Why User Intent Matters in SEO and Content Marketing [Video]

User intent (search intent) is the goal a user wants to reach with the query they type into a search engine.

Picture this. You are a company that sells artificial turf exclusively for five-a-side football pitches. Your turf is rubber-backed and cannot be used in gardens.

You want organic traffic from Google to grow your sales. Which keyword would you want to rank on the first page for?

Did "artificial turf" come to mind first? It did for me.

But when I researched the term, the people making that search were not looking for football pitches at all. They wanted good-looking, even colourful, artificial grass for around the house and the garden.

Is that our audience? No. This is exactly where user intent becomes decisive, and where the keywords we want to target change.

Let me give you another example from my own work.

A client of mine manufactures sound-absorbing foam for insulating rooms such as music studios and cinemas. When we first met, they asked me to raise their visibility for "sound insulation".

Looking at the keyword, its volume was higher than every other term we could target in the sector (7K).

But the people making that search are mostly browsing for information and ideas. Their intent to buy is weak.

We did succeed with the keyword the client wanted, but alongside it we targeted terms such as "sound insulation foam" (3K volume).

This time I made my point with data: there was a threefold difference between the unique traffic-to-conversion rate of the sound-insulation page and that of the sound-insulation-foam page. Even though we ranked second for both terms, the "foam" page produced more conversions and a better rate.

That way of thinking is what we have to change. We should start with research and build our content already knowing what the person making the query wants.

"Produce the content in the way that best matches the purpose behind the query."

So how do we analyse user intent?

Let's go a little deeper and find new ways of uncovering intent.

What are the four types of search intent?

The four types of search intent in the common SEO classification are informational, navigational, commercial investigation and transactional. The table below gives each type with the user's goal, an example query and the content type that matches it.

How does Google classify user intent?

Google classifies user intent into four query types in its Search Quality Rater Guidelines: Know, Do, Website and Visit-in-Person. A Do query aims to accomplish a goal, such as buying or downloading something. The guidelines call some Know queries Know Simple queries, which ask for a single fact. One query can carry more than one intent, and the guidelines separate its dominant, common and minor interpretations. Raters score how well a result meets the user's intent on the Needs Met scale, from Fully Meets to Fails to Meet.

Google's page on ranking results states that Search first establishes the intent behind a query to return relevant results. Words like "cooking" or "pictures" in a query tell its systems that recipes or images may match the intent best.

Using the SERP to understand intent better

The search engine results page (SERP) shows which intent dominates a query. We cannot know the intent behind every query with total certainty, because different people make the same search for different reasons. What we want to find is which intent dominates. Then we build our strategy around it.

At this point we have to trust the SERP, because Google knows user behaviour better than we do. Search results cannot serve every intent at once, but they will surface the one most often intended.

Of course, trusting the top-ranked sites blindly on every topic would be a mistake. There will be times when our own judgement or our own data has to come first.

Which SERP features point to search intent?

SERP features point to search intent because Google picks the result types that match the intent it detects. Five patterns help you read them.

• Product listings with prices: commercial or transactional intent.
• A map with local business listings: local intent, as in Google's own "pizza" example.
• Image or video results near the top: the user wants to see or watch something.
• A featured snippet or a "People also ask" box: informational intent.
• A brand's own site with sitelinks in first place: navigational intent.

What do Google's click records say about search intent?

Google's click records show search intent in action: which result users chose for a query and how long they stayed on it. In the US Department of Justice (DOJ) case against Google, a January 2025 note of a call with Google engineer Pandu Nayak describes NavBoost. NavBoost measures how many times users click a document for a query, by location and device type, over the most recent 13 months. A February 2025 note with engineer HJ Kim defines clicks (C) as how long a user stayed on a linked page before returning to the results page.

The leaked Content Warehouse documentation contains a PerDocData attribute called asteroidBeltIntents, described as "for indexing Asteroid Belt intent scores". PerDocData holds per-document data. The module behind the attribute keeps intents and scores in parallel lists, with scores scaled to integers between 0 and 100. The module page lists no intent names, and the weight and live use of the scores are unknown. These records support three checks in intent research.

• Check the results on mobile and desktop from your target location: your visitors see those versions, and NavBoost splits its data by both.
• Answer the dominant intent on the first screen, so the visitor has no reason to return to the results page.
• Keep one dominant intent per page, as the grouping section below recommends.

My post on measuring leak signals on your own site explains the same limit: a field shows what Google stores, not how ranking uses it.

Reading intent with help from Ads

Google Ads bid data helps to find the queries with strong purchase intent. Say we want to target the users with the strongest intent to buy. When we sort the relevant terms by top-of-page bid in the Google Ads Keyword Planner, we can assume competition is high on the highest-bid keyword. We can infer that the people searching those competitive terms have a stronger purchase intent.

Reading intent from the organic results

Search your target keyword on Google and study the first five results. Looking at the content of those five pages you will find shared patterns, and those patterns let you interpret the user's intent.

The top three results are likely the pages that answer the intent best, which makes them particularly worth studying.

Modifiers that change the intent of a query

Some words, added to the beginning or the end of a query, change the user's intent entirely. People searching "13 inch macbook", for instance, may want specifications and prices.

But someone searching "best 13 inch macbook" wants a comparison. In those results we see comparison pages ranking first.

Anyone who wants to dig further into the words that change query intent should read Moz's article on the subject.

Another example: a simple plural can change the intent too. For "seo tool", Ahrefs ranks first.

For "seo tools", a page listing tools takes first place.

As this example shows, the plural changes the search intent: users want a result that lists tools and lets them compare.

How to group keywords by intent

To group keywords by intent, we can split the keyword list we plan to target into intent-based categories, grouping terms whose intent is the same or similar. Then we can produce content that serves the purpose of each group. To find topics for that content, see my article on coming up with new content ideas.

But hold on: for me to sell, the user has to reach the product page. Doesn't it hurt conversion if someone who wants a comparison lands somewhere other than the product page?

You cannot make someone who came to compare do something outside their purpose anyway. Perhaps they are comparing one last time before buying. Serving a user something outside their intent will hurt SEO performance too.

Intent-based grouping for e-commerce sites

E-commerce may be the sector where user intent matters most. Let's split intent into four groups: ready to buy (transactional), researching products (navigational), gathering information (informational) and not going to spend anything (other).

1. The group closest to buying (transactional)

People closest to purchase are generally ready to pay, and this is where we can capture the highest conversion rate. Their searches carry modifiers such as "buy", "coupon", "discount" and "free shipping".

2. Product researchers (commercial investigation)

Product researchers want to examine products before deciding. We need to help them with the landing page best suited to persuading them. This group uses modifiers such as "best", a brand name, or "cheap".

3. Informational queries

Queries made to learn something convert less well than the first two groups. This group uses phrases such as "how to buy".

4. The ones who will not spend (other)

The users who will not spend search with words such as "free", "gratis" and "download". Converting them is the hardest job of all. Build a mailing list and aim for conversion later, when they are in a position to buy.