What is Search Intent & How can it be Enhanced using AI?

“Search Intent in SEO is getting useful answers to user’s intriguing questions over the world wide web.”

Ever since the inception of Google in 1997, it hasn’t made any change in its objective; that is,

“To serve People with the Best.”
“To offer the User the Best Answer to its Query.”

Fixing this one thing, the overlord has worked hard to modify the ways in which these goals can be achieved. Every search made on Google (or any other search engine) there lies a user, a person. And behind that person lies an intention, a need, and a reason to do that search on Google or any other search engine.

It’s seen frequently that while applying search engine optimization (SEO) marketing strategy, businesses usually focus on navigating and understanding various ranking factors to raise their authority and web visibility.

And in the wake of approaching SEO and occupying a higher position on SERPs, they often forget to realize and target the ‘human side of SEO.’

Well, Google’s Search Intent concept is an eye-opener for such a category of people to be able to get genuine results from an SEO campaign.

Search Intent

Is merely a concept that represents the primary goals of web users where they seek answers to their questions. It is what the user really wants to find on Google.

Search intent forms its basis on the search behavior that is further segmented into categories based on the user’s purpose and how it can help businesses (and websites) to boost their SEO results.

The search behavior and intent behind search habits are bifurcated into the following:

• Navigational search queries
• Informational search queries
• Transactional search queries
• Visit-in-person search queries

These are the main styles of internet searches that pave the path to understanding Search Intent Marketing, what people want, what is their motivation for making a purchase, and what intent urges them to take action.

#Navigational Search Queries
Here the visitor’s intent is to easily and nimbly reach out to a page or specific location and already know they need to land up. Say, a brand website or a social media login page.

#Informational Search Queries
Here the user’s intent is to reach a place seeking some sort of useful information. This is a broad concept where people get their fingers to type on Google and the search results display data via a rich snippet or a graph where many times they may not even click on a result. Say, ‘Where is India’, ‘history of the Britishers’, etc.

#Transactional Search Queries
Here the ultimate goal of a user is inclined towards making a purchase or completing any sort of a transaction. Say, people may eventually buy a product/service, request a quote, download software, fill out a form, etc.

#Visit-in-Person Search Queries
Here the search intent is to help people find a location or navigate to a place. This may include searches intended to find a restaurant, browse options for a storefront, or get directions to a landmark, etc.

How Google’s Vision Turned How To Respond To Search?

It was clear that both to take a significant step in the quality of its results and to break that game of cat and mouse with the Black Hat, Google had to go a step beyond a simple mathematical algorithm, however sophisticated it might be.

And the idea was to go from being a sophisticated mathematical algorithm, but ultimately dumb (which does not understand what it does) to an intelligent system that understands what it is doing at a level that is as close to human as possible.

Thus, the results would be of better quality and the system would be much more difficult to deceive. This is how Artificial Intelligence got into the algorithm. Personally, here I would highlight, above all, two aspects:

• The introduction of the Knowledge Graph in 2012 adds semantic understanding (that is, the meaning) of the relevant content and context.
• The analysis of user behavior in searches and landing pages, which gives Google very important clues about how well or badly the page in question responds to the search.

These are the two keys that redefined how you have to think today if you want to be successful in your SEO work.

[Prefer Reading: “What is Semantic Search?”]

How does Artificial Intelligence help to Enhance Search Intent?

Artificial Intelligence became part of Google’s strategy for delivering quality and relevant results for a user query as soon as the need for advanced technology became apparent.

Although the emergence of new technologies makes targeting and digital marketing easier and more effective, it cannot be disregarded that AI’s interference in digital marketing has radically changed its overall design.

The majority of customers today expect high accuracy, relevance, and instants in search engine results. In order to provide a personalized experience, the engines should cater to your needs – regardless of how you phrase your query or the exact wording you use. The use of artificial intelligence (AI) is on the rise within companies in order to improve their search engine capabilities.

Machine learning (ML) techniques are being tapped by companies to improve search relevance. Customer behavior and analytics in this field are applied in order to create machine learning initiatives that link customers with the things they want most.

AI-powered statistical analysis is used by many companies to determine search results. With this advancement, companies aim to establish what information is relevant for each individual based on several factors, including their organization’s objectives, the region of the user, the user’s history of interaction, and other provisional aspects.

To deduce interpretations and determine outputs of these complications, intricate algorithms are needed. In these situations, AI-powered search relevance will be most valuable.

A machine learning algorithm can further distinguish between low-quality and high-quality content and rank those based on their quality.

Using AI, search engine optimization (SEO) techniques that unfairly benefit from an algorithm can be identified (such as stuffing keywords into product descriptions or invisible text) and these results can be placed below high-quality, intent-driven results.

If you want to do modern SEO successfully, you have to be very clear about the concepts of search intent and keywords, and how they relate to each other. Now, with a much smarter Google, you have to understand very well what you are responding to as only then can you be successful in modern SEO.