Long-tail keywords are easy to overlook. Each one draws only a handful of searches a month, so they rarely stand out in a keyword list sorted by volume alone — but grouped together, they often make up the majority of a site’s search traffic.
That math matters even more now that AI search is in the mix: AI Overviews, Google AI Mode, and chat-based assistants increasingly answer specific, question-shaped queries directly, and long-tail phrasing is what you need to target if you want to show up in those systems.
Below, we’ll cover what long-tail keywords are, why they matter for search rankings and AI visibility, how to find them and rank for them, and how to track your progress.
What are long-tail keywords?
Long-tail keywords are highly precise search engine queries people use when they’re searching for something specific or searching conversationally. These queries attract relatively low search volumes and face relatively low competition.
Here’s a long-tail keyword example:
Long-tail vs. mid-tail vs. short-tail keywords
Long-tail, mid-tail, and short-tail keywords differ in specificity, search volume, and keyword competition. Long-tail keywords are the most specific, short-tail keywords are the broadest, and mid-tail keywords sit between the two.
The line between mid-tail and long-tail keywords is blurry. Instead, categorize keywords based on your judgment of their specificity, popularity, and competition levels within the context of your niche.
Why are long-tail keywords important in SEO?
Long-tail keywords are important in search engine optimization (SEO) because they’re relatively easy to rank highly for, they can drive high-quality traffic, they have high collective search volumes when grouped, and they can help you appear in AI-generated responses.
They’re relatively easy to rank highly for
Long-tail keywords are relatively easy to rank highly for because they’re specific and relevant to fewer websites.
This makes long-tail keywords less competitive than broad keywords. You can evaluate keyword competition for any term by analyzing the search engine results page (SERP). The lower the quality of the top websites and webpages, the easier it should be for you to earn a high ranking.
Alternatively, use Semrush’s keyword tools to analyze the below keyword difficulty metrics:
- Keyword difficulty (KD %): Measures how hard it is to rank in Google’s top 10 results
- Personal keyword difficulty (PKD %): Measures how hard it’ll be for your website specifically to rank in Google’s top 10 results
They can drive high-quality traffic
Long-tail keywords can drive high-quality traffic because people who use precise keywords often have high buying intent — i.e., they know exactly what they’re looking for and are almost ready to take action.
For example, someone searching for a product with specific features is more likely to buy than someone searching for the general product type.
Because long-tail queries often signal stronger purchase or decision intent, optimize page copy and calls to action for conversion. Track outcomes like form fills or add-to-cart actions to measure the value these keywords bring beyond visits alone.
They can have high collective search volumes when grouped
Long-tail keywords can have high collective search volumes if you group them together based on search intent (what the user wants). By targeting these grouped keywords together on the same page, you can reach a larger audience than if you were to only focus on a single keyword.
For example, the long-tail keywords below have average monthly search volumes as low as 30. But the keyword group (or keyword cluster) has a collective search volume of 980, according to Semrush data.
Long-tail searches tend to be highly fragmented because there can be lots of different ways to phrase a complex query. In practice, that means grouping related long-tail queries onto a single consolidated page or FAQ hub, rather than creating one thin page per keyword.
With this approach, you can capture the whole cluster’s search volume without diluting your site with near-duplicate content.
They can help you appear in AI responses
Long-tail keywords can help you appear in AI responses because AI search is conversational, and long-tail keywords match that phrasing.
People engage with AI systems by typing specific, natural-language queries instead of short keyword fragments. Content built around those queries aligns more closely with what users type into ChatGPT, Google AI Mode, and similar platforms.
Two other mechanics make long-tail phrasing perform well in AI search:
- AI tools use query fan-out. AI systems expand a single query into many related sub-queries to gather a fuller picture before composing a response. Targeting a range of long-tail variations around a topic increases the number of these sub-queries your content can match.
- Long-tail sections are easier for AI systems to retrieve. AI Overviews and chat assistants pull specific passages, not entire pages, when composing an answer. A page built around clear long-tail questions — one question (heading) followed by one self-contained answer — gives AI systems a cleaner unit to extract than a page that only addresses its topic broadly.
For example, Canva’s highly specific content may help it appear in this ChatGPT response:
How to find long-tail keywords
Find long-tail keywords using a mix of research tools (like Semrush’s Keyword Magic Tool) and manual exploration. This includes:
- Using keyword research tools
- Exploring Google’s autocomplete predictions
- Analyzing Google’s People Also Ask boxes
- Looking at your current keyword rankings
- Checking competitors’ keyword rankings
- Asking AI chatbots for ideas
- Exploring online communities
- Using conversational and zero-volume long-tail keywords
- Performing prompt research
Here’s how to find long-tail keywords with each method.
Use a keyword research tool
Use a keyword research tool like Semrush Keyword Magic Tool to search a database of 28.8 billion keywords and filter based on various keyword metrics.
To get started, enter a term to base your search around. Then add your domain, choose your target country, and click “Search.”
The tool will display “Broad Match” keywords that contain your starting term or a close variation. You can select other match types, but this option tends to work best.
To focus on keywords most likely to be long-tail, filter your results based on search volume, PKD %, and word count.
For example:
- Volume: 0-1,000
- PKD %: 0-29
- Word count: 3+
Another option is to apply the “Questions” filter. Because question keywords are often long-tail by nature.
Once you’ve applied your chosen filters, analyze your results and save your favorite keywords to a list.
Explore Google’s autocomplete predictions
Google’s autocomplete predictions are based on real searches (among other factors) to help you find long-tail keywords for free.
Start typing relevant terms into Google’s search bar to see what long-tail predictions show up:
Just bear in mind that these predictions aren’t exhaustive and are personalized to you, so they aren’t necessarily the queries your audience is searching for.
Plus, you won’t have access to keyword search volumes or difficulty scores. You can get these metrics by entering your keywords into Semrush’s Keyword Overview tool, which is free to try.
Analyze Google’s People Also Ask questions
Google People Also Ask (PAA) boxes contain questions related to the user’s search, and these questions can be good examples of long-tail keywords.
Perform relevant Google searches to see if any PAA questions show up.
Alternatively, use a tool like AnswerThePublic to collect PAA questions in bulk.
Note that these tools won’t provide keyword search volumes or difficulty scores. To check these metrics, enter your keywords into Keyword Overview.
Look at your current keyword rankings
Look at your current keyword rankings to see if your website naturally ranks for any long-tail keywords.
Generally, you’ll find it easier to boost existing rankings than to earn new ones because you’ll already have a foundation to build on.
You can check your rankings for up to 1,000 queries chosen by Google in Google Search Console.
After signing in or setting up, go to “Performance” > “Search results.” Then, scroll down to the “Queries” table to look for long-tail keywords. Find ones where you are ranking in position 11-20. This indicates content close to ranking within the top 10.
Alternatively, check your rankings with Semrush’s Organic Rankings tool.
This tool lets you filter results based on keyword search volumes and difficulty scores, so it’s easier to find the long-tail keywords where you have the best chance of improving rankings.
Check your competitors’ keyword rankings
Checking your competitors’ keyword rankings to see what they rank for can give you ideas for relevant long-tail keywords, and you can do this with a tool like Semrush’s Organic Rankings.
Enter a competitor’s domain into the tool and go to the “Positions” report. Then, filter for low-volume, low-difficulty keywords to find the most probable long-tail keywords.
You can save your favorite keywords to a keyword list.
Ask AI chatbots for ideas
Ask AI chatbots like ChatGPT to provide long-tail keyword ideas based on your chosen topic.
Start with a seed term (a broad keyword) and ask an AI chatbot to generate a large batch of conversational variations grouped by sub-intent (comparison questions, how-to questions, troubleshooting questions).
For example, you could prompt: “Generate 50 long-tail, question-style search queries related to [seed term], grouped by whether the searcher is comparing options, troubleshooting a problem, or looking for a how-to.” That produces a structured list you can filter for relevance, instead of a handful of ad hoc suggestions.
Like this:
Bear in mind that AI chatbots don’t have access to real search engine data. They generate ideas based on what they’ve learned from analyzing high volumes of content. So, cross-check the results against real search data in Keyword Overview before prioritizing them.
Explore online communities like Reddit and Quora
Exploring online communities like Reddit and Quora gives you the exact language your audience uses when asking questions. And using this same language in your content can help you appear in the results when your audience turns to search engines and AI chatbots.
Use the search functions on these platforms to find relevant subcommunities or posts to explore.
Like this:
Because they’re so specific, these keywords might not appear in keyword databases and might not have measurable search volumes. But they could still be worth targeting.
Use conversational and zero-volume long-tail keywords
Conversational and zero-volume long-tail keywords are worth targeting even when your keyword tool shows no demand for them, as these are queries people are using in voice searches and AI chatbots.
Some of the highest-intent long-tail keywords show up as zero or near-zero volume in keyword research tools — that doesn’t mean no one’s searching for them.
Voice search and AI chat interfaces produce long, natural-language questions that keyword databases often can’t measure accurately, because there are too many close variations of the same underlying question for any single phrasing to register meaningful volume on its own.
A question like “what are family-friendly things to do near a downtown convention center on a weekday afternoon” might get typed a dozen slightly different ways — each showing zero monthly searches individually, while the underlying demand is real and answerable.
One way to find these ultra-specific queries is by reviewing your site’s internal search logs or your support chat transcripts. The exact phrasing customers use tells you how they naturally ask about your topic.
Because these keywords may never show meaningful search volume, judge them by whether you can answer them well and whether doing so serves a topic you already cover — not by a volume threshold.
Perform prompt research
Performing prompt research reveals the prompts your audience uses in chatbots like ChatGPT and Google’s AI Mode.
Semrush’s Prompt Research tool surfaces the actual prompts and questions people put to AI platforms for a given seed term, so you’re working from observed demand.
Enter your seed term and click “Analyze.”
Scroll down and click “Prompts” to view the prompts and topics people search in AI platforms, along with the responses they get.
Look for prompts with a high “Relevance” rating. And click the “#” in the “Brands” column to see which brands are mentioned in the AI response. Review their content to see how you can write something more helpful and authoritative to earn mentions and citations as well.
How to rank for long-tail keywords
To rank for long-tail keywords, you need to follow SEO best practices like adding keywords to your content, ensuring your site has no errors, and creating useful and relevant content.
Here are some of the most important tips for achieving high long-tail keyword rankings:
- Create keyword clusters. Group your keywords together based on search intent. You should then target grouped keywords together for a single page and prioritize clusters that seem the most valuable (for example, keyword clusters can be valuable if you think they’ll contribute to sales).
- Target keywords in the right places. Decide whether a long-tail keyword cluster deserves a dedicated piece of content or a subsection within a broader page. This depends on the search intent and your wider content strategy.
- Focus on helpfulness. Create unique, helpful content that addresses the target user’s precise needs. Only choose keywords that complement your topical expertise as both search engines and AI systems value sites with authority on a specific topic.
- Use keywords naturally. Try to naturally incorporate keywords into your page’s title tag, heading tags, alt tags, and body content. Always prioritize the naturalness of your content over matching a keyword exactly.
- Create search-friendly filter pages. Consider optimizing your most important filter pages if your website has filtering options (e.g., for product price and color). This mainly involves making them accessible to search engines and adding unique content.
- Use relevant schema markup. Use schema markup to help search engines understand and display different types of data on your page. For example, FAQ schema could help search engines identify questions and answers.
- Build internal links. Link to long-tail pages from related pages on your site. This helps search systems and users to discover these pages and understand their relevance.
- Structure content for AI retrieval. Write each section so it can stand alone: a clear heading, a direct opening sentence that answers the question, and enough context that the section makes sense without the rest of the page. This is what lets AI systems pull your content into an answer, and it also makes pages easier for human readers to skim.
How to find long-tail keywords for PPC
Find long-tail keywords for pay-per-click (PPC) marketing by looking for keywords with low competition and low costs per click (CPCs) for sponsored results in search engines.
Sponsored results can take a few forms. This example SERP features product listing ads and a traditional paid search ad:
You can find low-competition, low-CPC keywords by using these keyword metrics in our keyword research tool:
- Competitive density (Com.): A score of 1.00 represents the highest level of competition among advertisers, while a score of 0.00 represents no competition among advertisers. The competitive density you choose depends on your business, but we recommend filtering between 0 and 0.2 for the least competitive terms.
- CPC: The average amount an advertiser pays per click, in U.S. dollars. The right range depends on your industry, so start by filtering between $0 and $0.50 and adjust from there.
Long-tail keyword examples
Here are real examples of how SaaS, local, and ecommerce websites have used long-tail keywords to attract high-quality traffic.
SaaS long-tail keyword example
SaaS companies can capture long-tail traffic by building landing pages for specific service-and-audience combinations, then writing content tailored to that exact combination rather than a generic feature page.
Wave, an accounting software company, applies this pattern across its site. The page below targets free accounting software for nonprofits, with content written for that audience and keywords appearing naturally throughout.
It features helpful content tailored specifically to this audience, with keywords appearing naturally throughout.
In August 2026, the page ranked in the top three results for 28 keywords — the majority of which were long-tail. Those rankings drove 783 monthly visits, with a traffic cost of $5.2K, according to Semrush’s Organic Rankings tool.
Wave also appeared prominently when we researched topics related to those keywords in AI tools like ChatGPT.
Local long-tail keyword example
Pages that group several related, low-competition questions under one topic can rank for many long-tail variations at once — particularly when the answers are closely related and relatively brief.
Choose Chicago applies this pattern by answering multiple FAQs about a single attraction on one page, letting each guide target a range of short-, mid-, and long-tail keywords with local intent.
Because the individual answers are relatively brief and topically connected, consolidating them serves searchers better than splitting each question into its own thin page — someone asking one of these questions is likely curious about the others too.
Here’s a snapshot of one of these guides:
In August 2026, this guide ranked in the top three results for 516 keywords, according to Organic Rankings data.
Ecommerce long-tail keyword example
Filtered navigation on ecommerce sites can generate unique, indexable pages that capture long-tail search intent automatically — as long as each filter combination gets its own optimized URL, title tag, and meta description rather than relying on a single generic category page.
Wayfair applies this pattern across its product filters. Many of the site’s filter pages rank for long-tail keywords because select filter combinations produce pages that map directly to specific searches, like this one for blue velvet living room sets:
And we can see that Wayfair earns mentions and citations for 81 prompts related to “blue velvet.”
To replicate this on your own site, make sure filter pages have crawlable, indexable URLs, unique titles and meta descriptions per combination, and enough unique on-page content — not just a product grid — to avoid looking like thin, duplicate pages to search engines.
How to track long-tail keyword rankings
Track long-tail keyword rankings in Google Search Console or with a dedicated rank tracking tool like Semrush Position Tracking.
Google Search Console shows the following metrics for up to 1,000 queries chosen by Google, according to your selected time range:
- Clicks: How many times users clicked your result
- Impressions: How many times users viewed your result
- Click-through rate (CTR): Represents clicks as a percentage of impressions
- Position: Your average highest ranking in organic results
Alternatively, use the Position Tracking tool to monitor the long-tail keywords of your choice.
The tool can show you the following information for each keyword in Google Search:
- Actual position vs. potential position
- Competitor rankings
- Whether you rank for any SERP features (e.g., PAA)
- Keyword search volumes, difficulty scores, etc.
- Estimated traffic vs. potential traffic
Position Tracking also reports your visibility in ChatGPT and Google AI Mode alongside organic rankings, so you can monitor both from the same dashboard.
