Study: Google AI Overviews Appear In 47% Of Search Results via @sejournal, @MattGSouthern

A new study shows that Google’s AI Overviews appear in nearly half of all search results and take up to 48% of mobile screen space.

Conducted by Botify and DemandSphere, the research analyzed over 120,000 keywords across 22 websites.

The study, conducted between August and September, finds that traditional SEO metrics like click-through rates may no longer give a complete picture of search performance.

When AI Overviews show up with featured snippets—which happens 60% of the time—these can occupy up to 76% of mobile screens, pushing regular listings out of view.

While strong organic rankings remain crucial, with 75% of AI Overview mentions coming from top-12 ranked pages, businesses need to adapt their strategies to the rise of AI in search.

Here are more highlights from the study.

Zero-Click Search

The study highlights a trend toward zero-click searches, with 60% of searches now resolved without users clicking links.

This shift creates a new challenge for businesses dependent on organic search traffic.

Search Volume & Keyword Length

Key findings about search patterns include:

  • Keywords with under 1,000 monthly searches triggered AI Overviews 55% of the time
  • Long-tail keywords (5+ words) generated AI Overviews in 73.6% of cases
  • Commercial intent queries showed AI Overviews 19.4% of the time
  • Informational queries triggered the feature 58.7% of the time

Crawlability Issues

The research showed that Google misses crawling about 50% of pages on large websites, while Bing misses 20% of pages that get organic traffic from Google.

The report notes:

“You may have the best answer in your site’s pages, but if they aren’t found within the Google search index, they risk not being cited in an AI Overview — no matter how well-optimized they are otherwise.”

Content Quality & Relevance

The study introduced a new way to measure content relevance using cosine similarity analysis.

It found that websites cited in AI Overviews often closely match the AI-generated summaries, indicating that higher quality content is linked to better visibility in AI search results.

What This Means

The study suggests several strategic priorities for businesses:

  • Measure visual SERP metrics like pixel depth to quantify true organic visibility
  • Analyze semantic similarity between page content and AI Overview summaries
  • Prioritize earning, growing, and defending top 12 organic ranking positions
  • Maintain strong SEO fundamentals to support organic performance
  • Develop a broader AI search strategy encompassing new platforms like Bing, ChatGPT Search, and Meta AI

Methodology & Scope

The research, conducted from August 15 to September 1, analyzed:

  • 36,000 commercial keywords
  • 85,638 informational keywords
  • 22 websites across e-commerce, publishing, and branded sectors
  • Both desktop and mobile search results

Looking Ahead

The study reveals changes in how users view search results and how businesses should manage their online visibility. AI Overviews pose challenges for organic search but also present opportunities for adaptable businesses.

Key points for search marketers include maintaining strong organic rankings, tracking visual SERP positioning, and creating content that meets user needs.

As search engines enhance their AI tools, it’s vital to maintain a strong foundation of technical SEO while expanding AI-focused strategies for greater visibility.


Featured Image: Cast Of Thousands/Shutterstock

How Significant Is AI Chatbot Traffic In B2B? via @sejournal, @Kevin_Indig

The first commercial power plant had only 59 customers when Thomas Edison built it in 1882.

Eighteen years later, access to electricity had already expanded to 3.8 million U.S. Americans (5% of households).1 From there, power grid access grew exponentially:

  • 8% in 1907.
  • 35% in 1920.
  • 68% in 1929.

We stand at the doorstep of a comparable technology: AI.

  • ChatGPT is the second fastest-growing consumer product.
  • Capital expenditures of hyperscalers could exceed $300 billion in 2025.2
  • AI already makes consultants, writers, and financial experts more efficient.
  • A joint report by Semrush and Statista found that 1 in 10 U.S. internet users go to gen AI for search first before exploring search engines.

But when is the right time for B2B companies to invest in AI chatbot visibility?

For companies with limited resources, investing in technology too early can be a costly distraction (pets.com). Being too late can cost even more (Kodak).

B2B is a particularly interesting case for three reasons:

  1. Longer sales cycles.
  2. High competition.
  3. AI chatbots answer a lot of information queries directly that used to bring traffic from Google. Ecommerce, for example, is different because searches either start on Amazon directly or shopping is natively integrated (see Perplexity shopping or Google’s new experience).

I analyzed referral traffic from the biggest AI chatbots to six B2B companies with a combined traffic volume of over 1 million monthly visits.

The data shows an average of 0.14% when comparing AI chatbot referrals to organic visits. That’s one referral for every 714 organic visits. Peanuts.

But in the next three years, AI chatbot referral traffic could make up over 35% of organic traffic. As a result, companies would do well to develop playbooks for growing visibility now to benefit from first-mover advantages.

How Much Traffic Do AI Chatbots Send?

Image Credit: Kevin Indig

In my case study of six B2B companies, referral traffic from AI chatbots has grown from an average of 250 visits per month in the first half of 2024 to over 1,300 in November (+5x).

The drivers are growing usage of AI chatbots, more links to sources, and OpenAI’s introduction of its AI search engine, ChatGPT Search.

Image Credit: Kevin Indig

Almost unsurprisingly, ChatGPT sends the most referral traffic, with almost 50%.

Perplexity comes in 2nd at 21.7%.

Gemini sits in a surprisingly distant fifth place.

Even Bing and Copilot send more traffic, even though Gemini was built by search monopoly Google. It’s unclear whether usage or design is responsible for Gemini’s low referral traffic.

Even though AI chatbot referral traffic is growing rapidly, it makes up only 0.34% in comparison to organic traffic.

For some companies, it’s as low as 0.09%, and for others, it’s as high as 0.9%. It’s easy to dismiss referral traffic from AI chatbots because of their miniscule size.

Every smart manager would categorize such a small customer acquisition channel as a distraction. And yet, it’s a mistake.

Referral traffic from AI chatbots grows at a staggering monthly average of 25.6%.

As humans, we’re inherently bad at understanding compound growth because most of our environment is linear (distance, time, etc.).

An annual growth rate of 7% seems harmless until you realize it doubles growth in 10 years.

Only 14% of U.S. Americans have tried ChatGPT.3 They’re early adopters.

Over 170 million more could join the trend in the next years (assuming 334 million Americans minus ~35% for age), which should skyrocket referral traffic even more. And that’s just the U.S.

On the flipside, organic traffic is flat to down for many B2B companies. In my sample set, organic traffic grew only 1.1x between January and November on average.

Image Credit: Kevin Indig

When considering constant growth rates, over one-third of organic traffic could come from AI Chatbots in three years.

In the sum total, AI chatbot referrals would make up over 34% of traffic. Two companies in my set of six are projected to get more than double as much traffic from AI chatbots than from search engines.

Referral to organic traffic ratio projections:

  • Today: 0.14% (January – November).
  • In a year: 0.79%.
  • In two years: 5.7%.
  • In three years: 52%.

Note that we don’t yet know whether AI chatbots cannibalize search engine usage one-to-one or whether we’ll do both.

I have a hunch it’s going to be the latter because AI adoption will happen in phases, and overall usage could increase because LLMs are so capable.

That’s also why my projection chart has a higher total as AI chatbot adoption grows in year 3, which means more potential traffic for B2B companies instead of less.

Of course, this is a small case study of only six B2B companies, and growth rates likely won’t stay constant.

Most projections are wrong, but this exercise helps to put in perspective how quickly the status quo can change.

Implications

My advice is clear: Don’t bank on steam engines. Bank on the power grid.

AI chatbots show early signs of compound growth that could become significantly faster than we can intuitively grok.

Here is what I tell my (B2B) clients:

  • Monitor LLM crawlers, referral traffic, and conversions by landing page to figure out which content gets crawled and performs well in AI chatbots.
  • Track your keywords as questions with a house-made, API-based tracking system or proprietary LLM tracking tools. Monitor visibility ChatGPT, Perplexity, Copilot/Bing, and Gemini because we don’t yet know whether “AI chatbot optimization” will lead to the same results for all chatbots, similar to how SEO is very similar for Google and Bing or whether they will reward different approaches.
  • Test net-new content and content adjustments to provide better answers in AI chatbots. Now is the time to write the playbook.
  • Keep doing classic SEO since AI chatbots still lean heavily on their results to ground answers.

1 The Residential Adoption of Electricity in Early Twentieth-Century America

2 Microsoft Corporation (MSFT) Set to Lead AI Spending Surge with $90 Billion CapEx in 2025, Says Morgan Stanley

3 A majority of Americans have heard of ChatGPT, but few have tried it themselves


Featured Image: Paulo Bobita/Search Engine Journal

What 7 SEO Experts Think About AI Overviews And Where Search Is Going via @sejournal, @theshelleywalsh

Generative AI and the introduction of AI Overviews to SERPs have dominated this year as search has changed more in the last year than in the last 10 or 20 years.

But it might be that many of these changes are coming in spite of Gen AI and not because of.

SEO has been maturing and aligning with classic marketing for many years. AI has been the catalyst that has now created an urgency to rethink SEO strategies and start to approach SEO in a digital marketing holistic way.

SEO is no longer about just being visible in SERPs. Consideration is also needed for visibility in Gen AI apps, social media, and any channel where your audience might be.

Search traffic will likely become more fractured across different channels, and an SEO’s job will become much more complex. The days of easy traffic are well in the rearview mirror.

For the last six months, I interviewed a series of the smartest minds in SEO about their thoughts on AIO.

I asked them all the same question: “What do you think about AI Overviews? How will they impact the industry, and where is this going?”

7 SEO Experts Share Their Thoughts About AI Overviews

The most interesting part about asking the same question to different people is that you get a wide variety of answers – all approaching from different angles.

All of the excerpts below are just an extract and summary taken from a series of short videos.

It’s worth watching each of the videos in full to get the nuance and detail of what each of the experts has to say.

Pedro Dias: AI Is Raising The Bar For Knowledge

I started by speaking to Pedro Dias earlier in the year.

Ex-Googler Pedro has always been focused on user experience, and he believes Gen AI is widening the gap between generalists and true specialists. And that real expertise will be more valuable than ever. It’s the middle ground that will be displaced.

Pedro also believes in building communities and considering the customer journey – where you can give away content for free and where you gate your most valuable resources for your audience.

“The real value lies in crafting more comprehensive materials. Ideally, these should be gated or shielded from Google, allowing us to funnel readers genuinely interested in deeper insights into our platforms. This approach protects our assets and enables us to nurture a loyal audience who seeks value beyond surface-level information.

Professionals need to determine what they can safely offer to AI for broad discovery and what content should remain exclusive to their clients. Every business must identify this balance. While competition will compel some to disclose more detailed content, creators must decide where to draw the line between free and premium offerings.

AI is raising the bar for knowledge. It’s widening the gap between generalists and true specialists, making deep expertise more valuable than ever. Middle-ground professionals, who rely on surface-level knowledge, are at risk of being displaced.

The industry will thrive on the backs of those investing in research, innovation, and specialized knowledge. Others may settle for AI-generated information, but there will always be an audience that seeks deeper insights and expertise.”

Erika Varangouli: SEO Cannot Be Independent Of Brand

Erika believes that we have been spoiled previously, as SEO was not as complex as it is today.

Search used to focus on keywords and clicks, which is a much more one-dimensional approach than what we face today.

She also believes that creativity and branding are essential moving forward.

“20 years ago, you’d just write stuff about car insurance – ‘best car insurance’ – and make sure you had it everywhere.

So, in reality, it wasn’t about understanding or satisfying an audience. But as online behaviors, features, and capabilities have developed, we couldn’t just continue doing SEO that way.

I think moving forward, one of the predominant skills is going to be creativity. SEO has always been about strategy and strategic thinking, but now, more than ever, it’s going to require creativity. And that will probably be the edge we have over AI.

It’s becoming clearer that SEO cannot work outside of understanding the basic principles of marketing, psychology, and branding.

I think something that’s been obvious for a long time is that SEO cannot be independent of brand. But it was functional even if you ignored it for a long time.

I think we’ve passed the point now where we cannot ignore it. SEO reports that rely on rankings, clicks, or traffic won’t look great, but how SEO can really bring results is through collaboration with other marketing disciplines and the business as a whole.

Think about the audience, owning the conversations – not owning the clicks – and you should be fine.”

Jono Alderson: Understanding The Problems Your Audience Has Will Be Crucial

Jono believes that AI Overviews are a symptom of a bigger change and that it was never Google’s objective to be a list of 10 blue links.

What they have always aspired to is to understand what you want and solve your problem.

“This 20-year period we’ve had of typing into an input box and getting a list of links was a temporary dysfunction on that journey.

Now, we’re seeing the first chapter of where they really wanted to get to, and that has some big changes. The obvious ones are things like zero-click searches becoming more prolific, where people type or speak something, and Google solves the problem in situ.

This has huge impacts on the web’s economic model – not just for sites relying on conversions but also those relying on clicks for advertising.

Google’s own advertising ecosystem, which relies on visits to ad-running websites, is affected, too. Everyone, including Google, is still figuring out what this all means.

The model of creating content just to bridge traffic to websites is falling apart because Google and users no longer need that content.

In many cases, Google’s AI-generated results will be better because they’re unbiased, multi-sourced, up-to-date, and not selling a specific product.

Producing content for keywords just to rank may not be the future of SEO. While being topical, newsworthy, or adding truly new value still works, if your strategy is based on just writing articles, there’s an existential crisis at hand.

Understanding the problems your audience has will be crucial. Instead of focusing on keywords or the products people want, we need to focus on the frustrations they have before they start searching.

I think conventional user research – surveys, asking questions – will be more important than building spreadsheets of keywords. Moving away from keywords and understanding human needs will be key.

Search behavior is already shifting. We need to stop thinking about just typing queries into Google.

People are searching on TikTok and Instagram, and even using voice commands with their smart homes. Brand discovery and awareness will play a bigger role, and we’ll need to adapt by creating content that’s useful, relevant, and trustworthy.”

Mark Williams-Cook: Branded Search Is The Gold Standard

Mark’s opinion is that we’re in an odd place and sitting on the fence between two technologies. He thinks that there is a disconnect between user expectations and search engine capabilities.

“The key point here is that with AI models like LLMs and overviews, we’ve introduced a new way and expectation for users.

Now, they can ask tools like ChatGPT a question as if they’re talking to another person and receive a direct answer.

The danger is that most people don’t understand how AI works or realize it can make mistakes.

Google has built trust over 20 years, so people assume its answers are accurate, even though AI Overviews have produced some very incorrect results.

The issue is users aren’t aware of AI’s limitations, so when an Overview gives faulty information, people’s defenses are down. They trust Google and assume AI is inherently ‘clever’ without realizing it can produce biased or inaccurate responses.

There are knowledge spaces, or ‘solved knowledge spaces,’ as Jono Alderson calls them, where information doesn’t change much, like a lasagna recipe. I think AI Overviews are useful in these areas, which might reduce traffic to sites focused on this kind of content. However, it’s honestly a relief to see less repetitive content online.

For industries impacted by AI overviews, it might be time to shift focus rather than trying to fit old practices into the new landscape.

The blended SERPs will focus more on overall presence, not just page optimization. It’s about where and how frequently your brand is mentioned across the web, more like digital PR. This favors brands with a broad digital footprint.

Ultimately, branded search – people searching specifically for your brand – is the gold standard, and I think that’s where AI overviews could push us.”

Dan Taylor: ChatGPT Search Will Lay The Groundwork For Significant Changes

I spoke to Dan a few days after ChatGPT Search launched. Dan conducted some initial research and testing on how the AI search engine handled queries.

He believes that in its current state, ChatGPT Search would not appeal to the mass market as it felt lacking. He thinks it is still raw and rugged and perhaps not quite ready for a broad audience of non-tech users.

But, he does think this could be a big moment similar to the introduction of Ask Jeeves (for those who remember). It pioneered a different approach to search modeling, and ChatGPT Search will be influential.

“ChatGPT Search is very query-dependent. For local search, for instance, it wasn’t a great experience. I noticed that, with niche or specific queries, it had a better logical structure.

For example, in a recent search for sports scores, Google prioritized the dominant, common interpretation over timeliness.

ChatGPT Search, however, better understood the fresh intent of the query. It wasn’t visually polished, but the information was accurate and elaborate.

In terms of SEO, if ChatGPT Search gains traction, SEOs will need to adapt to optimize for this new format. The summaries in AI Overviews are already doing a lot of the work for users, but there’s an open question about accuracy and trustworthiness that’s fundamental to how this will develop.

I think it has the potential to be a pioneering force in AI-powered search. This could be the ‘Ask Jeeves’ moment for AI search, helping to establish the landscape for a new wave of competition.

We’re in a different ecosystem now, and OpenAI is heavily funded. Whether it remains at the forefront, or another big player steps in, ChatGPT Search will at least lay the groundwork for significant changes in search.”

Alli Berry: Combining AI With A Strong Sense Of Brand Will Lead The Future

Alli predominantly works in the finance space, so her experience has not been impacted as much as other verticals. Currently, Google limits AI Overviews in Your Money or Your Life (YMYL) SERPs.

Like many others, she believes that a shift to branding is needed and that smaller companies will need to engage audiences directly, and reduce their reliance on Google.

“I don’t have a strong yes or no opinion on these Overviews; I see them as the next generation of disruption at the top of the SERPs.

Now, it’s on us as practitioners to figure out how to make the most of them. I’ve had great success with featured snippets in the past, so I hope we can replicate that with AI Overviews.

I think the space will have to change. Right now, the financial industry feels very transactional, and there’s not much emphasis on building long-term relationships or communities.

Few finance sites do this well, and it’s a huge opportunity. Smaller companies will need to collect user information, engage audiences directly, and reduce their reliance on Google.

If brands don’t adapt, they’ll fade out. Quick-hit search answers won’t sustain them in the long run. Whether in finance or another industry, brands need to focus on recognition and audience growth.

That requires thoughtfulness and an effort to create something people want to connect with. This change, while challenging, will improve the brands that survive.

We’ve come full circle to classic marketing. Building brand recognition is vital.

Digital marketing went through a phase of undervaluing traditional advertising because it was hard to measure ROI. But now, it’s about creating brand associations, being visible, and providing value to audiences through direct content like newsletters.

Brands that combine AI with a strong sense of brand will lead the future. That combination is critical moving forward. “

Arnout Hellemans: It’s More About Experience Optimization

Arnout thinks we are on the verge of a big shift. Google must reinvent itself, but its focus right now seems to be on competing with Amazon.

There could be a future where Google integrates its accounts so you can make purchases directly within the search interface.

He can see that the younger generations are using TikTok and Snapchat instead of Google. He also thinks that to create demand in search volume, you need to create hype on those platforms.

Arnout is also driven by creating better user experiences and focusing on conversions and not clicks. He believes that we should optimize websites not just for traffic but to help people convert.

“Google had the technology to launch something like ChatGPT before OpenAI, but they didn’t because they knew it would hurt their bottom line. They were forced into it when people flocked to ChatGPT. Now, with so many alternatives, Google has to adapt.

With the launch of ChatGPT Search, how much market share will it take from Google? I think it’ll be significant. Brave, Perplexity, and other engines will nibble at Google’s dominance.

Most of these searches are informational, so initially, it might not cut into ad revenue. But, as users shift from informational searches to comparisons and eventually purchases, the impact will grow.

Google could already provide a similar experience but hesitates because of shareholder value. It’ll be interesting to see the initial market share data.

If they lose a small percentage, it might be manageable, but if they lose 10% or more, they’ll have to act quickly. Ad revenue may still rise in the short term due to higher CPC prices, but [in the] long term, the competition is fierce.

Younger generations are gathering knowledge from TikTok. It’s fascinating. Most of their knowledge comes from there. The biggest spikes in Google Trends now are TikTok trends.

To generate search volume, you need to hype solutions on platforms like YouTube, Instagram, and TikTok. That’s how you create demand.

It’s fascinating to think about the younger generation’s habits. They even use Snapchat over Google Maps now. It’s hard for us to imagine, but that’s their reality.

I think we’re moving towards an age where it’s not about sheer traffic but about delivering a truly optimized experience. The old age of SEO is gone.

It’s more about experience optimization – truly delivering the best experience ever. “

What We Can Takeaway About AI Overviews

Although we have eight different responses to the same question, the common themes and what we can take away from these conversations are to:

  • Leverage your expertise and deep knowledge with your audience.
  • Focus on brand building and building your audience.
  • Build communities around your brand.
  • Create content that solves problems.
  • Embrace TikTok in the user journey to find information.
  • AIO mostly takes away informational queries that don’t hold any conversion value.
  • Focus on conversion and not clicks.

Thank you to all the experts who appeared as guests on IMHO and offered their time and opinions.

More Resources:


Featured Image: Deemerwha Studio/Shutterstock

OpenAI Releases ChatGPT o1, ‘World’s Smartest Language Model” via @sejournal, @martinibuster

Today OpenAI rolled out what Sam Altman says is the world’s smartest language model in the world plus a brand new Pro tier that comes with unlimited usage limits and with a higher level of computing resources.

OpenAI ChatGPT o1 Model

Sam Altman announced on X (formerly Twitter) that their new AI model is now live and available in ChatGPT right now and will be arriving to the API soon.

He tweeted:

“o1, the smartest model in the world. smarter, faster, and more features (eg multimodality) than o1-preview. live in chatgpt now, coming to api soon.

chatgpt pro. $200/month. unlimited usage and even-smarter mode for using o1. more benefits to come!”

Screenshot Of ChatGPT 01 Model Availability

ChatGPT Pro Mode $200/Month

ChatGPT Pro Mode is a new tier that has more “thinking power” than the standard version of o1, which increases it’s reliability. Answers in Pro mode take longer to generate, displaying a progress bar and triggering an in-app notification if the user navigates to a different conversation.

OpenAI describes the new ChatGPT Pro Mode:

“ChatGPT Pro provides access to a version of our most intelligent model that thinks longer for the most reliable responses. In evaluations from external expert testers, o1 pro mode produces more reliably accurate and comprehensive responses, especially in areas like data science, programming, and case law analysis.

Compared to both o1 and o1-preview, o1 pro mode performs better on challenging ML benchmarks across math, science, and coding.”

The new tier is not a price increase from the regular plan, which is called Plus. It’s an entirely new plan called Pro.

OpenAI’s new o1 Pro plan provides unlimited access to its new o1 model, along with o1-mini, GPT-4o, and Advanced Voice. It also includes o1 Pro Mode, which has access to increased computational power to generate more refined and insightful responses to complex queries.

Read more about OpenAI’s new pro plan and O1 model:

Introducing ChatGPT Pro

Featured Image by Shutterstock/One Artist

ChatGPT Search Shows 76.5% Error Rate In Attribution Study via @sejournal, @MattGSouthern

OpenAI’s ChatGPT Search is struggling to accurately cite news publishers, according to a study by Columbia University’s Tow Center for Digital Journalism.

The report found frequent misquotes and incorrect attributions, raising concerns among publishers about brand visibility and control over their content.

Additionally, the findings challenge OpenAI’s commitment to responsible AI development in journalism.

Background On ChatGPT Search

OpenAI launched ChatGPT Search last month, claiming it collaborated extensively with the news industry and incorporated publisher feedback.

This contrasts with the original 2022 rollout of ChatGPT, where publishers discovered their content had been used to train the AI models without notice or consent.

Now, OpenAI allows publishers to specify via the robots.txt file whether they want to be included in ChatGPT Search results.

However, the Tow Center’s findings suggest publishers face the risk of misattribution and misrepresentation regardless of their participation choice.

Accuracy Issues

The Tow Center evaluated ChatGPT Search’s ability to identify sources of quotes from 20 publications.

Key findings include:

  • Of 200 queries, 153 responses were incorrect.
  • The AI rarely acknowledged its mistakes.
  • Phrases like “possibly” were used in only seven responses.

ChatGPT often prioritized pleasing users over accuracy, which could mislead readers and harm publisher reputations.

Additionally, researchers found ChatGPT Search is inconsistent when asked the same question multiple times, likely due to the randomness baked into its language model.

Citing Copied & Syndicated Content

Researchers find ChatGPT Search sometimes cites copied or syndicated articles instead of original sources.

This is likely due to publisher restrictions or system limitations.

For example, when asked for a quote from a New York Times article (currently involved in a lawsuit against OpenAI and blocking its crawlers), ChatGPT linked to an unauthorized version on another site.

Even with MIT Technology Review, which allows OpenAI’s crawlers, the chatbot cited a syndicated copy rather than the original.

The Tow Center found that all publishers risk misrepresentation by ChatGPT Search:

  • Enabling crawlers doesn’t guarantee visibility.
  • Blocking crawlers doesn’t prevent content from showing up.

These issues raise concerns about OpenAI’s content filtering and its approach to journalism, which may push people away from original publishers.

OpenAI’s Response

OpenAI responded to the Tow Center’s findings by stating that it supports publishers through clear attribution and helps users discover content with summaries, quotes, and links.

An OpenAI spokesperson stated:

“We support publishers and creators by helping 250M weekly ChatGPT users discover quality content through summaries, quotes, clear links, and attribution. We’ve collaborated with partners to improve in-line citation accuracy and respect publisher preferences, including enabling how they appear in search by managing OAI-SearchBot in their robots.txt. We’ll keep enhancing search results.”

While the company has worked to improve citation accuracy, OpenAI says it’s difficult to address specific misattribution issues.

OpenAI remains committed to improving its search product.

Looking Ahead

If OpenAI wants to collaborate with the news industry, it should ensure publisher content is represented accurately in ChatGPT Search.

Publishers currently have limited power and are closely watching legal cases against OpenAI. Outcomes could impact content usage rights and give publishers more control.

As generative search products like ChatGPT change how people engage with news, OpenAI must demonstrate a commitment to responsible journalism to earn user trust.


Featured Image: Robert Way/Shutterstock

Coca-Cola’s AI Holiday Campaign Fails To Engage Viewers Emotionally via @sejournal, @gregjarboe

Decision-makers at brands and agencies know that the new AI-generated holiday ads from Coca-Cola have attracted a lot of criticism.

Others have described the three new AI versions of the classic “Holidays Are Coming” campaign as “a soulless and creepy, dystopian nightmare” and “the biggest branding blunder of the year,” with others saying the AI campaign “destroyed the spirit of Christmas” and “earns Coca-Cola a lump of coal.”

Strong words. But has Manuel “Manolo” Arroyo, the executive vice president and global chief marketing officer for the company, just made a career-damaging move?

In testing for festive campaigns globally by DAIVID, none of Coke’s new AI-generated holiday ads made the top 30 most effective holiday campaigns of 2024 against 90 other Christmas ads.

Watch the new AI-generated holiday ads, which were created by three different ad agencies, and form your own opinion.

Secret Santa

Secret Level created “Coca-Cola – Secret Santa (AI-Generated Christmas Ad 2024).”

Holidays Are Coming

Silverside created “Coca Cola – Holidays Are Coming.”

Unexpected Santa

Wildcard created “Coca-Cola – Unexpected Santa (AI-Generated Christmas Ad 2024).”

Holidays Are Coming 2020

While you’re reviewing these new versions, you should also watch the version that was uploaded to Coca-Cola Great Britain & Ireland’s YouTube channel back in 2020.

How Do Coke’s New AI Versions Compare To The Classic 2020 Ad?

What do you notice? What do you wonder?

Attention

All the new AI versions generated above-average attention from the start.

However, the classic version, which starts with a boy ringing a bell, captures more attention than any of the AI versions, which mostly start with shots of snowy landscapes.

People will generally attract more attention than images of trees and lakes.

Prevalence Of Intense Emotions

According to testing by DAIVID, none of the AI ads generate the same levels of intense positive emotions as the 2020 version, and all of them are below the industry average.

The 2020 version generates almost twice as much warmth as the norm, while the AI versions are level or slightly above.

The AI version that generated the most warmth was still 38% less likely to make people feel warmth than the 2020 version.

The AI versions were less relatable and less – for want of a better word – real.

Brand Recall

All of the new AI versions predictably scored above the industry average for correct brand recall.

This is not surprising, considering that people know the ad well, and the brand is present throughout and integral to the storyline (Coke Trucks).

The classic scores higher than the AI versions, though. This, again, is possibly due to the familiarity of the ad, but also the fact the famous “Holidays Are Coming” track kicks in much quicker.

Next Step Intents

One of the emotions that the AI versions consistently scored higher than the 2020 ad for is feelings of craving. All are around two to three times higher than average.

This is probably due to the close-ups of someone opening a cold bottle of Coke, which wasn’t included in the 2020 version.

What Was The Most Effective AI Version?

Ian Forrester of DAIVID reported:

“The AI versions of Coke’s classic ‘Holidays Are Coming’ campaign were strong for attention in the first second and brand recall, but were let down by their evocation of intense positive emotions, which were all below the industry norm.

The difference between the AI and the original was most stark in their evocation of warmth, a mainstay of Christmas advertising. The original evoked intense warmth among 33.0% of viewers, whereas the AI versions were significantly below this.

So, while the AI is producing images which on the face of it seem cute and heart-warming, the human viewer to some degree discerns their synthetic nature, which detracts from their impact.”

How Can Brands Avoid AI Negative Backlash?

After analyzing the data published by DAIVID, I reached out directly and spoke to their Chief Growth Officer, Barney Worfolk-Smith:

GJ: Why does AI have such a negative perception?

BWS: It’s not surprising that the use of generative AI, especially jazzing up familiar Christmas traditions like Coke’s truck, garners some negative opinions.

As the introduction of generative AI into processes is nascent and messy at best, none of us really know exactly how it will play out.

So, some in the advertising community who feel a sense of ominous threat will instantly adopt a negative stance. I don’t blame them, but the reality is, the toothpaste is out of the tube, so we should all have a hand on the wheel of a human-AI hybrid Christmas Coke truck to have a stake in the future.

GJ: Can brands navigate carefully to avoid backlash?

BWS: Generative AI is present – or at least coming down the chimney – in almost all aspects of advertising. It’s actually incumbent upon brands to try bits of it out.

Sure, it’s going to be bumpy, but the backlashes will frequently be confined to the advertising community.

As a result, as long as they’re doing measured introductory human AI experiments and not dismissing the agency of record, I think they’ll avoid a hit on the share price.

GJ: Why was the original video such a classic?

BWS: The original was a glorious confluence: strong, familiar emotions, which Coca-Cola evokes generally, the shared history of Santa and Coca-Cola’s colors, and a palpable, relatable sense of anticipation that even the “Grinchiest” of us feel in the run-up to Christmas.

GJ: Why has AI failed to replicate the success of the first campaign?

BWS: At DAIVID, we understand the importance emotions play in advertising effectiveness – and the AI versions all garnered below-average U.S. positive emotional responses.

Without a doubt, the uncanny valley plays a part here, especially with an advert that is so recognizable to so many of us.

GJ: What must marketers do when using AI in video or images?

BWS: Marketers need to take their eyes off the spreadsheet and on to the creative process.

Of course, AI can drive efficiencies, but it can also open up new avenues of creativity, and that will happen when creatives are empowered to use AI, not be threatened with it.

Embrace AI Cautiously In Holiday Ads

Holiday ads are notoriously tricky to navigate and strike the right sentiment, with the best intention often missing the mark.

Feelings of warmth and nostalgia are at the heart of the festive season. Perhaps AI just can’t replicate the nuance of human emotion – or more likely, humans don’t like the idea of AI trying to replicate that.

Coca-Cola’s new ads emphasizes the challenge for brands to cultivate emotional authenticity when engaging with their audience as AI becomes more integrated into advertising campaigns.

It reminds us to embrace AI cautiously while upholding the human elements that underpin marketing campaigns – holiday ads, in particular.


Methodology

DAIVID used its AI-powered platform that predicts the emotions an ad will generate, and its likely impact on brand and business metrics – enabling advertisers to measure the effectiveness of their ad campaigns at scale.

They tested 90 Christmas ads for 39 different emotions. The strength of emotions people feel is ranked from 1-10, with 8-10 considered “intense.” Data for the chart was compiled at 7:00 AM on November 15, 2024. 


More resources:


Featured Image: Evgeny Karandaev/Shutterstock

GraphRAG Update Improves AI Search Results via @sejournal, @martinibuster

Microsoft announced an update to GraphRAG that improves AI search engines’ ability to provide specific and comprehensive answers while using less resources. This update speeds up LLM processing and increases accuracy.

The Difference Between RAG And GraphRAG

RAG (Retrieval Augmented Generation) combines a large language model (LLM) with a search index (or database) to generate responses to search queries. The search index grounds the language model with fresh and relevant data. This reduces the possibility of AI search engine providing outdated or hallucinated answers.

GraphRAG improves on RAG by using a knowledge graph created from a search index to then generate summaries referred to as community reports.

GraphRAG Uses A Two-Step Process:

Step 1: Indexing Engine
The indexing engine segments the search index into thematic communities formed around related topics. These communities are connected by entities (e.g., people, places, or concepts) and the relationships between them, forming a hierarchical knowledge graph. The LLM then creates a summary for each community, referred to as a Community Report. This is the hierarchical knowledge graph that GraphRAG creates, with each level of the hierarchical structure representing a summarization.

There’s a misconception that GraphRAG uses knowledge graphs. While that’s partially true, it leaves out the most important part: GraphRAG creates knowledge graphs from unstructured data like web pages in the Indexing Engine step. This process of transforming raw data into structured knowledge is what sets GraphRAG apart from RAG, which relies on retrieving and summarizing information without building a hierarchical graph.

Step 2: Query Step
In the second step the GraphRAG uses the knowledge graph it created to provide context to the LLM so that it can more accurately answer a question.

Microsoft explains that Retrieval Augmented Generation (RAG) struggles to retrieve information that’s based on a topic because it’s only looking at semantic relationships.

GraphRAG outperforms RAG by first transforming all documents in its search index into a knowledge graph that hierarchically organizes topics and subtopics (themes) into increasingly specific layers. While RAG relies on semantic relationships to find answers, GraphRAG uses thematic similarity, enabling it to locate answers even when semantically related keywords are absent in the document.

This is how the original GraphRAG announcement explains it:

“Baseline RAG struggles with queries that require aggregation of information across the dataset to compose an answer. Queries such as “What are the top 5 themes in the data?” perform terribly because baseline RAG relies on a vector search of semantically similar text content within the dataset. There is nothing in the query to direct it to the correct information.

However, with GraphRAG we can answer such questions, because the structure of the LLM-generated knowledge graph tells us about the structure (and thus themes) of the dataset as a whole. This allows the private dataset to be organized into meaningful semantic clusters that are pre-summarized. The LLM uses these clusters to summarize these themes when responding to a user query.”

Update To GraphRAG

To recap, GraphRAG creates a knowledge graph from the search index. A “community” refers to a group of related segments or documents clustered based on topical similarity, and a “community report” is the summary generated by the LLM for each community.

The original version of GraphRAG was inefficient because it processed all community reports, including irrelevant lower-level summaries, regardless of their relevance to the search query. Microsoft describes this as a “static” approach since it lacks dynamic filtering.

The updated GraphRAG introduces “dynamic community selection,” which evaluates the relevance of each community report. Irrelevant reports and their sub-communities are removed, improving efficiency and precision by focusing only on relevant information.

Microsoft explains:

“Here, we introduce dynamic community selection to the global search algorithm, which leverages the knowledge graph structure of the indexed dataset. Starting from the root of the knowledge graph, we use an LLM to rate how relevant a community report is in answering the user question. If the report is deemed irrelevant, we simply remove it and its nodes (or sub-communities) from the search process. On the other hand, if the report is deemed relevant, we then traverse down its child nodes and repeat the operation. Finally, only relevant reports are passed to the map-reduce operation to generate the response to the user. “

Takeaways: Results Of Updated GraphRAG

Microsoft tested the new version of GraphRAG and concluded that it resulted in a 77% reduction in computational costs, specifically the token cost when processed by the LLM. Tokens are the basic units of text that are processed by LLMs. The improved GraphRAG is able to use a smaller LLM, further reducing costs without compromising the quality of the results.

The positive impacts on search results quality are:

  • Dynamic search provides responses that are more specific information.
  • Responses makes more references to source material, which improves the credibility of the responses.
  • Results are more comprehensive and specific to the user’s query, which helps to avoid offering too much information.

Dynamic community selection in GraphRAG improves search results quality by generating responses that are more specific, relevant, and supported by source material.

Read Microsoft’s announcement:

GraphRAG: Improving global search via dynamic community selection

Featured Image by Shutterstock/N Universe

Microsoft’s AI SEO Tips: New Guidance For AI Search Optimization via @sejournal, @MattGSouthern

Microsoft has provided guidance on how to optimize content for AI-powered search engines.

This advice is timely now that OpenAI has launched ChatGPT Search, which uses Bing’s search index.

Understanding user intent is everything in this new era of search, Microsoft says:

“In the past, digital marketing strategies often relied heavily on demographic data and broad customer segments. But in this era of generative AI, the focus now shifts from who the customer is to what they are looking for—in real-time.”

Microsoft explains several ways websites can optimize content for AI-powered search.

AI SEO Recommendations

Intent-Based Content

Content should address the underlying purpose of user queries, Microsoft says:

“Focus on the intent behind the search query rather than just the keywords themselves. For example, if based on your keyword research, you find that users are searching for “how to choose eco-friendly coffee makers,” provide detailed, step-by-step guides rather than just general information.”

Natural Language Processing (NLP)

Websites should leverage NLP techniques to align content with how AI systems process and understand language.

Microsoft states:

“Generative engines, such as Bing Generative Search, deliver content to searchers by understanding and generating human language through Natural Language Processing (NLP). By analyzing vast amounts of text data to learn language patterns, context, and semantics, they’re able to provide relevant and accurate responses to user queries.”

Additionally, Microsoft emphasized the following sentence in italics:

“Leveraging these same NLP strategies in creating your content can optimize it to rank higher, increase its relevance, and enhance its authority, ultimately boosting its visibility and effectiveness.”

Strategic Keyword Implementation

To improve your website and landing pages for AI search engines, Microsoft recommends these keyword strategies:

  • Long-tail keywords for specific user interests
  • Conversational phrases matching natural speech patterns
  • Semantic keywords providing contextual relevance
  • Question-based keywords addressing common user queries

Freshness

Microsoft encourages keeping content updated and suggests using the IndexNow protocol to quickly notify search engines about website changes.

This helps maintain search rankings and ensures AI systems have the latest information.

Microsoft states:

“While it can be tempting to set it and forget it, AI systems depend on the latest, freshest information to determine the most relevant content to display to searchers. Regularly updating your content not only helps maintain your rankings but also keeps your audience engaged with current and valuable information. This practice can significantly influence how AI systems perceive and rank your website.”

Why This Matters

ChatGPT Search now uses Bing’s index, making these optimization strategies vital for websites seeking better visibility in AI-powered searches.

While this can help you create more optimized content, Microsoft acknowledges there’s no “secret sauce” for AI search systems.

How To Get Indexed In ChatGPT Search

Refer to our article on ChatGPT search indexing to ensure your content is indexed in ChatGPT’s real-time search engine.

You can also watch the short video I recorded on this topic below:


Featured Image: jomel alos/Shutterstock

ChatGPT Search May Have A Shot At Google via @sejournal, @Kevin_Indig

ChatGPT Search (CGS) is a landmark launch in the shift from traditional to AI Search.

Now, OpenAI competes with Google (Search) heads-on. Note the subtle elbow hit between the lines in the announcement:

Getting useful answers on the web can take a lot of effort. It often requires multiple searches and digging through links to find quality sources and the right information for you.

The positioning is clear: ChatGPT Search is a way to get a straight answer without digging through cluttered search results or browsing websites.

CGS, which is directly integrated with ChatGPT instead of a standalone search engine, decides whether a query benefits from web results or not, and you can rerun queries through other models like o1 preview to compare the answers:

ChatGPT will choose to search the web based on what you ask, or you can manually choose to search by clicking the web search icon.

It keeps the context of your search going in a conversation interface (bolding from me):

Go deeper with follow-up questions, and ChatGPT will consider the full context of your chat to get a better answer for you.

ChatGPT Search’s interface features prominent links to sources (Image Credit: Kevin Indig)

OpenAI has a strategic advantage, as I explained in Search GPT:

The Information reports that OpenAI loses $5 billion a year in expenses. Just capturing 3% of Google’s $175 billion Search business would allow OpenAI to recoup expenses.

OpenAI has a strategic advantage over Google: Search GPT can provide a very different, maybe less noisy, user experience than Google because it’s not reliant on ad revenue. In any decision regarding Search, Google needs to take ads into account.

CGS marks the entry to a new paradigm where traditional search engines like Google or Bing compete with AI chatbots.

They solve the same problems for users as search engines but with lower friction. But it also marks a critical event that should lead you to evaluate your strategy.

Companies face a choice to invest and “be early” to AI Search or ignore the noise and stay the course. What makes this decision hard:

  1. Divided opinions about Chat GPT’s chance to take significant market share from Google.
  2. Rapidly changing mechanisms of AI Search platforms.
  3. Confusion about what to do.

The first search engines didn’t represent the model (Google) that eventually won.

In the same vein, the AI Search experience we’re seeing today might be completely different in a few years. However, there is little doubt that search is fundamentally changing.

As a result, my recommendation is to invest in AI Search. It is not capital-intensive (yet), but the upside to finding a playbook is high.

If CGS grabs significant Google market share, you’re in a good position. If it fails, no harm is done.

Collision Course

Based on recent traffic trends, ChatGPT could catch up to Google in 2 years. (Image Credit: Kevin Indig)

In the chart above, I extrapolated ChatGPT’s and Google’s total traffic over the next two years if the trend from the last six months remains constant.

This chart will probably outrage or scare you, but the chance that events unfold exactly as depicted in this chart is low.

The reason I bring it up here is to consider the fact that many structural changes start slowly based on the saying “first gradually, then suddenly.”

It took Google about three to four years to beat Yahoo, Altavista, and Lycos. Given that new technology gets to critical mass ever faster, I’m not surprised ChatGPT could do it faster (in theory).

ChatGPT’s traffic has already passed the No. 3 search engine, Bing (YouTube is second).

When you look at comments and posts on social media, more and more people report using ChatGPT instead of Google for various purposes, but that could be availability bias.

Image Credit: Kevin Indig

One point a lot of people miss when looking at the traffic comparison between ChatGPT and Bing is that they’re not the same, and yet this is a fair comparison.

ChatGPT is more than a search engine. People use it for all sorts of things. But that’s exactly the point: a search engine that looks like Google never stood a chance to compete with Google or Bing.

CGS is something new, and that’s why it stands a chance. So, when you see chatgpt.com passing bing.com, the critical argument is not that both do different things but that they’re used to accomplish the same goal.

After all, search is just a way to solve problems or achieve goals, not to search for the sake of searching.

To clarify, I don’t think Google or Alphabet as a company is at risk of dying. I do think CGS has a chance to capture significant market share, and too many people underestimate how fast this can go.

Referral Traffic Skyrockets

ChatGPT’s outgoing referral traffic is skyrocketing (Image Credit: Kevin Indig)

AI Search marks a new paradigm where users get a direct answer without having to browse websites. So, how should companies think about pivoting their strategy?

Here’s what I’m telling my clients when they ask me whether they should pivot their SEO roadmap: For now, no. Reserve 10 to 20% of capacity to establish visibility in AI Search and for experimentation.

Look for signal: If you’re hesitant to invest more in AI Search right now, at least monitor traffic to and from ChatGPT. Base your decision on how long ChatGPT can keep its current traffic trend up.

Establishing visibility: This referral dashboard from Flow Agency is great for monitoring referral traffic.

With a few tweaks, you can monitor conversions in GA4 as well. You should also monitor site crawls from LLMs and your performance on Bing.

Then, experiment with content tweaks to improve your AI Search visibility. Keep investing in traditional SEO because it forms the basis of AI Search and answers.

Place a bet: The big question in this is whether you’re willing to take a bet or play it safe.

Being a first-mover to SEO had massive benefits as the incumbents tend to stay incumbents, mainly caused by strong backlink profiles, robust user signals, and brand familiarity.

For now, ChatGPT uses Bing search results to ground and weigh answers, which means sites with strong visibility on Bing also have a high chance of being very visible in CGS.

However, there is a chance that using Search for RAG (grounding) is just a jumping-off point until AI Search platforms have gathered enough of their data (queries and user behavior).

Early in this transition period, not much changes. Content that ranks well in traditional search engines, specifically Bing, gets a higher weighting in CGS, which means traditional SEO has a big impact on visibility in AI Search.

AI Chatbot referral traffic is skyrocketing, and ChatGPT’s new search capability could accelerate that growth even more.

Outgoing referral traffic from chatgpt.com increased massively in August and September, according to Similarweb.

Image Credit: Kevin Indig

Noticeable call-outs:

  • YouTube’s referral traffic increased from .17% in July to 3.9% in September.
  • Bing grew from 0% in April to 1.8% in September.
  • Amazon grew from 0% in July to 1.1% in September.

If referral traffic keeps growing at the same rate, it will get interesting in the next six to 12 months. It’s not just the volume but also the quality of traffic.

People use longer and more complex questions when they engage with AI answers, according to Sundar Pichai. Length is a way to be more specific.

Longer questions allow search engines, LLMs, and marketers to better understand and serve users what they want.

Based on conversations and observations, referral traffic from AI chatbots isn’t consistently higher than search traffic in every case, but in most.

Looking Forward

I’m leaving you with two interesting questions:

1. Is it a coincidence that ChatGPT Search came out three days after Apple Intelligence launched publicly?

Apple launched Apple Intelligence, which uses ChatGPT in certain situations:

Apple is integrating ChatGPT access into experiences within iOS 18, iPadOS 18, and macOS Sequoia, allowing users to access its expertise — as well as its image- and document-understanding capabilities — without needing to jump between tools. Siri can tap into ChatGPT’s expertise when helpful.

Users are asked before any questions are sent to ChatGPT, along with any documents or photos, and Siri then presents the answer directly.

Additionally, ChatGPT will be available in Apple’s systemwide Writing Tools, which help users generate content for anything they are writing about. With Compose, users can also access ChatGPT image tools to generate images in a wide variety of styles to complement what they are writing.

We also know how valuable Google’s exclusive search deal with Apple is.

From Monopoly:

Apple’s impact on Google Search is massive. The court documents reveal that 28% of Google searches (US) come from Safari and make up 56% of search volume. Consider that Apple sees 10 billion searches per week across all of its devices, with 8 billion happening on Safari and 2 billion from Siri and Spotlight.

“Google receives only 7.6% of all queries on Apple devices through user-downloaded Chrome” and “10% of its searches on Apple devices through the Google Search App (GSA).” Google would take a big hit without the exclusive agreement with Apple.

Since Search is part of ChatGPT, any API request could trigger the new Search feature.

As a result, ChatGPT has a direct line to searches and actions on Apple devices whenever Apple Intelligence uses ChatGPT. Is that integration the new version of Google’s deal with Apple?

I speculated that OpenAI could work on a browser in Search GPT:

If the main benefit or Search GPT for OpenAI is a revenue stream and access to more user data, the next logical step for OpenAI is to build a (AI-powered) browser.

Browser data is incredibly valuable for understanding user behavior, personalization and LLM training. Best of all, it’s app-agnostic, so OpenAI could learn from users even when they use Perplexity or Google.

We’ve seen the power of browser data in the Google lawsuit, where it turned out Google relied on Chrome data all along for ranking. The only layer that’s more powerful is the operating system and device layer.

OpenAI seems to be very aware of the importance of being the default when we look at how hard it pushes its Chrome extension, which changes the default browser search engine to ChatGPT.

2. As it’s likely that more users don’t browse the web but get answers from ChatGPT, Gemini, Perplexity, etc. directly, will the open web become a place primarily for bots instead of humans? And how would that change the purpose and look of websites?


1 Introducing ChatGPT search

2 Introducing Apple Intelligence, the personal intelligence system that puts powerful generative models at the core of iPhone, iPad, and Mac


Featured Image: Paulo Bobita/Search Engine Journal

ChatGPT Search Indexing: Essential Steps For Websites via @sejournal, @MattGSouthern

As the availability of ChatGPT Search expands, understanding its indexing mechanics will be vital for digital visibility.

While Bing’s index plays a key role, OpenAI’s system surfaces content using its own crawlers and attribution methods.

Here is a breakdown of the technical requirements for ensuring your website is indexed correctly.

Technical Framework

ChatGPT Search combines Bing’s search index with OpenAI’s proprietary technology.

According to OpenAI’s technical documentation, the platform utilizes a fine-tuned version of GPT-4o, enhanced with synthetic data generation techniques and integration with their o1-preview system.

The platform employs three distinct crawlers, each serving different purposes.

The OAI-SearchBot serves as the primary crawler for search functionality, while ChatGPT-User handles real-time user requests and enables direct interaction with external applications.

The third crawler, GPTBot, manages AI model training and can be blocked without affecting search visibility.

Implementation

Proper indexing begins with robots.txt configuration.

Your website’s robots.txt should specifically allow OAI-SearchBot while maintaining separate permissions for different OpenAI crawlers.

In addition to this basic configuration, websites must ensure proper indexing by Bing and maintain a clear site architecture.

It’s worth noting that allowing OAI-SearchBot doesn’t automatically mean the content will be used for AI training.

It can take approximately 24 hours for OpenAI’s systems to adjust to new crawling directives after a site’s robots.txt update.

Content Attribution

ChatGPT Search includes several key features for content publishers:

  • Source Attribution: All referenced content includes proper citation
  • Source Sidebar: Provides reference links for verification
  • Multiple Citation Opportunities: A single query can generate multiple source citations
  • Locations: Searches for specific locations will return an interactive map, as shown below.
Image Credit: OpenAI

Additional Considerations

Recent testing has revealed several important factors:

  • Content freshness affects visibility
  • Pages behind paywalls can still be cited
  • URLs returning 404 errors may still appear in citations
  • Multiple pages from the same domain can be referenced in a single response

Recommendations

Indexing in ChatGPT requires ongoing attention to technical health, including regular verification of the robots.txt file and crawler access.

Publishers should prioritize maintaining factual accuracy and up-to-date information while implementing a clear content structure.

This ensures that pages remain accessible across traditional search engines and AI-powered platforms, helping websites achieve broader visibility.


Featured Image: designkida/Shutterstock