lpark

M Posted 1 year 5 months ago

t 9 min read

Longtail keywords are becoming critical as search becomes more conversational with the advent of AI chat. Learn what longtail keywords are and how to win them here

Why are Long Tail Keywords Important?

A long tail keyword is a phrase that is generally made from three to five words. Since these keywords are more specific than generic terms, they allow you to target niche demographics. These keywords are also less competitive than generic keywords because they are designed to better reflect how people make queries. With long tail keywords, you are able to attract more high-quality traffic to your website which is more likely to lead to conversions.

During the customer journey, long tail keywords become more important as their journey evolves. Typically, users begin with a simple search and as the search engines guide them to solving their pain point, their searches become more detailed. This is where long tail keywords will become important to separate your brand from your competition. 

BrightEdge Generative Parser reveals that as of January 2025, 35% of AI Overview results now handle multiple search intents simultaneously, with projections showing this could reach 65% by Q1 2025. This means users increasingly combine multiple aspects of their journey into single, detailed searches - making long tail keywords that address specific combinations of needs more valuable than ever.

Are long tail keywords important for SEO?

Over 70% of search queries are made using long tail keywords. This has become particularly prevalent with people using voice search more often. People now generally enter queries into Google using the same types of phrasing as they do when they are speaking with a friend. This is called natural language. Using long tail keywords, therefore, makes your content more likely to draw these users into your website and begin the process of the buyer’s journey. In addition, generative AI such as that found in Google’s AI Overviews are expanding the ways long tail keywords can be used to pinpoint conversational search patterns. As AI enables users to combine multiple intents, the way they use long tail keywords becomes vital in earning citations from these engines. You can learn more about Google SGE in our Ultimate Guide to AI Overviews!

Long tail keywords being comprised of a few words makes them much more specific. This means that both users and site owners generally receive better results. Brands receive traffic that is more closely aligned with their content, which will improve their ability to effectively bring new customers into the sales cycle. Customers also receive content that is more closely aligned with their objective, making them happier.

The specificity of long tail keywords also means that there is less competition for each keyword phrase. Brands can better customize their specific keywords for what they provide users.

Long Tail Keywords: Strategic Importance in AI Search

The rise of AI-powered search has fundamentally shifted how users interact with search engines, making long tail keywords more valuable than ever for SEO practitioners. According to BrightEdge Generative Parser data, search queries that trigger AI Overviews have become increasingly conversational, growing from an average of 3.1 words in June 2024 to 4.2 words by year's end. This shift reflects a growing user comfort with more natural, detailed search patterns that align perfectly with long tail keyword strategies.

For SEO practitioners, this evolution presents a unique opportunity. Rather than competing directly with major brands for broad keywords, long tail optimization allows websites to earn citations in AI search results by providing complementary, specific information. BrightEdge Generative Parser data shows that AI Overviews are now pulling from a significantly broader range of sources - up to 151% more unique websites for complex B2B queries and 108% more for detailed product searches. This means that websites optimizing for specific, detailed long tail phrases have an increased chance of being cited in comprehensive AI-generated responses.

This democratization of citations in AI search results means that digital marketers and SEO’s can focus on developing deep, specific content that answers particular aspects of user queries, rather than trying to compete for broad, highly competitive terms. By targeting the natural language patterns that users increasingly employ in their searches, websites can position themselves as valuable sources of specific information that AI systems will reference when building comprehensive responses to user queries.

Long tail keyword example

Depending on the topics your site creates content around and how many pages you have, you will want to collect a pretty large relevant list of long tail keywords that you can use throughout your site. It's not realistic, or SEO-healthy, for you to optimize your site for the same keywords on every page, therefore you'll need a running list of great keywords.

If you're a local brand looking for local foot traffic, adding "near me" to your long tail keywords is a good practice. For example, long tail keywords including "organic coffee shops near me" or "buy Guiana chestnut plant near me" are both good examples of when a user is at the final stages of their buyer journey searching via long tail queries. Using specific keywords like "organic coffee shop" and "Guiana chestnut plant" will help you to rank better as they're further from common keywords bigger brands are trying to rank for.

Researching long tail keywords

1. Build your buyer personas and map them to customer journeys.
2. Use this information to help you identify topics that your personas will want to see at each stage of their journey.
3. Leverage your own query research via search engines by typing a simple search into the search bar and see what keywords autofill into long tail keywords. These keywords are what users are searching for and you should optimize for them. You can see to the right that we typed "best seo" into Google. Long tail keywords autofilled to show us what users are most often looking for when it comes to "best seo."
4. Use keyword technology, like the BrightEdge Data Cube X, to identify the relevant keywords that you can best rank for that also have high traffic rates.
5. Monitor your success with your keywords, looking closely at your traffic and engagement rates. This will tell you how many people you are attracting and how well your content is answering the need of their query.

Long-tail keywords are valuable tools for those looking to optimize their content and attract more relevant visitors. The better you are able to better understand your users, the better you will be able to meet their needs and bring in new customers for your organization.

lpark

M Posted 1 year 5 months ago

t 9 min read

We're barely into 2025, and the transformation of search through AI is already reshaping how users discover and consume content. At BrightEdge, we're closely monitoring these developments to help marketers not just adapt, but thrive in this dynamic landscape. As AI-driven experiences become integrated into search engines like Google and Bing, and AI-first search engines like ChatGPT Search and DeepSeek gain momentum, the question on every marketer's mind is clear: How do we optimize for AI search without abandoning everything we know about SEO?

The good news? You don't need to rewrite the entire playbook. AI search still aims to deliver the best possible answer to a user's query—just as traditional search engines do. However, there are new dimensions to ranking, indexing, and retrieval that require strategic adaptation. Our analysis reveals four critical areas you need to focus on to ensure your content remains visible and influential in AI-generated responses.

The Shifting Search Landscape

Before diving into strategies, let's examine what's changing:

• AI search engines are experiencing significant adoption: ChatGPT is gaining traction rapidly, representingapproximately a $4 billion shift in the search market, even as Google maintains dominant overall market share.

• AI Overviews are consuming more SERP real estate: The average AI Overview result has expanded to 1,000 pixels tall—a 50% increase since August 2024—pushing traditional organic results further down the page.

• New AI-first search engines like DeepSeek are emerging: These platforms prioritize contextually rich answers with transparency and efficiency, signaling a shift toward more sophisticated AI-driven retrieval models.

With these changes in mind, here are the four essential strategies to ensure your content is indexed, cited, and surfaced effectively in AI search environments.

1. Focus on the Follow-Up: Structure Content for Multi-Step Search Journeys

Traditional SEO optimizes for single queries—someone searches, finds an answer, and clicks through. AI search works differently. It anticipates the next question a user might ask, often chaining multiple queries together to provide context-rich, multi-step answers.

Strategic Implications for Marketers

Rather than just answering one question, structuring your content to support deeper exploration and contextual relationships between topics may increase your visibility in AI-generated responses. Consider these approaches:

• Thinking beyond single queries: AI connects related topics, so your content should naturally guide users to their next question through internal links and logical content progression.

• Providing layered, contextual information: Content that explores a topic holistically may increase your chances of being cited in AI responses, as it potentially addresses multiple related queries in one resource.

• Using natural language and question-based formatting: As AI is anticipating questions people would have, building content around these questions, incorporating elements from things like the “People Also Ask” results in Google, can ensure your content is covering bases that AI may try to address. 

For BrightEdge users, Copilot for Content Advisor helps identify the most common questions around a topic that AI may anticipate, and even generates configurable first drafts. Focusing on these related questions is critical to ensure your content is as citable as possible.

2. Give AI Hints About Your Content: Leverage Schema Markup

AI models process content differently than humans do—they analyze structured signals. While there's no direct evidence that AI search engines use schema to render results, implementing structured data may help crawlers better understand the context and classification of your content, potentially increasing your citation chances.

Best Practices for Schema Implementation

Schema markup provides AI crawlers with hints about what your content is about, answering key contextual questions like:

• Who is the author?

• What format is this content? (list, FAQ, how-to, article, etc.)

• What unique details does this content provide? (product dimensions, pricing, statistics, etc.)

For marketers this means you need to ensure you are: 

• Using structured data liberally: Implement FAQPage, HowTo, and Article schema to clearly define your content's purpose.

• Focusing on Schema that matters: Google’s John Mueller actually warns against over-use of Schema Tags, particularly on product pages, so ensuring you are only using those that will truly help crawlers understand your content without potentially confusing them is critical. 

• Understanding schema's role: Remember, schema isn't a ranking factor—but it helps AI understand your content.

One common challenge with Schema is knowing which tags to prioritize among the 300+ options on Schema.org. BrightEdge's SearchIQ makes this easier by analyzing and summarizing the most common Schema tags deployed among top-ranking pages in your market, providing clear guidance on where to focus and revealing gaps between your pages and competitors.

3. Ensure AI Crawlers Can Access Your Website

Just as with traditional search, if AI models can't crawl your site, they can't cite your content. Many companies unknowingly block AI-driven crawlers in their robots.txt files, limiting their ability to be referenced in AI search results.

How to Optimize for AI Crawlers

Check if your site is accidentally blocking key AI crawlers, including:

• Google-Extended (Google's AI-related crawler used with Gemini etc.)

• GPTBot (OpenAI's dedicated crawler for LLM training)

• PerplexityBot (Used by Perplexity AI's search engine)

• ClaudeBot (Anthropic's AI crawler)

To ensure visibility:

• Review your robots.txt file and ensure AI-related bots are not being restricted.

• Use Bing Webmaster Tools to verify that Bing is indexing your content—there is strong evidence that ChatGPT's SearchGPT uses Bing's index.

BrightEdge users can integrate Bing Webmaster Tools directly into the platform, making it easier to monitor performance in Bing. Significant impression drops could signal that something may be blocked.

4. Make Your Site as Accessible as Possible

AI-powered search engines still rely on fundamental crawling principles, but they factor in a wider range of queries, meaning even deep, under-optimized pages may be valuable for citation.

Why Accessibility Matters More Than Ever

• AI anticipates incremental user queries, meaning that even deeply nested pages on your site may be valuable as a follow-up answer in an AI-generated response.

• If AI crawlers can't reach these pages, they won't be considered for citation.

• JavaScript-heavy pages may be harder for AI crawlers to process, so ensuring pre-rendering or static HTML versions exist can prevent AI search engines from missing critical content.

How to Improve AI Search Accessibility

• Ensure deep pages are fully crawlable—your AI SEO success isn'tjust about homepage and top pages.

• Use internal linking to surface valuable content—help AI connect related content by making deeper pages easier to find.

• Check JavaScript dependencies—some AI crawlers may struggle with dynamic rendering, so test your site's accessibility by disabling JavaScript in your browser.

BrightEdge users leverage Content IQ to maintain quality governance by running regular crawls that can identify blocked pages, bad redirects, or other technical issues that may prevent emerging crawlers from indexing new pages.

Looking Ahead: Evolution, Not Revolution

The evolution of search presents unprecedented opportunities for marketers to connect with their audiences. While AI-driven search is evolving rapidly, the fundamentals of good SEO still apply—with some critical adjustments.

AI search isn't replacing SEO—it's redefining it. Brands that embrace AI-first SEO strategies today will be in the best position to win in the next era of search. At BrightEdge, we'll continue tracking these developments closely to help you navigate and succeed in this dynamic landscape.

In addition to above, capabilities like BrightEdge's Data Cube X help identify specific opportunities within your industry and ensure your content aligns with user search patterns and AI preferences. 

While SEO for AI isn’t an entirely new practice, it does require us to put a focus on some fundamental elements we may not always focus on with traditional SEO. BrightEdge is here as your partner to ensure you are ready to win in this exciting new era of search!