to create content that best satisfies queries entered by users on their smartphones or desktops. Creating content with user intent in mind helps increase the value of the information being showcased.[2] Keyword research can help determine user intent. The search terms a user enters into a web search engine to find content, services, or products are the words that should be used on the webpage to optimize for user intent.[3]

Google can show SERP features such as featured snippets, knowledge cards or knowledge panels for queries where the search intent is clear. SEO practitioners take this into account because Google can often satisfy the user intent without having the user leave Google SERP. The better Google gets in figuring out user intent, the less users are going to click on search results. As of 2019,[update] less than half of Google searches result in clicks.[citation needed]

## Types

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Though there are various ways of classifying the categories of user intent, overall, they tend to follow the same clusters. Until recently,[when?] there were three broad categories: informational, transactional, and navigational.[4] However, after the rise[5] of mobile search, other categories have appeared or have segmented into more specific categorisation.[6][7] For example, as mobile users may want to find directions or information about a specific physical location, some marketers have proposed categories such as "local intent," as in searches like "XY near me." Additionally, there is commercial search intent, which is when someone searches for a product or service to know more about it or compare other alternatives before finalizing their purchase.[citation needed]

See the major types with examples below:

Informational Intent: Donald Trump, Who is Maradona?, How to lose weight?

Navigational Intent: Facebook login, Wikipedia contribution page

Transactional Intent: Latest iPhone, Amazon coupons, cheap dell laptop, fence installers

Commercial Intent: top headphones, best marketing agency, x protein powder review,

Local Search Intent: restaurants near me, nearest gas station,

Many search queries also have mixed search intent. For example, when someone searches "Best iPhone repair shop near me" is transactional and local search intent. Mixed search intent can easily happen with homonyms and such SERPs tend to be volatile because user signals differ.[citation needed]

User intent is often misinterpreted, and thinking that there are just a few user intent types is not giving the complete picture of the user behavior.

It is also a term to describe what type of activity, business or services users are searching for (not only the user behavior after the search).

Example: when you write 'Spanish games' in the search engine (your browser settings in English) you have results for learning Spanish methods, not a real games with Spanish origin. In this example, the user intent is to learn Spanish language, not to play typical games. This intent is reflected by Google and the other search engines, and they strive to display their SERP results based on the user interest.

## See also

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* Keyword research
* Intent marketing
* Search engine result page
* Principle of least astonishment
* Mobile marketing

## References

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1. ^ Jansen, Jim (July 2011). Understanding Sponsored Search: Core Elements of Keyword Advertising. New York, NY, USA: Cambridge University Press. p. 44\. ISBN 9781107011977.
2. ^ "How to Create a User-Intent SEO Strategy". 28 September 2018.
3. ^ L., Ledford, Jerri (2015). Search engine optimization bible, 2nd ed. Wiley. ISBN 978-1-118-08081-8. OCLC 933401063.`{{cite book}}`: CS1 maint: multiple names: authors list (link)
4. ^ Broder, Andrei (Fall 2002). "A Taxonomy of Web Search" (PDF). SIGIR Forum. 36 (2): 5–6. doi:10.1145/792550.792552. S2CID 207602540. Retrieved 27 December 2016.
5. ^ "The Rise of Mobile Search: From 2012 to 2015". Texo Design. Archived from the original on 6 July 2018. Retrieved 26 December 2016.
6. ^ KhudaBukhsh, Ashiqur; Bennett, Paul; White, Ryen (2015). "Building Effective Query Classifiers: A Case Study in Self-harm Intent Detection" (PDF). CIKM '15 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management: 1735–1738. Retrieved 26 December 2016.
7. ^ Search Quality Evaluator Guidelines (PDF). 28 March 2016. pp. 61–74. Retrieved 26 December 2016.