The AI search landscape is evolving at breakneck speed, and our latest data from BrightEdge's Generative Parser™ and AI Catalyst reveals patterns that every SEO and marketing professional needs to understand as Generative Engine Optimization becomes the norm. As users shift from traditional searches to AI-powered experiences, we're witnessing fundamental changes in how information is discovered and presented.

Here at BrightEdge, we’ve continued to analyze tens of thousands of queries and prompts across ChatGPT and Google's AI Overviews. There are four critical themes that are reshaping digital marketing strategies right now.

1. The 76% Convergence: Same Brands, Different Stories

One of our most striking observations is the overlap between ChatGPT and AI Overviews when it comes to brand recommendations. Our AI Catalyst analysis of shopping prompts revealed that these platforms recommend the same brands 76% of the time—but how they present these brands couldn't be more different.

A Tale of Two AI Approaches

While both platforms lead with selection and variety (51-54% of mentions), their storytelling diverges dramatically:

• ChatGPT: The Comprehensive Catalog
  • Emphasizes selection/variety in 54% of responses
  • Mentions deals/pricing in 50% of recommendations
  • Uses functional language ("offers," "provides") three times more frequently
  • Adopts a "this platform offers..." mindset
• AI Overviews: The Selective Curator
  • Emphasizes selection/variety in 51% of responses
  • Mentions deals/pricing in only 41% of recommendations
  • Focuses on competitive positioning
  • Takes a "better than competitors..." approach

Real-World Example: Textbook Shopping (As seen in AI Catalyst)

Notice how both platforms recommend similar textbook sites like Chegg, CampusBooks, and VitalSource, but ChatGPT highlights their services ("significant discounts and additional services like homework help") while AI Overviews emphasizes market position ("vast marketplace offering competitive prices").

The Language Divide

One of the things BrightEdge AI Catalyst allows users to do is analyze the way each of the AI Search engine talks about brands. This is significant because this isn’t language from a page snippet or a meta description. This is how the generative AI is describing your brand. What’s particularly interesting is that ChatGPT is far more likely to use words like “offers”, “provides” or “enables” implying they are describing what products or shopping locations can do for the user. This 3x difference in functional language usage reveals fundamental differences in how these platforms conceptualize brand recommendations.

Strategic Opportunity

This convergence proves you don't need separate websites or radically different content strategies for each platform. The winning approach? Create comprehensive content that showcases your selection while explaining your unique value. Quality content that covers the right bases wins everywhere.

2. The Volume Divide: ChatGPT's Marketplace vs. Google's Curation

Perhaps nothing illustrates the fundamental difference between these platforms better than how they handle brand recommendations in shopping queries. When we compare shopping queries, even though there is a rank overlap with 76% of the brands mentioned, ChatGPT is likely to recommend more brands. In fact we see that 43% of the time they recommend brands, there’s more than 10. AI Overviews? Only 4.7% of the time.

The Numbers Tell the Story

• ChatGPT operates like a digital marketplace:
  • Includes 10+ brands in 43.9% of responses
  • Maintains consistent brand inclusion across all query types
• AI Overviews function as selective curators:
  • Include 10+ brands in just 4.7% of responses
  • Show dramatic variation based on query intent

Query Intent Drives Visibility

Percentage of Prompt Types where Brands are Recommended

The data reveals fascinating patterns in how user prompts influence brand visibility:

• "Where to buy" prompts: AI Overviews include brand recommendations 39.3% of the time
• "Deals/coupons" prompts: AI Overviews include brand recommendations only 12.2% of the time
• Adding "buy online" to any query: Increases the likelihood of AI Overviews including brands by 33.9 percentage points

This suggests that Google may be relying on other SERP features (shopping carousels, product grids, sponsored listings) for commercial queries, while ChatGPT creates comprehensive brand marketplaces within its responses.

3. Device Divergence: Mobile and Desktop Serve Different Masters

Our analysis reveals that mobile and desktop AI Overviews aren't just different sizes—they're fundamentally different products targeting distinct user behaviors. This is very evident when queries could trigger things like shopping carousels.

The Mobile Experience

Mobile AIO’s reveal a fascinating paradox: while mobile AI Overviews take up less screen space, they're actually doing more heavy lifting for e-commerce queries. In fact, throughout the past month, we observed a 3x higher appearance rate for shopping queries on mobile.

What's really happening here is that mobile AI Overviews are filling a different role in the purchase funnel. While desktop might skip AIOs for transactional queries (letting shopping grids handle it), mobile uses AIOs as an educational bridge—helping users understand product categories, compare options, and make informed decisions before they tap through to buy. It's less about immediate transactions and more about guiding discovery, which explains why mobile e-commerce AIOs appear so much more frequently despite having less screen real estate to work with.

The Desktop Experience

Desktop AI Overviews are essentially playing a different game than mobile. The 80% larger screen real estate isn't just about size—it's about Google having the space to deliver comprehensive, authoritative answers that can truly compete with traditional search results.

The consistency factor is particularly telling: desktop AIOs appear more predictably because desktop users have different expectations and behaviors. They're typically in research mode, sitting down for longer sessions, ready to digest detailed information. Meanwhile, mobile's variability suggests Google is still experimenting with how much information to show users who are on-the-go.

The 39% higher keyword coverage on desktop reinforces our thesis about device divergence—Google is essentially building two different products. Desktop gets the full treatment because users expect depth, while mobile remains selective, knowing that users need quick answers and that other SERP features (like shopping carousels) can handle transactional needs. This isn't just a responsive design choice; it's a fundamental difference in how Google conceptualizes the role of AI Overviews across devices

Strategic Implications for Marketers

This divergence clearly indicates that Google is treating these as separate products:

• 80% more screen space on desktop means more detailed explanations and citation opportunities
• Create mobile-first educational content and product guides, not just product pages
• Content strategy may need to be different for mobile and desktop Generative Engine Optimization

Strategic Imperatives for the AI-First Era

These insights point to clear actions for marketers navigating the AI search landscape:

1. Unified Content Strategy

With 76% brand overlap, create content that performs across platforms while acknowledging their different presentation styles. Focus on

• Leading with selection/variety or top use cases
• Including functional benefits as part of your optimization strategy
• Using competitive advantages and core differentiators
• Tracking brand sentiment across prompt types

2. Understand the Query Landscape

The surge in long-form queries shows users type conversationally. Your content needs to:

• Optimize for geographic and contextual variations
• Answer specific situational combinations, not generic info
• Mirror natural language patterns over keywords

3. Device-Specific Optimization

Recognize that mobile users are in discovery mode while desktop users seek comprehensive information:

• E-commerce brands especially need mobile-first AIO strategies
• Desktop content should be more detailed with citation opportunities
• Consider different content approaches for each platform

4. Depth Over Breadth

With AI Overviews becoming more selective but detailed:

• Create authoritative content that addresses complete user contexts
• Focus on comprehensive answers that showcase expertise
• Ensure your website clearly displays purchasing options
• Provide buying guides that convey your brand's distinct identity

5. Track Cross-Platform Performance

Monitor how both ChatGPT and AI Overviews describe your brand:

• Track mention patterns across all AI platforms
• Monitor referral traffic from different AI sources
• Use tools like BrightEdge's AI Catalyst for comprehensive visibility

The Bottom Line

The data is clear: AI search isn't just an evolution of traditional search—it's a revolution in how users interact with information online. With ChatGPT creating digital marketplaces and Google's AI Overviews acting as selective curators, with users asking increasingly complex questions, and with mobile and desktop experiences diverging dramatically, the landscape demands new strategies.

The winners in this new landscape will be those who understand these patterns and adapt their strategies accordingly. The good news? You can optimize once and rank everywhere—but only if you understand how each platform tells your story differently.

With technologies like BrightEdge's AI Catalyst and Data Cube X providing visibility into these changes, marketers can stay ahead of the curve and ensure their content thrives in the AI era. The key is understanding that while the brands may be the same, the stories these AI platforms tell—and the users they serve—are fundamentally different.

Search is evolving faster than ever—and that’s opening up a big new opportunity for PR teams.

Thanks to AI-powered search engines like Google’s AI Overviews, ChatGPT, and Perplexity, more people are getting direct answers without ever clicking a link. These AI systems aren’t just listing websites—they’re making recommendations. And when your brand is mentioned in those answers, it’s a powerful signal to the user: this is someone to trust.

That’s where PR comes in.

This shift doesn’t mean PR has to become something completely different. In fact, AI search rewards exactly what PR already does well—building credibility, earning trust, and shaping the brand’s story in places that matter. What’s changed is that now, those efforts can directly influence how (and whether) your brand shows up in the new discovery layer of search.

Here’s how PR teams can take advantage of this moment—by focusing on the sources AI trusts, understanding how citations work, and using new data to guide their strategy.

AI Answers Are Becoming a Brand’s First Impression

When AI Overviews show up in Google search results, they take up serious screen space. BrightEdge research shows that when an AI Overview appears, the click-through rate on the top organic listing drops from 25.8% to just 7.4%.

That’s not bad news—it’s a wake-up call. It means users are getting what they need from the AI answer itself. And if your brand is recommended in that answer, that’s where discovery begins.

This changes the role of PR in a good way. Instead of hoping a media placement gets picked up and shared, you now have a direct path to helping your brand get cited where people are actively looking for trusted answers.

Drop of in CTR when an AI Overview is present - Being part of the AI recommendation matters more than ever:

Why PR Is in a Great Spot to Win Here

Search engines powered by AI don’t just pull from top-ranking content—they pull from sources they view as credible, clear, and relevant to the query.

We used BrightEdge Generative Parser™ to compare sources across multiple AI Engines and found important patterns:

• Google AI Overviews tend to cite content that’s concise, updated, and comes from trusted domains.
• Perplexity leans into content that’s rich in facts, citations, and comparisons.
• ChatGPT with browsing pulls from Bing’s index and often favors content that’s fresh and consistently authoritative.

None of that should sound intimidating to PR experts. If anything, it’s encouraging. Because what AI is really looking for is well-communicated credibility. And PR is already great at that.

What’s different now is that you can see which mentions are showing up in AI search, and take action based on that. PR doesn’t need to guess which placements matter most anymore. With platforms like BrightEdge AI Catalyst, you can actually track which domains get cited in AI answers—and use that data to guide your outreach.

What to Focus on If You’re in PR

Here are four areas where PR teams can have an immediate impact in the AI search landscape.

1. Know Which Sources AI Engines Trust

The first step is figuring out which websites and publishers AI engines are pulling from in your space.

BrightEdge’s AI Catalyst makes this easy. It tracks the domains cited in Google AI Overviews, ChatGPT, and other AI engines for the topics and prompts that matter to your brand. That means you can:

• See which media outlets, expert blogs, and publishers consistently get cited and for what articles.
• Prioritize those for outreach and earned media
• Align with SEO and content teams on where to build visibility

You don’t need to overhaul your PR strategy—you just need to aim your efforts where they’ll make the biggest difference.

2. Pitch to the Lists, Roundups, and Reviews AI Loves

When someone asks Google “what’s the best software for nonprofits?” they’re not just looking for a brand—they’re looking for a list they can trust.

AI engines love structured content. Many responses from AI draw on sources like this. If your brand is mentioned in one of those pieces—and that piece is on a site the AI trusts—you’ve just earned a shot at being in the answer.

This is a natural fit for PR. Pitching for inclusion in these types of articles, or collaborating with journalists who write comparison pieces, is already part of the job. Now, it comes with an added upside: you’re influencing how AI introduces your brand to potential customers.

3. Highlight What Makes Your Brand Worth Mentioning

The more clearly your brand is positioned, the more likely it is to be picked up by AI engines.

When PR teams pitch stories, submit product info, or provide quotes, highlighting these kinds of attributes gives AI more to work with. Over time, this messaging builds up across the web—and increases your chances of being pulled into AI-generated summaries.

4. Track AI Mentions Like You Track Media Coverage

If you’re already tracking media pickups and share of voice, it’s time to add a new layer: share of AI voice.

Using BrightEdge AI Catalyst, PR teams can:

• See where and when your brand is mentioned in AI answers
• Monitor sentiment and positioning in those mentions
• Compare visibility against competitors
• Spot new opportunities for outreach

You don’t have to guess whether a placement had downstream impact. You can now see if it helped you earn a spot in AI recommendations—and if it didn’t, you have the data to see what did.

PR’s Role Is Expanding—in the Best Way

This new AI-powered landscape isn’t pushing PR to become something it’s not. It’s giving PR a bigger stage and better data.

You still pitch stories, build relationships, and shape narratives. Now, you also get to see how that work shows up in the new front door of brand discovery: the AI answer.

Best of all, this doesn’t mean overhauling your day-to-day. It means:

• Aiming your outreach where it counts most
• Understanding what makes a brand recommendable in AI
• Using data to prove your impact

In a time when users are asking AI what to buy, who to trust, and how to solve problems—being cited in those answers is the new PR win.

Final Thought: This Is a Big Opportunity for PR to Lead

AI is quickly becoming the first stop in a user’s journey. That means PR is no longer just supporting awareness. It’s influencing the recommendation engine at the heart of modern search.

With capabilities like BrightEdge AI Catalyst, PR teams can take control of this new channel—tracking what’s working, spotting what’s missing, and steering the conversation in the right direction.

And the best part? This is already in your wheelhouse.

You’ve been shaping brand perception all along. Now you get to do it in the one place where trust matters most: the answer people see first.

Structured data is a way to label and organize the information on your webpages so machines (and AI) can understand it. Google defines it as “a standardized format for providing information about a page and classifying the page content”developers.google.com. In practice, structured data uses vocabularies like Schema.org and formats like JSON-LD to annotate key elements of your content. For example, on a recipe page you might mark up ingredients and cook time; on a blog you might mark up the author and publish date. Common schema types include FAQPage (for question-and-answer content), HowTo (step-by-step guides), Product (with nested Offer and Review data for e-commerce), Review (for ratings), Article/NewsArticle, and Organization (company info). Implementing these schemas makes your page’s purpose explicit to crawlers. While structured data itself isn’t a direct ranking factor, it helps search engines—and the AI systems built on them—understand and surface your content better.  Schema.org provides a repository of accepted schemas, with common types including:

• FAQPage – marks up lists of questions and answers.
• HowTo – annotates instructional steps or tutorials.
• Product (+ Offer, Review) – highlights product details (name, price, availability, ratings) for shopping results.
• Review – marks up ratings and reviews of products or services.
• Organization – provides business or brand details (name, logo, contact).
• Article/NewsArticle – labels blog posts or news content (headline, author, date).
• Event – (extra) for events with dates and locations.
• LocalBusiness – (extra) for physical businesses with address and hours.

Using JSON-LD (Google’s preferred format) and including schema in your HTML tells search crawlers exactly what each piece of content means. Properly implemented schema can generate rich results (like stars, carousels, or FAQ drop-downs) and even Knowledge Panels that improve visibility. In short, structured data is how you explicitly signal page content to search engines, laying the groundwork for both traditional rich results and AI-driven answers.

How Structured Data Enhances AI Visibility

As AI features (like Google’s AI Overviews, ChatGPT, or engines such as Claude) emerge, structured data could have the potential to play a key role in helping those systems find and use your content. Google’s documentation notes that AI Overviews pull information from “a range of sources, including information from across the web. In practice, this means if your content is indexed and understandable, it can be surfaced in generative answers. Google advises no special markup is needed – just follow normal SEO guidelines– but schema gives extra clarity. It feeds the knowledge-graph and context layers that AI relies on.

In sum, while an AI search engine won’t “parse” your JSON-LD to form its answer word-for-word, schema makes your content more digestible to search crawlers and knowledge graphs. That, in turn, has potential to increase the chance your information will be included or cited by AI overviews and answer engines.

Best Practices for Implementing Structured Data

For implementing structured data as part of your AI search strategy, consider the following:

• Use JSON-LD: Google recommends JSON-LD placed in a <script> tag. It’s flexible and separate from your HTML, making it easier to manage.
• Choose Relevant Schema: Only apply schemas that match the page content. For example, use FAQPage on actual FAQ pages or HowTo on step-by-step guides. Avoid marketing up irrelevant content.
• Validate Your Markup: BrightEdge’s SearchIQ can help ensure your schema is detectable and competitive with websites that rank for similar keywords.
• Focus on Evergreen Types: Key types like Article, Product/Offer/Review, FAQPage, HowTo, and Organization are widely used and recommended for content visibility.
• Don’t Overdo It: Use schema “liberally” where it adds clarity, but avoid excess. Google’s John Mueller even cautions against schema bloat on things like product pages.  Only markup what truly helps explain the content.
• Leverage SEO Tools: Tools can reveal where to focus. For instance, BrightEdge’s SearchIQ analyzes the top-ranked pages in your space and highlights which schema types they use. This helps you prioritize the most impactful markups. Similarly, BrightEdge’s Data Cube X can surface emerging queries or AI-related trends. Use it to find content gaps and new opportunities to apply relevant schema (e.g. rising how-to topics or FAQs).
• Monitor and Audit: Regularly crawl your site (using technologies like ContentIQ) to ensure your structured data remains intact and error-free after any updates. Update schemas when content changes (e.g., new product attributes, post authorship, etc.).

By following these practices, you ensure that your content is both technically sound for search crawlers and semantically clear for AI engines. In the AI era, well-structured markup is a signal that helps your pages stand out in new search experiences.

The Impact of Structured Data on SEO

Structured data has long boosted traditional SEO, and that impact continues. The most obvious effect is enhanced listings in search results. Pages with proper schema can appear with rich snippets: review stars, pricing info, FAQ expanders, breadcrumbs, and more.

Moreover, schema is critical for voice, image, and other modern search channels. Voice assistants and visual search tools rely on structured cues. For example, marking up FAQ content can enable answers read aloud by smart speakers.

Even beyond clicks, structured data bolsters site authority in Google’s knowledge graph. Content marked up as an Organization, Person, or Entity can feed Google’s backend understanding of your brand. Consistent schema use (across your website and external data sources) strengthens how the web knows your entities. In turn, that can influence AI-driven panels and answers.

Structured Data and AI Technologies

Different AI-powered search tools interact with structured data in different ways:

• AI Overviews: Google’s AI snapshots pull in content from indexed pages and Google’s Knowledge Graph. The official guidance is that links in overviews are chosen automatically. However, schema still helps. Pages marked up clearly are easier for Google to parse into its knowledge graph, making them more likely to be cited as sources. In practice, FAQ and HowTo markup have become popular for AI because they directly answer questions.
• ChatGPT Search / SearchGPT (OpenAI): This AI search often uses Bing’s index as its source. That means your Bing-indexed pages (with schema) are potential sources. One report notes you should ensure Bing is crawling your site – ChatGPT Search will cite even lower-ranked pages if they’re well-structured. Structured data here serves the same purpose as in traditional SEO: making your content authoritative and easy to digest.
• Perplexity AI: Perplexity is a generative Q&A engine that cites web sources in its answers. While it hasn’t released official SEO guidelines, it clearly relies on quality web content. Schema can help Perplexity’s algorithms quickly identify answers: e.g., a Product schema immediately flags where the price and review are. The general advice is the same – great content + clear structure means better chances of being cited by Perplexity or similar tools.
• Anthropic Claude: In early 2025, Claude introduced web search. That means Claude (when web-enabled) will pull real-time info from indexed sites. Again, the fundamentals apply: structured, high-quality content is more likely to be used. Claude even provides direct citations in its responses once it finds your content.

In all cases, the common thread is that AI tools are consuming the content you publish, and they prefer content that is clear, authoritative, and well-annotated. SEO best practices – such as high domain authority, expert-written content, and strong internal/external links – still matter tremendously for AI visibility. Structured data is one more piece of that puzzle.

Looking Ahead: The Future of Structured Data in AI

The trend is clear: structured data adoption is growing as AI search matures. We expect structured data markup to expand its vocabulary further to accommodate AI needs.

Crucially, structured data is becoming part of the semantic layer that underpins AI. As generative models demand verifiable facts, clear schema provides the grounding they need. SEO leaders have noted that investing in structured data today is “not just about SEO anymore – it’s about building the semantic layer that enables AI. “In other words, schema turns your site into a machine-readable knowledge graph, and future AI tools will rely on that graph to answer questions accurately.

For digital marketers, this means structured data will remain a priority. Watch for new schema types (e.g., QAPage, Speakable, or sector-specific schemas) and ensure content is marked up accordingly. At the same time, keep core SEO strong: rich content, good UX, and technical hygiene (like open crawl paths for AI bots).

Schema and structured data remain an adjacent factor in driving visibility in both AI and traditional rankings.  For marketers who need to reach customers in both of these facets, it’s critical that structured data is part of your approach to SEO. 

Understanding Content Quality Signals for AI Algorithms

In today’s AI-driven search landscape, content quality matters more than ever. Search engines use sophisticated AI algorithms (like Google’s BERT and MUM) to assess whether page content truly serves users’ needs. High-quality, original content written for people continues to rank best. As Google’s guidance suggests, “using AI doesn’t give content any special gains. It’s just content. If it is useful, helpful, original, and satisfies aspects of E-E-A-T, it might do well in Search.” In other words, no matter how it’s created (even if AI-assisted), content must demonstrate real value and authenticity.

In practice, content quality signals are the factors search algorithms use to judge a page’s value. These include the depth and relevance of information, originality of insights, author expertise, and user engagement metrics. In the AI era, search systems have been updated to reward “original, helpful content written by people, for people” and to demote content made “primarily to gain search engine traffic”. For SEO professionals, understanding these signals means focusing on content that users find genuinely useful, rather than those designed primarily for an algorithm.

The Importance of Content Quality in the Age of AI

With so much AI-generated content flooding the web, search engines have doubled down on quality. Google explicitly warns against “mass-produced” or spammy content, whether human- or AI-generated, and emphasizes user-first content. In recent updates (e.g. March 2024 Core Update), Google has targeted sites with large amounts of generic AI content. Ensuring content that is AI generated remains useful or users was a core function of Google’s Helpful Content update which has been enhanced and updated since 2022.

Defining Content Quality Signals

Content quality signals encompass everything from topical depth to technical presentation. At a high level, they include relevance to user intent; completeness and accuracy; clarity and organization; authoritativeness (E-E-A-T); and positive user engagement. For example, Google’s Quality Rater Guidelines focus on E-E-A-T (Experience, Expertise, Authoritativeness, Trust) when assessing quality. Even though these guidelines are for human raters, they reflect the types of signals algorithms value. Other signals include fresh content for timely topics, original research, and rich media or data that demonstrate depth. Additionally, page-level user experience (fast loading, mobile-friendliness, easy navigation) affects experience and thus indirectly signals quality.

The Role of User Experience in Content Assessment

User experience (UX) is a key part of content quality. Google’s page experience signals (Core Web Vitals, mobile usability) ensure that even great content isn’t buried behind a poor experience. According to Google, “our core ranking systems look to reward content that provides a good page experience”. This means slow or hard-to-navigate pages can undermine even excellent content. Moreover, search engines look at how users interact with content: do they stay and scroll, or bounce back to search results?

Impact of High-Quality Content on Search Rankings

High-quality content continues to be rewarded in the AI search era. Google’s Helpful Content (2022 onward) explicitly boosts original, people-first content in rankings. Content that genuinely addresses user queries is favored; generic or duplicated content is downgraded. As Google notes, whether content is AI-generated or not, it must be “useful, helpful, original” and meet E-E-A-T standards to perform well. In 2024, Google’s March Core Update impacted many sites with thin or low-quality content, especially sites relying heavily on AI-generated text. This underscores that content quality signals – originality, expertise, trust – have a direct impact on visibility. For SEO and digital marketers, the lesson is clear: prioritize substance over volume.

How AI Algorithms Evaluate Content Quality

Modern search algorithms rely on sophisticated AI and machine learning to parse and rank content. These AI models analyze key factors such as relevance, depth, novelty, and credibility. For instance, Google’s neural matching systems (like BERT) understand the context of words and concepts in both queries and pages. This means content is evaluated on semantic meaning, not just keyword presence. The Multitask Unified Model (MUM) and other AI can even “read” multiple languages and formats to judge the completeness of an answer. In essence, AI algorithms assess whether a page thoroughly and accurately addresses a topic.

• Key factors AI algorithms consider: AI ranking systems evaluate multiple signals including topical relevance (how well content matches user intent), originality of insights, topic comprehensiveness, and information freshness. They also assess expertise through credible sources, author credentials, and citation patterns. Content structure elements like headings help AI understand meaning and context. Advanced models like BERT and MUM weigh these factors to prioritize content that's clear, well-organized, and helpful to users.
• Human vs. AI content evaluation: Human quality raters and AI algorithms work as complementary systems. Quality raters use Google's E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness) to evaluate content usefulness, with trust being the most critical component. These human evaluations help Google assess its search ranking systems but don't directly influence rankings. Human raters provide nuanced judgment to guide algorithm development, while the AI systems ultimately rank pages based on measurable, data-driven signals.
• Significance of context: Modern search engines understand context, not just keywords. Google's Neural Matching system connects the concepts behind your words to relevant content, even when exact terms don't match. This means your content should focus on thoroughly covering topics and addressing user intent rather than keyword stuffing. Include related subtopics, use structured data, and think about what questions your audience is really asking—not just what words they're typing.

Quality Signals: What AI Algorithms Look For

Search AI models seek specific quality signals in content. The most important include:

• Originality: Search engines reward unique content that adds new information or perspectives. Create original research, case studies, or expert analysis rather than rehashing what's already out there. Google can tell the difference between fresh insights and copied content.
• Authority: Show you know what you're talking about! Include author credentials, cite reliable sources, and demonstrate expertise in your content. Google's E-E-A-T framework values first-hand experience and subject knowledge. Clear author information and confident, thorough explanations help establish your authority.
• Engagement: How users interact with your content matters. Search engines notice if readers spend time on your page, scroll through it completely, or quickly leave. Content that keeps visitors engaged (through good writing, multimedia, or interactive elements) signals quality. Make your content genuinely helpful so users don't immediately return to search results.

Common Pitfalls: Low-Quality Content Signals

• Avoid Filler Content: Search engines penalize pages padded with fluff or irrelevant information. Every sentence should serve a purpose and address the user's query. Don't use extra words just to make content longer and avoid generic introductions or repetitive passages that don't add value.
• Quality Penalties Are Real: Google actively demotes or removes low-quality content from search results. Sites with shallow, spammy, or unhelpful content lose visibility. Focus on creating genuinely useful content rather than just trying to attract clicks, as this approach risks serious penalties.
• Be Careful with AI Content: Mass-produced AI content without human oversight can hurt your site rankings. Google can identify and penalize automatically generated content that lacks originality or added value. Use AI as a helpful tool, not a replacement for human expertise—always edit, fact-check, and add unique insights to any AI-assisted content.

Best Practices for Creating AI-Friendly Content

• Create Deep, Original Content: Go beyond basics by conducting research or gathering unique data. Develop content with fresh perspectives that can't be found elsewhere. Include examples, case studies, and expert quotes to demonstrate thoroughness and value.
• Demonstrate Expertise: Showcase author credentials through bylines and detailed bios. Link to credible sources, address user questions completely, and maintain high accuracy standards, especially for sensitive topics like health or finance. Technologies like Autopilot automatically ensure your content is clustered to demonstrate where your expertise is. It even calibrates with search results to update as behaviors change.
• Enhance User Engagement: Write clearly and break up text with headings, bullet points, and relevant visuals. Include informative images with descriptive alt text and captions. Engaging content encourages longer sessions, which search engines view favorably.
• Structure Content Properly: Use appropriate heading tags (H1, H2) to create a logical hierarchy. Implement schema markup to help search engines understand your content's purpose. Analyze top-ranking competitors to identify which schema types work well in your industry.
• Use Data-Driven Insights: Leverage analytics to track performance and refine your approach. Monitor which content formats are trending in search results and adapt accordingly. Technologies like Copilot for Content Advisor ensure content fully encompasses a topic to be cite-able in AI and ranked in traditional search.

To thrive as AI algorithms evolve, prioritize genuine value. Continue focusing on user intent, E-E-A-T, and content originality. Stay agile: monitor performance, adapt to new query patterns, and keep an eye on AI search developments. By building content strategies around these enduring signals now, you’ll be prepared for whatever new quality standards AI search brings in the future.

Why Long-Tail SEO Matters More Than Ever

AI-powered search—especially Google’s AI Overviews—is rewriting the rules of SEO. In the past year alone, long-tail, conversational queries have exploded in frequency. According to our recent study on AI Overviews, queries showing an AIO with 8+ words have grown 7x since AIOs launched in May 2024. Users are asking more complex questions, and Google’s AI is now capable of delivering nuanced, contextual responses directly in the search results.

This shift isn’t cosmetic—it’s strategic. Marketers who focus only on head terms may miss the real discovery moment: being cited, surfaced, or recommended by AI before a user ever clicks.

Long-tail keyword optimization is your front door to this AI-driven visibility. Let’s dive into how to find, optimize, and measure long-tail keywords in an AI-first world.

Understanding Long-Tail Keywords in the AI Era

Long-tail keywords are specific, lower-volume phrases typically made up of four or more words. In an AI-powered search environment, these queries take on new significance:

• They reflect how people naturally speak or think—mirroring prompts typed into ChatGPT or voiced to a virtual assistant.
• They signal high intent—users searching “how to optimize solar panel efficiency in cloudy climates” are not browsing, they’re problem-solving.
• They fit perfectly into the AI Overview format, which synthesizes content from multiple sources to answer detailed prompts.

Then: “solar panel efficiency”
Now: “how to optimize solar panel efficiency in cloudy climates” (now likely to trigger an AIO)

What used to be overlooked as niche is now front and center in Google’s generative results.

Why Long-Tail Keywords Are Critical for AI Search

BrightEdge data shows:

• 49% increase in Google impressions since AIOs launched, but a 30% drop in CTR as more users engage with the AI layer without clicking.
• 48.3% increase in technical vocabulary, with queries using domain-specific language that AI Overviews now handle with ease.
• A 400% increase in citations from positions 21–30, and 200% more from positions 31–100—AI is reaching deeper into the SERP to source helpful, topic-rich content.

In this context, long-tail keywords aren’t just useful—they’re essential. Here’s why:

• Lower competition: These queries are less saturated, especially if you move beyond the “best X for Y” structure and into nuanced use cases.
• Higher relevance: They often imply clear intent and enable AI systems to identify focused answers for users.
• Greater citation potential: Because AI Overviews don’t just pull from the top of page one, well-structured, long-tail content has a real shot at being included—even without a #1 ranking.

How to Identify AI-Optimized Long-Tail Keywords

1. Use AI-Powered Keyword Discovery Tools
   Platforms like BrightEdge Data Cube X help uncover the specific phrasing users are typing into Google—and which ones generate an AI Overview. You can:
   • Search by intent category (how-to, transactional, informational)
   • Filter by AI-triggering potential
   • Spot which queries align with emerging AIO coverage
2. Watch for Conversational Patterns
   Monitor sources like People Also Ask, Reddit, and Google’s new “AI follow-ups” for real-world phrasing. Many AIO-triggering prompts are long-tail in nature and come in the form of:
   • Problem statements (“why is my basil plant wilting indoors”)
   • Niche comparisons (“CRM for remote SaaS teams”)
   • Specific use cases (“email automation tools for nonprofits with <$10M budget”)
3. Cluster Keywords Around User Intent
   Use Keyword Reporting to group long-tail variations into themes. Don’t build isolated pages for each—organize them by:
   • Primary query (e.g., “AI tools for keyword research”)
   • Related long-tail intents (e.g., “free keyword research AI tools,” “AI tools for B2B SEO,” etc.)

This helps ensure your content is seen as comprehensive and contextually rich—a key ranking factor in generative search.

How to Optimize Content for Long-Tail Discovery in AI Search

1. Align With Natural Language
   AI Overviews reward human-like phrasing. Write your content as if you’re answering a question for a colleague—not just a robot. Avoid keyword stuffing. Instead:
   • Use the full long-tail query in your page title or H1.
   • Answer the implied question clearly within the first paragraph.
   • Support the content with examples, lists, or short paragraphs—formats favored by AIOs.
2. Focus on “Prompt Completeness”
   Think like the AI: can your content answer the user’s full question in one place?
   • If the query is “How do I treat an ACL tear without surgery?”, your content should cover both causes and non-surgical treatment options—with structured sections and clear subheadings.
   • Use schema markup (e.g., FAQPage) to make that content more digestible for AI parsing, even if schema doesn’t directly trigger AIOs yet.
3. Focus on the Follow-up to Core Keywords
   BrightEdge data shows that 89% of AI citations come from outside the top 10 organic results. That’s unprecedented.
   AI search isn’t just looking for the “best-ranking” content—it’s looking for the best-fit content.
   Be that fit.

Using AI to Scale Your Long-Tail Strategy

Leverage BrightEdge Copilot and Data Cube X
AI can help you:

• Generate long-tail variants for each intent (e.g., using Copilot to ideate around a core concept)
• Spot rising trends and surface them before competitors
• Map your content to what’s being pulled into AI Overviews via Data Cube X Serp Features

Measuring Long-Tail Performance in an AI World

Success in long-tail AI SEO isn’t just traffic. It’s visibility, inclusion, and influence. Track:

• AIO citation presence via BrightEdge Generative Parser
• Share of voice on long-tail clusters across competitor content
• Engagement metrics for long-tail landing pages (e.g., scroll depth, time on page)
• Conversions driven by niche content—especially in B2B or high-intent categories

If you're seeing high impressions and low clicks, don’t panic. That might mean you're appearing inside AIOs—an increasingly valuable form of visibility. Use BrightEdge Google Search Console Reporting to confirm and refine.

Final Thoughts: From Rank to Recommendation

AI search is making long-tail the main event—not just a side tactic.

• Users are asking longer, more specific questions (8+ word searches up 7x)
• AI is citing deeply relevant, structured content, even from the bottom of the SERP
• The new game isn’t “rank for head term.” It’s “be the best possible answer to a real-world prompt.”

Understanding E-E-A-T: The Cornerstone of Quality Content

Google's quality guidelines emphasize E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) as the framework for evaluating content quality, especially as AI-generated content becomes more common.

In 2022, Google added "Experience" to the previously known E-A-T framework, highlighting the importance of first-hand, real-world knowledge. This means successful content should demonstrate the author's actual experience, such as personal product use or location visits.

E-E-A-T isn't a single ranking metric but rather a framework that influences how algorithms evaluate content. Google's systems look for signals of each component:

• Experience: Content showing first-hand expertise and depth of knowledge
• Expertise: Clear demonstration of subject matter knowledge
• Authoritativeness: Establishing credibility through author bylines, bios, and references
• Trustworthiness: Clear sourcing, evidence of expertise, and background information about authors or sites

This framework is crucial because it underpins Google's helpful-content standards. Google has clarified that content quality matters more than who (or what) created it—meaning even AI-generated content must earn trust by meeting E-E-A-T criteria

Low-quality, automated content created merely to manipulate rankings is treated as spam, while original content demonstrating E-E-A-T is more likely to rank well. Remember: quality over quantity is key, as Google prioritizes content providing real value.

The Impact of AI on Content Creation and SEO

AI content tools are transforming how marketing teams generate and scale content. BrightEdge users have used Copilot for Content Advisor to generate millions of briefs and drafts to aid in optimized content creation. It assists in automated content drafting, on-page optimization, and keyword research. Generative AI can dramatically speed up content production – for example, writing a page that might take hours can be done in seconds with a prompt.

These technologies must be coupled with original human elements. This means infusing AI drafts with original anecdotes, examples, and strategic thinking that set your content apart.

Challenges and Opportunities in the AI Era

The Growing Impact of AI Tools

SEO professionals are increasingly adopting AI tools for content creation and optimization, seeing significant improvements in publishing speed and content iteration capabilities. While AI delivers clear benefits, many professionals still prioritize maintaining content quality and authenticity when leveraging these technologies.

Quality Standards Remain Paramount

Google's position is straightforward: using automation isn't prohibited, but automated content must be high quality and "helpful and people-first." Content generated solely to manipulate search rankings violates spam policies. The best approach is using AI to enhance your strategy—BrightEdge's Copilot for Content Advisor exemplifies this balanced approach, helping teams generate idea lists or first drafts while maintaining focus on user value.

Evolution of Search Behavior

AI is transforming how users interact with search. Generative AI features like Google's AI Overviews are appearing more frequently. These direct-answer features can reduce clicks to traditional results since users often find their answers without leaving the search page. This doesn’t mean AI-assisted content can’t serve AI and traditional results. In fact, maintaining strong organic rankings helps ensure your content appears in AI-generated answers as well.

Overall, AI offers tremendous opportunity to create and optimize content at scale, but it raises the bar on quality. Marketers must use AI tools strategically, uphold E-E-A-T, and adapt to new search formats. Done right, AI can free teams to focus more on strategy and user needs, while continuing to build content that humans and algorithms alike trust.

Implementing E-E-A-T Principles in AI-Generated Content

Infusing Human Expertise and Experience

Building true E-E-A-T into AI-assisted content requires deliberate steps to demonstrate expertise, authority, and trust. Google's quality criteria specifically look for content that shows first-hand expertise and depth of knowledge, such as actual product usage or location visits. To achieve this:

• Incorporate real experiences: Add case studies, personal anecdotes, or data analysis that only knowledgeable professionals could provide.
• Include subject-matter experts: Have specialists write or review content to ensure accuracy and add unique insights.
• Showcase credentials: Always include author bylines with relevant qualifications to help users judge credibility.
• Support with authority: Link to recognized sources, official research, and reputable websites to boost authority.
• Ensure accuracy: Fact-check all AI-generated statements and remove unsupported claims.
• Consider transparency: When appropriate, disclose AI assistance while ensuring human oversight is emphasized.

By blending AI efficiency with real expertise, demonstrating clear authoritativeness, and building trust through accuracy, AI-assisted content can meet Google's highest quality standards.

Optimizing Content for AI Search

As search evolves, strategies must adapt to align with how AI systems interpret and present content:

• Use structured data: Implement schema markup (FAQ Page, HowTo, Product) to help AI systems recognize authoritative answers.
• Format for clarity: Use clear headings and bullet points so AI can easily parse your content.
• Prioritize page experience: Ensure fast loading times and follow Core Web Vitals for better user engagement.
• Create concise answers: Structure content with key answers immediately visible, as AI-driven interfaces often pull short summaries.
• Monitor engagement: Track metrics like click-through rate and session duration to gauge content effectiveness.
• Update regularly: Refresh top-performing content to stay aligned with evolving AI patterns.

The most successful approach combines structured content, excellent user experience, and data-informed updates while always prioritizing user needs and questions. This human-centered strategy ensures content thrives in the AI-driven search landscape.

Measuring E-E-A-T Success in AI Search Environments

As AI search features become more prominent, measuring E-E-A-T effectiveness requires specialized metrics that reflect both traditional SEO and AI-specific performance:

AI Feature Inclusion

Track how often your content appears in AI search features like Google's AI Overviews or generative answer boxes. Being consistently cited in these AI-generated summaries indicates your content demonstrates the expertise and authority that AI systems recognize. Monitor which specific pages and topics receive the most AI citations to identify your strongest E-E-A-T content.

Organic Traffic Patterns with AI Integration

Analyze traffic changes as AI features expand. Look for correlations between strong E-E-A-T signals and content resilience against potential traffic declines from AI answer boxes. Pages with robust expertise signals often continue receiving clicks even when competing with AI summaries, as users seek deeper information from trusted sources.

Query Intent Satisfaction

Measure how well your content addresses the complete user journey in AI-first search. AI systems evaluate content based on how thoroughly it answers user questions and anticipates follow-up needs. Track whether users who land on your page from AI-influenced search results engage deeply or quickly return to search results (indicating incomplete answers).

AI-Specific Engagement Signals

Track new engagement patterns emerging in AI search interactions. This includes metrics like zero-click searches (where users get information directly from AI summaries) versus full-content engagement. Content with strong E-E-A-T often drives users to seek more detailed information beyond AI summaries.

Structured Data Effectiveness

Measure how your schema implementation impacts AI feature inclusion. Content with proper structured data (FAQPage, HowTo, etc.) that aligns with E-E-A-T principles is more easily parsed by AI systems. Track whether improvements in structured data lead to better representation in AI search features.

Authority Recognition in Competitive Analysis

Compare your AI feature inclusion rate against competitors for the same queries. If your content appears more frequently in AI-generated answers for shared keywords, it suggests your E-E-A-T signals are stronger. Use this comparative data to identify opportunities for enhancing expertise and authority markers.

For successful measurement, combine traditional analytics with AI-specific tracking tools that monitor your content's performance across emerging search features. This holistic approach ensures your E-E-A-T strategy remains effective as search continues its evolution toward AI-first experiences.

Finally, adopt a mindset of continuous improvement. Regularly review performance data to spot underperforming content. A drop in traffic or engagement might mean E-E-A-T elements need strengthening (e.g., adding expert quotes, updating references, or clarifying trust signals). Use this feedback loop: refine content based on metrics and re-test. In summary, E-E-A-T implementation for AI search is not a one-time task but an ongoing strategy. By grounding content in real expertise and trust now, you’ll be ready for whatever AI-driven search engines bring next.

Site migrations have always been one of the riskiest moments for organic search—but in 2025, the stakes have grown higher. Search isn’t just about rankings anymore. It’s about how you appear in AI-generated answers, summaries, and recommendations. Whether you’re rebranding with a new domain, launching a redesign, or moving to a new CMS, the wrong migration decisions can erase years of hard-earned search visibility across both traditional SERPs and AI search.

This guide was created to reflect the new search reality—where AI models not only crawl and rank your content but decide whether to cite it in high-visibility summaries. We wrote a step-by-step migration guide helped thousands of marketers navigate the basics. But this new guide is for 2025: which requires the fundamentals but you must also have an AI-focused strategy which will require some specific capabilities.

Site Migrations Happen Regardless of Experience Levels

This guide is written for digital marketers—not just technical SEOs— who are tasked with leading or supporting a website migration. Whether you're planning a full domain switch or relaunching a mobile-first redesign, there are fundamental steps required which ensure your transition is smooth.

We’ll walk you through:

• Major Migration Types
• What to do pre-launch, during launch, and post-launch
• How AI search engines like Google’s AI Overviews and SearchGPT evaluate and cite content differently from traditional engines
• The capabilities within BrightEdge and OnCrawl that can help you prepare, execute, and monitor your migration successfully

What Is a Site Migration?

A site migration is any substantial change to your website’s domain, structure, or platform that affects how it appears and performs in organic search. The changes may be technical, content-driven, or structural—but all of them impact how Google, Bing, and now AI engines crawl, interpret, and cite your pages.

Here are common types of migrations digital marketers may oversee:

• Domain name change or rebrand (e.g., oldbrand.com &rarr; newbrand.com)
• Protocol shift (HTTP &rarr; HTTPS)
• URL structure changes, like removing .html, restructuring categories, or shifting from subdomains to subfolders
• Platform or CMS migration, which can introduce new templates, URL formats, and rendering behavior
• Website redesign or code overhaul, often changing content hierarchy, page templates, and load times
• Mobile migration, such as moving from m.example.com to a fully responsive single site
• International site migration, such as consolidating ccTLDs into a subfolder model
• Site consolidation, combining multiple brand sites or microsites into one
• Host or server migration, where speed, uptime, and crawlability could be affected

Each of these scenarios is technically different—but they all require you to preserve one thing: your SEO equity, including rankings, links, citations, crawl paths, and topical authority.

In 2025, you also need to preserve your AI equity: the structured signals, schema, and associations that feed your presence in AI search results.

The AI Search Changes the SEO Migration Playbook

AI-powered search—like Google’s AI Overviews, Bing’s Copilot, and tools like Perplexity—don’t just index your site. They summarize, synthesize, and cite content from across the web.

That means your visibility isn’t just about where you rank anymore. It’s about whether AI systems trust your content enough to include you in answers.

During a site migration, you risk losing that trust if:

• Previously cited content is removed or merged without maintaining its identity
• Schema or structured data is dropped
• Pages are slower to render, load behind JavaScript, or fail to meet accessibility standards
• Redirects are misconfigured, creating loops or soft 404s
• Internal link structures are weakened, breaking topical authority chains

To win in AI search after a migration, you must go beyond traditional redirects and rankings. You need to:

• Maintain clarity, structure, and speed in every new page
• Monitor how your visibility in AI summaries and citations changes
• Use schema markup and semantic consistency to reinforce your topical authority

With BrightEdge Data Cube X, you can track how your site is cited and how changes affect your visibility—across both keyword-based and AI-driven search results.

Pre-Migration: Planning, Benchmarking, and Risk Assessment

Whether you’re running a site redesign, consolidating properties, or migrating to a new CMS, the planning phase is where you make or break success. Here’s what digital marketers need to do before launch:

1. Run a Complete Content and URL Inventory

Use BrightEdge ContentIQ or OnCrawl to crawl your site and export:

• All active URLs
• Title tags, meta descriptions, and H1s
• Canonical tags and schema markup
• Internal link structures and click depth

This becomes your working document to map redirects, ensure metadata preservation, and retain content integrity. Combine with BrightEdge Data Cube X to overlay performance data: which pages rank, convert, or appear in AI panels?

2. Set Benchmarks: Traditional + AI Search

Don’t just track keyword rankings. Track:

• Organic traffic by page
• AI Overview citations by query (using Data Cube X)
• Backlinks and top referrers
• Indexed URLs in Search Console

Use this to create KPIs: “Preserve 95% of AI citations and 90% of organic traffic within 60 days post-migration.”

3. Create Your Redirect Map

Depending on the type of migration, you may use:

• 1:1 redirect mapping (old URL &rarr; new URL)
• Wildcard redirects (entire path structures moved with patterns)

Use 301 redirects exclusively, not 302s. Test them in staging. Create a spreadsheet with columns: Old URL, New URL, Redirect Type, Schema Preserved (Y/N).

4. Audit Your Structured Data Strategy

Preserving schema types—Product, Article, FAQ, etc.—is now an AI priority. Confirm that your schema will:

• Remain intact post-migration
• Be upgraded if templates change
• Align with what’s cited in AI results (e.g., using FAQPage for common questions)

5. Crawl and Validate Your Staging Site

Run ContentIQ or OnCrawl on your staging site before go-live. Check:

• Canonicals reflect the new domain/structure
• Page speed meets Core Web Vitals
• Schema validates cleanly
• All test redirects function correctly
• Meta tags and headers are carried over

Lock the staging environment with robots.txt and noindex, but verify all pages render cleanly—especially JS-heavy templates.

Migration Day: Execute with Precision

Launch isn’t just a technical handoff. It’s an SEO and AI visibility event.

Key Tasks:

• Enable all 301 redirects and test top 100 legacy URLs
• Update internal links and canonical tags to reflect the new domain or structure
• Submit updated XML sitemaps in Google Search Console and Bing Webmaster Tools
• Use Google’s Change of Address tool if you’ve changed domains
• Validate that schema, meta tags, hreflangs, and mobile tags have transitioned correctly

Monitor crawl behavior with OnCrawl log analysis in real-time to confirm that bots are hitting the new URLs and following redirects properly.

Post-Migration: Monitor, Fix, and Optimize

The weeks after migration are your window to catch and fix issues before they become long-term visibility losses.

What to Watch:

• Redirect coverage (ContentIQ + GSC Coverage report)
• Indexation shift (Old site index down, new site index up)
• Keyword rankings + AI citations (Data Cube X + SearchIQ)
• Traffic anomalies (BrightEdge’s Anomaly Detection)
• Bot crawl paths (OnCrawl live logs)

If you notice a major page drop in AI summaries or organic rankings, use:

• BrightEdge Copilot to rewrite content or metadata inline with AI patterns
• Autopilot to automatically optimize underperforming pages

Also, use SearchIQ to see what technical or content-related shifts may be affecting how you’re cited in AI Overviews.

Final Thoughts: Modern Migrations Require Modern Strategy

Migrating a website has always required planning. But in 2025, you’re not just migrating URLs. You’re migrating your relevance, your trust, and your AI presence.

The best migrations don’t just preserve—they improve. With capabilities like ContentIQ, Data Cube X, SearchIQ, Copilot, and Autopilot from BrightEdge—and technical analysis from OnCrawl—you can:

• Plan and map with confidence
• Migrate without SEO loss
• Monitor and recover post-launch
• Prepare your site to win across both search and AI systems

Search is no longer one-dimensional. Your next migration should be built for the AI-first era.

2025 SEO Site Migration Checklist

Preserve SEO performance and AI search visibility across domain, CMS, and site structure changes.

Pre-Migration Planning

Content & Technical Preparation

• Crawl and inventory all current URLs (BrightEdge ContentIQ / OnCrawl)
• Identify top-performing pages (SEO traffic, conversions, backlinks, AI citations)
• Export and map all title tags, meta descriptions, H1s, canonicals, and schema
• Benchmark rankings and AI citations (BrightEdge Data Cube X + SearchIQ)
• Document baseline metrics: indexed pages, traffic by URL, CTR, page speed
• Assess structured data coverage and plan to preserve/expand it
• Run a full technical SEO audit and address crawl issues on the old site
• Set site migration KPIs (e.g. “recover 95% of traffic within 60 days”)

Redirect Strategy

• Create a detailed 301 redirect map (Old URL &rarr; New URL)
• Use wildcard redirects only when structure is unchanged
• Ensure no redirect chains or loops
• Validate redirect logic in staging environment

Staging Site Validation

• Block indexing (robots.txt disallow + noindex meta)
• Run full crawl (ContentIQ / OnCrawl) to validate:
  • Internal links
  • Canonical tags
  • Meta data
  • Schema markup
  • Page speed
  • Mobile rendering

Migration Execution

Go-Live Checklist

• Launch all 301 redirects at go-live (not after)
• Switch internal links and canonicals to new URLs
• Submit updated XML sitemap to Google Search Console + Bing
• Use Change of Address tool (if applicable)
• Verify schema, hreflangs, and structured data are live
• Check robots.txt and remove staging disallow directives
• Validate analytics tracking is working on all pages
• Announce relaunch across owned channels (blog, social, email, PR)

Post-Migration Monitoring

Week 1–4 Tasks

• Monitor 301s and crawl errors (Search Console + ContentIQ)
• Track indexation trends: old URLs dropping, new URLs rising
• Compare traffic and rankings to pre-migration benchmarks
• Watch for anomalies using BrightEdge Anomaly Detection, such as:
  • Sudden drop in organic clicks or impressions for high-priority pages
  • Drop in keyword rankings for target terms
  • Spike in 404 (Not Found) errors from old URLs not redirecting
  • Any 5xx (server) errors indicating instability or downtime
  • Crawl rate drops or delays in sitemap processing by Google
• Track AI search presence in Overviews and summaries (SearchIQ)
• Monitor server logs for unexpected bot behavior (OnCrawl):
  • Googlebot hitting disallowed or missing URLs
  • Lack of crawl activity on newly launched pages
  • Disproportionate hits to old URLs without follow-through to redirects

Post-Migration Monitoring

Week 1–4 Tasks

• Monitor 301s and crawl errors (Search Console + ContentIQ)
• Track indexation trends: old URLs dropping, new URLs rising
• Compare traffic and rankings to pre-migration benchmarks
• Watch for anomalies using BrightEdge Anomaly Detection, such as:

• Sudden drop in organic clicks or impressions for high-priority pages
• Drop in keyword rankings for target terms
• Spike in 404 (Not Found) errors from old URLs not redirecting
• Any 5xx (server) errors indicating instability or downtime
• Crawl rate drops or delays in sitemap processing by Google

• Track AI search presence in Overviews and summaries (SearchIQ)
• Monitor server logs for unexpected bot behavior (OnCrawl):

• Googlebot hitting disallowed or missing URLs
• Lack of crawl activity on newly launched pages
• Disproportionate hits to old URLs without follow-through to redirects

Content & Optimization

• Reoptimize underperforming pages (BrightEdge Autopilot)
• Use Copilot to revise titles, descriptions, and schema as needed
• Run full audit on live site (ContentIQ) to catch missed issues

Ongoing

• Keep 301 redirects active for 12+ months
• Reach out to high-value sites to update backlinks to new URLs
• Track AI visibility monthly to grow beyond pre-migration baseline

We are all navigating a constantly changing search and AI landscape. As the ground shifts beneath our feet, marketers have never had a more critical time to evolve and stay ahead.

Today, together with our customers, we are making a monumental step forward as we launch BrightEdge AI Catalyst.

For The First Time Ever: Get the Complete View of Your Brand Across Traditional and AI Search

As AI and Search accelerates how brands are perceived and perform, I am proud to announce that our customers now have access to the first comprehensive solution that enables brands to influence their presence across multiple generative AI search engines.

Customers can track their digital footprint and track, understand, and optimize their presence across all aspects of search, from core and traditional search through to multiple Generative AI search engines.

And It Is All in One Enterprise-Grade Platform!

Building on our history and foundations in AI and data-driven insights, BrightEdge AI Catalyst allows brands to instantly amplify impact, outperform competitors, and confidently navigate AI search engines, including ChatGPT, Perplexity, and Google's AI Overviews.

At the heart of our customer success approach are three core principles: Inspiration, Innovation, and Impact.

• Inspiration: Inspire New Ways of Thinking
  • We inspire marketers to better understand their audiences using data insights to help customers connect with them in more meaningful ways.
• Innovation: Innovate With Cadence
  • We innovate to keep customers ahead of digital market changes through a regular cadence of market-leading technology product launches.
• Impact: Impact Multiple Business Outcomes
  • We help marketers deliver real, tangible results and business outcomes that genuinely transform their business.

These principles guide our commitment to empowering marketers with the tools and insights they need to succeed in today's dynamic landscape.

Let me share some more context on how we got to today!

The Transformation Is Here as Billions of People Turn To AI

• ChatGPT just surpassed 500 million weekly active users in late March.
• Gemini's web traffic grew to 10.9 million average daily visits worldwide.
• Bing's Copilot increased to 2.4 million.
• Anthropic's Claude reached 3.3 million daily visits.
• DeepSeek's chatbot eclipsed 16.5 million visits.

I find it super interesting that people are increasingly trusting in AI technology.

Research from Attest reveals that 68% of consumers trust information from Generative AI, with 41% having more confidence in AI search results than paid search listings. As these AI engines are growing fast monthly, each has its own interface and logic, and each shapes perceptions of brands in different ways.

BrightEdge Generative Parser ™ data shows that March referral traffic from these AI-first search engines continues to grow significantly.

• ChatGPT +19%
• Perplexity +12%
• Gemini +19%
• Claude +166%

However, while Google still dominates the industry with a 92% market share and optimizing for AI Overviews is always your first step, it shows that more and more brands are being discovered and interpreted across multiple AI platforms, each with their own:

• Interface
• Logic
• Way of shaping brand perceptions

Furthermore, some platforms will position your brand negatively; many leave you out entirely.

The Era of AI Inevitability

AI is actively shaping what customers know, trust, and believe. People are not just searching anymore; they are asking AI and AI is giving an opinion.

This represents a fundamental shift from focusing on just search rankings to understanding how AI presents brands.

Introducing BrightEdge AI Catalyst

I am thrilled to announce BrightEdge AI Catalyst, enabling brands to see where and how they are perceived everywhere it matters by AI engines.

BrightEdge AI Catalyst Completes Search Picture for Brands to Win in AI Era

Building on our two-decade history of pioneering innovation in search and AI markets, we are providing our customers with a unified overview of where they are winning and losing in key conversational moments across critical AI platforms.

But it is not just visibility that matters.

It is the proven performance results delivered with action from AI.

By leveraging billions of historical and real-time data points, customers can act around crucial revenue-generating touchpoints across both traditional search and AI search.

The AI Catalyst Advantage

Cross-Platform Visibility

Monitoring brand performance across multiple AI platforms has become increasingly complex. That is why we developed Catalyst to provide unified cross-platform visibility:

• Customers can now track their brand presence and sentiment simultaneously across Google's AI Overviews, ChatGPT, and Perplexity.
• Our dashboards allow brands to monitor performance across the entire AI search ecosystem.
• It is all in one place, providing the complete picture needed to make strategic marketing decisions.

AI Search Behavior Insights

Understanding how audiences use AI search platforms often leads to ineffective content strategies. Marketers can now bridge the gap between understanding AI search behaviors and prompt research:

• Together with BrightEdge Copilot, customers can eliminate guesswork with precise AI prompt suggestions based on actual audience behavior.
• It taps into our deep knowledge and data repository to analyze your website, existing search patterns, and billions of historical queries.
• This delivers accurate, targeted insights that align with actual AI search usage.

Multi-Platform Optimization

Creating separate content strategies for each AI platform is inefficient and costly. As marketers face resource constraints—especially when trying to optimize for multiple AI platforms simultaneously—we have placed efficiency at the core of this innovation:

• Customers can optimize once and rank everywhere with efficient content strategies that work across multiple AI-driven search environments.
• This saves valuable time and resources while maintaining consistent messaging.

Real-Time Intelligence

The AI search landscape evolves weekly, if not daily, and keeping pace with change is hard:

• BrightEdge AI Catalyst provides real-time intelligence and targeted, actionable recommendations for improving AI-driven visibility.
• We process billions of data points in real-time, allowing our customers to make quick strategy adjustments when they matter most.

AI-Influenced Journey Mapping

Understanding the customer journey has always been crucial, but AI has fundamentally transformed how customers discover and engage with brands:

• With BrightEdge AI Catalyst, we have pioneered new approaches to mapping these AI-influenced journeys.
• This includes advanced features for persona development, intent mapping, and journey analysis.
• It reveals how your audience interacts with AI systems throughout their decision-making process.
• It identifies key AI touchpoints that impact engagement and conversion, helping our customers create more effective targeting strategies.

The Full Picture: AI-Driven Brand Perception and Driving Performance

AI Catalyst gives brands the complete picture of how AI highlights their brand—where they appear, where they do not, and how they are presented.

But it also does much more by connecting the data dots:

• Built on 20 years of working with top brands, using billions of searches to give marketers the clarity they need now.
• It connects this information directly to business plans, goals, and results—all inside the BrightEdge platform.
• It shows the complete picture and helps brands act (with confidence and trust in data) whenever and wherever AI affects presence, perception, and performance.

Learn more about BrightEdge AI Catalyst here: https://www.brightedge.com/ai-catalyst

This is Your AI Moment – Let Us Guide You

AI is rewriting the rules of search. We are not just keeping up—we are leading the way. And we are here to make sure you do not get left behind.

And there is more.

With GSC Reporting, we are helping you answer the question every leader is asking: How is AI impacting my existing Search business? Now, you can finally measure that directly. And with the new BrightEdge Chrome Extension, we are putting real-time optimization into your workflow so that every page, update, and decision happens with AI insights behind it. This empowers you to act at the speed that AI demands.

This Is What Enterprise AI Is: Connected, Actionable, And Built for Impact.

Together with our customers, we are not just adapting to AI—we are building the capabilities to win. Let us keep pushing forward to shape the future of search and AI.

Want to learn more about how BrightEdge can help your business navigate the AI search revolution? Contact us today for a personalized demo.

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.

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!