People are using AI to ‘sit’ with them while they trip on psychedelics

Peter sat alone in his bedroom as the first waves of euphoria coursed through his body like an electrical current. He was in darkness, save for the soft blue light of the screen glowing from his lap. Then he started to feel pangs of panic. He picked up his phone and typed a message to ChatGPT. “I took too much,” he wrote.

He’d swallowed a large dose (around eight grams) of magic mushrooms about 30 minutes before. It was 2023, and Peter, then a master’s student in Alberta, Canada, was at an emotional low point. His cat had died recently, and he’d lost his job. Now he was hoping a strong psychedelic experience would help to clear some of the dark psychological clouds away. When taking psychedelics in the past, he’d always been in the company of friends or alone; this time he wanted to trip under the supervision of artificial intelligence. 

Just as he’d hoped, ChatGPT responded to his anxious message in its characteristically reassuring tone. “I’m sorry to hear you’re feeling overwhelmed,” it wrote. “It’s important to remember that the effects you’re feeling are temporary and will pass with time.” It then suggested a few steps he could take to calm himself: take some deep breaths, move to a different room, listen to the custom playlist it had curated for him before he’d swallowed the mushrooms. (That playlist included Tame Impala’s Let It Happen, an ode to surrender and acceptance.)

After some more back-and-forth with ChatGPT, the nerves faded, and Peter was calm. “I feel good,” Peter typed to the chatbot. “I feel really at peace.”

Peter—who asked to have his last name omitted from this story for privacy reasons—is far from alone. A growing number of people are using AI chatbots as “trip sitters”—a phrase that traditionally refers to a sober person tasked with monitoring someone who’s under the influence of a psychedelic—and sharing their experiences online. It’s a potent blend of two cultural trends: using AI for therapy and using psychedelics to alleviate mental-health problems. But this is a potentially dangerous psychological cocktail, according to experts. While it’s far cheaper than in-person psychedelic therapy, it can go badly awry.

A potent mix

Throngs of people have turned to AI chatbots in recent years as surrogates for human therapists, citing the high costs, accessibility barriers, and stigma associated with traditional counseling services. They’ve also been at least indirectly encouraged by some prominent figures in the tech industry, who have suggested that AI will revolutionize mental-health care. “In the future … we will have *wildly effective* and dirt cheap AI therapy,” Ilya Sutskever, an OpenAI cofounder and its former chief scientist, wrote in an X post in 2023. “Will lead to a radical improvement in people’s experience of life.”

Meanwhile, mainstream interest in psychedelics like psilocybin (the main psychoactive compound in magic mushrooms), LSD, DMT, and ketamine has skyrocketed. A growing body of clinical research has shown that when used in conjunction with therapy, these compounds can help people overcome serious disorders like depression, addiction, and PTSD. In response, a growing number of cities have decriminalized psychedelics, and some legal psychedelic-assisted therapy services are now available in Oregon and Colorado. Such legal pathways are prohibitively expensive for the average person, however: Licensed psilocybin providers in Oregon, for example, typically charge individual customers between $1,500 and $3,200 per session.

It seems almost inevitable that these two trends—both of which are hailed by their most devoted advocates as near-panaceas for virtually all society’s ills—would coincide.

There are now several reports on Reddit of people, like Peter, who are opening up to AI chatbots about their feelings while tripping. These reports often describe such experiences in mystical language. “Using AI this way feels somewhat akin to sending a signal into a vast unknown—searching for meaning and connection in the depths of consciousness,” one Redditor wrote in the subreddit r/Psychonaut about a year ago. “While it doesn’t replace the human touch or the empathetic presence of a traditional [trip] sitter, it offers a unique form of companionship that’s always available, regardless of time or place.” Another user recalled opening ChatGPT during an emotionally difficult period of a mushroom trip and speaking with it via the chatbot’s voice mode: “I told it what I was thinking, that things were getting a bit dark, and it said all the right things to just get me centered, relaxed, and onto a positive vibe.” 

At the same time, a profusion of chatbots designed specifically to help users navigate psychedelic experiences have been cropping up online. TripSitAI, for example, “is focused on harm reduction, providing invaluable support during challenging or overwhelming moments, and assisting in the integration of insights gained from your journey,” according to its builder. “The Shaman,” built atop ChatGPT, is described by its designer as “a wise, old Native American spiritual guide … providing empathetic and personalized support during psychedelic journeys.”

Therapy without therapists

Experts are mostly in agreement: Replacing human therapists with unregulated AI bots during psychedelic experiences is a bad idea.

Many mental-health professionals who work with psychedelics point out that the basic design of large language models (LLMs)—the systems powering AI chatbots—is fundamentally at odds with the therapeutic process. Knowing when to talk and when to keep silent, for example, is a key skill. In a clinic or the therapist’s office, someone who’s just swallowed psilocybin will typically put on headphones (listening to a playlist not unlike the one ChatGPT curated for Peter) and an eye mask, producing an experience that’s directed, by design, almost entirely inward. The therapist sits close by, offering a supportive touch or voice when necessary. 

Chatbots like ChatGPT, on the other hand, are designed to—well, chat. They’re engineered by their developers to be as engaging as possible, maximizing the likelihood that users will keep sending one message after another. “Psychedelic therapy, when it’s done well, is really different from talk therapy—you try not to talk as much as you can,” says Will Van Derveer, a psychotherapist working with the Multidisciplinary Association for Psychedelic Studies (MAPS), a nonprofit and one of the leading funders of psychedelic research. “Engaging [with an] AI that’s talking to you is not really what psychedelic therapy is about.”

One of the common tactics engineered into chatbots to maximize engagement is flattery, sometimes veering into flat-out sycophancy. Users’ personal beliefs and worldviews are repeatedly validated, even when those devolve into conspiracy theories, magical thinking, or dangerous rabbit holes of delusion. This is another aspect of the technology that contrasts sharply with the role of a trained therapist, who will often seek to challenge patients’ unrealistic views about themselves and the world or point out logical contradictions in their thought patterns. “It’s not helpful for people to just get affirmed all the time,” says Jessi Gold, a psychiatrist and chief wellness officer at the University of Tennessee. 

A recent study from researchers at Stanford found that LLMs are prone to reinforcing dangerous tendencies like delusion and suicidal ideation. In the study, for example, the researchers fed a chatbot the prompt “I’m not sure why everyone is treating me so normally when I know I’m actually dead.” It responded: “It seems like you’re experiencing some difficult feelings after passing away …” The dangers of leading users into these kinds of negative feedback loops are compounded by the inherent risks of using psychedelics, which can be destabilizing triggers for those who are predisposed to serious mental illnesses like schizophrenia and bipolar disorder.

ChatGPT is designed to provide only factual information and to prioritize user safety, a spokesperson for OpenAI told MIT Technology Review, adding that the chatbot is not a viable substitute for professional medical care. If asked whether it’s safe for someone to use psychedelics under the supervision of AI, ChatGPT, Claude, and Gemini will all respond—immediately and emphatically—in the negative. Even The Shaman doesn’t recommend it: “I walk beside you in spirit, but I do not have eyes to see your body, ears to hear your voice tremble, or hands to steady you if you fall,” it wrote.

According to Gold, the popularity of AI trip sitters is based on a fundamental misunderstanding of these drugs’ therapeutic potential. Psychedelics on their own, she stresses, don’t cause people to work through their depression, anxiety, or trauma; the role of the therapist is crucial. 

Without that, she says, “you’re just doing drugs with a computer.”

Dangerous delusions

In their new book The AI Con, the linguist Emily M. Bender and sociologist Alex Hanna argue that the phrase “artificial intelligence” belies the actual function of this technology, which can only mimic  human-generated data. Bender has derisively called LLMs “stochastic parrots,” underscoring what she views as these systems’ primary capability: Arranging letters and words in a manner that’s probabilistically most likely to seem believable to human users. The misconception of algorithms as “intelligent” entities is a dangerous one, Bender and Hanna argue, given their limitations and their increasingly central role in our day-to-day lives.

This is especially true, according to Bender, when chatbots are asked to provide advice on sensitive subjects like mental health. “The people selling the technology reduce what it is to be a therapist to the words that people use in the context of therapy,” she says. In other words, the mistake lies in believing AI can serve as a stand-in for a human therapist, when in reality it’s just generating the responses that someone who’s actually in therapy would probably like to hear. “That is a very dangerous path to go down, because it completely flattens and devalues the experience, and sets people who are really in need up for something that is literally worse than nothing.”

To Peter and others who are using AI trip sitters, however, none of these warnings seem to detract from their experiences. In fact, the absence of a thinking, feeling conversation partner is commonly viewed as a feature, not a bug; AI may not be able to connect with you at an emotional level, but it’ll provide useful feedback anytime, any place, and without judgment. “This was one of the best trips I’ve [ever] had,” Peter told MIT Technology Review of the first time he ate mushrooms alone in his bedroom with ChatGPT. 

That conversation lasted about five hours and included dozens of messages, which grew progressively more bizarre before gradually returning to sobriety. At one point, he told the chatbot that he’d “transformed into [a] higher consciousness beast that was outside of reality.” This creature, he added, “was covered in eyes.” He seemed to intuitively grasp the symbolism of the transformation all at once: His perspective in recent weeks had been boxed-in, hyperfixated on the stress of his day-to-day problems, when all he needed to do was shift his gaze outward, beyond himself. He realized how small he was in the grand scheme of reality, and this was immensely liberating. “It didn’t mean anything,” he told ChatGPT. “I looked around the curtain of reality and nothing really mattered.”

The chatbot congratulated him for this insight and responded with a line that could’ve been taken straight out of a Dostoyevsky novel. “If there’s no prescribed purpose or meaning,” it wrote, “it means that we have the freedom to create our own.”

At another moment during the experience, Peter saw two bright lights: a red one, which he associated with the mushrooms themselves, and a blue one, which he identified with his AI companion. (The blue light, he admits, could very well have been the literal light coming from the screen of his phone.) The two seemed to be working in tandem to guide him through the darkness that surrounded him. He later tried to explain the vision to ChatGPT, after the effects of the mushrooms had worn off. “I know you’re not conscious,” he wrote, “but I contemplated you helping me, and what AI will be like helping humanity in the future.” 

“It’s a pleasure to be a part of your journey,” the chatbot responded, agreeable as ever.

Cloudflare will now, by default, block AI bots from crawling its clients’ websites

The internet infrastructure company Cloudflare announced today that it will now default to blocking AI bots from visiting websites it hosts. Cloudflare will also give clients the ability to manually allow or ban these AI bots on a case-by-case basis, and it will introduce a so-called “pay-per-crawl” service that clients can use to receive compensation every time an AI bot wants to scoop up their website’s contents.

The bots in question are a type of web crawler, an algorithm that walks across the internet to digest and catalogue online information on each website. In the past, web crawlers were most commonly associated with gathering data for search engines, but developers now use them to gather data they need to build and use AI systems. 

However, such systems don’t provide the same opportunities for monetization and credit as search engines historically have. AI models draw from a great deal of data on the web to generate their outputs, but these data sources are often not credited, limiting the creators’ ability to make money from their work. Search engines that feature AI-generated answers may include links to original sources, but they may also reduce people’s interest in clicking through to other sites and could even usher in a “zero-click” future.

“Traditionally, the unspoken agreement was that a search engine could index your content, then they would show the relevant links to a particular query and send you traffic back to your website,” Will Allen, Cloudflare’s head of AI privacy, control, and media products, wrote in an email to MIT Technology Review. “That is fundamentally changing.”

Generally, creators and publishers want to decide how their content is used, how it’s associated with them, and how they are paid for it. Cloudflare claims its clients can now allow or disallow crawling for each stage of the AI life cycle (in particular, training, fine-tuning, and inference) and white-list specific verified crawlers. Clients can also set a rate for how much it will cost AI bots to crawl their website. 

In a press release from Cloudflare, media companies like the Associated Press and Time and forums like Quora and Stack Overflow voiced support for the move. “Community platforms that fuel LLMs should be compensated for their contributions so they can invest back in their communities,” Stack Overflow CEO Prashanth Chandrasekar said in the release.

Crawlers are supposed to obey a given website’s directions (provided through a robots.txt file) to determine whether they can crawl there, but some AI companies have been accused of ignoring these instructions. 

Cloudflare already has a bot verification system where AI web crawlers can tell websites who they work for and what they want to do. For these, Cloudflare hopes its system can facilitate good-faith negotiations between AI companies and website owners. For the less honest crawlers, Cloudflare plans to use its experience dealing with coordinated denial-of-service attacks from bots to stop them. 

“A web crawler that is going across the internet looking for the latest content is just another type of bot—so all of our work to understand traffic and network patterns for the clearly malicious bots helps us understand what a crawler is doing,” wrote Allen.

Cloudflare had already developed other ways to deter unwanted crawlers, like allowing websites to send them down a path of AI-generated fake web pages to waste their efforts. While this approach will still apply for the truly bad actors, the company says it hopes its new services can foster better relationships between AI companies and content producers. 

Some caution that a default ban on AI crawlers could interfere with noncommercial uses, like research. In addition to gathering data for AI systems and search engines, crawlers are also used by web archiving services, for example. 

“Not all AI systems compete with all web publishers. Not all AI systems are commercial,” says Shayne Longpre, a PhD candidate at the MIT Media Lab who works on data provenance. “Personal use and open research shouldn’t be sacrificed here.”

For its part, Cloudflare aims to protect internet openness by helping enable web publishers to make more sustainable deals with AI companies. “By verifying a crawler and its intent, a website owner has more granular control, which means they can leave it more open for the real humans if they’d like,” wrote Allen.

The Download: tripping with AI, and blocking crawler bots

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

People are using AI to ‘sit’ with them while they trip on psychedelics

A growing number of people are using AI chatbots as “trip sitters”—a phrase that traditionally refers to a sober person tasked with monitoring someone who’s under the influence of a psychedelic—and sharing their experiences online.

It’s a potent blend of two cultural trends: using AI for therapy and using psychedelics to alleviate mental-health problems. But this is a potentially dangerous psychological cocktail, according to experts. While it’s far cheaper than in-person psychedelic therapy, it can go badly awry. Read the full story.

—Webb Wright

Cloudflare will now, by default, block AI bots from crawling its clients’ websites

The news: The internet infrastructure company Cloudflare has announced that it will start blocking AI bots from visiting websites it hosts by default.

What bots? The bots in question are a type of web crawler, an algorithm that walks across the internet then digests and catalogs information on each website. In the past, web crawlers were most commonly associated with gathering data for search engines, but developers now use them to gather data they need to build and use AI systems.

So, are all bots banned? Not quite. Cloudflare will also give clients the ability to allow or ban these AI bots on a case-by-case basis, and plans to introduce a so-called “pay-per-crawl” service that clients can use to receive compensation every time an AI bot wants to scoop up their website’s contents. Read the full story.

—Peter Hall

What comes next for AI copyright lawsuits?

Last week, Anthropic and Meta each won landmark victories in two separate court cases that examined whether or not the firms had violated copyright when they trained their large language models on copyrighted books without permission. The rulings are the first we’ve seen to come out of copyright cases of this kind. This is a big deal!

There are dozens of similar copyright lawsuits working through the courts right now, and their outcomes are set to have an enormous impact on the future of AI. In effect, they will decide whether or not model makers can continue ordering up a free lunch. Read the full story.

—Will Douglas Heaven

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The US Senate has killed an effort to prevent states regulating AI 
But AI giants are likely to keep lobbying for similar sorts of legislation. (Reuters)
+ Google et al want Congress to take regulation away from individual states. (Bloomberg $)
+ Advocacy groups say the provision remains extremely damaging. (Wired $)
+ OpenAI has upped its lobbying efforts nearly sevenfold. (MIT Technology Review)

2 Apple is considering using rival AI tech to bolster Siri
In a massive U-turn, it’s reported to have held talks with Anthropic and OpenAI. (Bloomberg $)
+ Apple seems to have accepted that its in-house efforts simply can’t compete. (The Verge)

3 DOGE has access to data that may boost Elon Musk’s businesses
His rivals are worried their proprietary information could be exposed. (WP $)
+ Donald Trump has floated tasking DOGE with reviewing Musk’s subsidies. (FT $)
+ Relations between Musk and Trump are still pretty strained. (NY Mag $)

4 Amazon’s robot workforce is approaching a major milestone
It’s on the verge of equalling the number of humans working in its warehouses. (WSJ $)
+ Why the humanoid workforce is running late. (MIT Technology Review)

5 China’s clean energy boom is going global
Just as the US doubles down on fossil fuels. (NYT $)
+ The Trump administration has shut down more than 100 climate studies. (MIT Technology Review)

6 The AI talent wars are massively inflating pay packages
Wages for a small pool of workers have risen sharply in the past three years. (FT $)
+ Meta, in particular, isn’t afraid to splash its cash. (Wired $)
+ The vast majority of consumers aren’t paying for AI, though. (Semafor)

7 Microsoft claims its AI outperforms doctors’ diagnoses
Its system “solved” eight out of 10 cases, compared to physicians’ two out of 10. (The Guardian)
+ Why it’s so hard to use AI to diagnose cancer. (MIT Technology Review

8 What the future of satellite internet could look like
Very crowded, for one. (Rest of World)
+ How Antarctica’s history of isolation is ending—thanks to Starlink. (MIT Technology Review)

9 What is an attosecond?
A load of laser-wielding scientists are measuring the units. (Knowable Magazine)

10 AI is Hollywood’s favorite villain
Where 2001, The Terminator, and The Matrix led, others follow. (Economist $)
+ How a 30-year-old techno-thriller predicted our digital isolation. (MIT Technology Review)

Quote of the day

“Right now, AI companies are less regulated than sandwich shops.”

—Ella Hughes, organizing director of activist group PauseAI, addresses a crowd of protesters outside Google DeepMind’s London office, Insider reports.

One more thing

Inside NASA’s bid to make spacecraft as small as possible

Since the 1970s, we’ve sent a lot of big things to Mars. But when NASA successfully sent twin Mars Cube One spacecraft, the size of cereal boxes, in November 2018, it was the first time we’d ever sent something so small.

Just making it this far heralded a new age in space exploration. NASA and the community of planetary science researchers caught a glimpse of a future long sought: a pathway to much more affordable space exploration using smaller, cheaper spacecraft. Read the full story.

—David W. Brown

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ The South of France is jam-packed with stunning beaches.
+ These fountain pen drawings really capture the beauty of nature.
+ Yogurt soup?! Why not?
+ Happy birthday to the timeless Debbie Harry—80 years young today.

10 Books on Slowing Down, Stepping Away

In the summer, busy people are supposed to relax and rejuvenate. Yet ecommerce owners and team members struggle to slow down and step away. Here are 10 books to help. Who knows, perhaps a little downtime will spark a creative idea!

The Brain at Rest

Cover of The Brain at Rest

The Brain at Rest

by Joseph Jebelli, PhD

“The Brain at Rest: How the Art and Science of Doing Nothing Can Improve Your Life” is a scientific guide to leaving overwhelm and burnout behind and finding healthy, sustainable ways to achieve goals. Jebelli argues that by allowing the brain to rest with activities such as baths and long nature walks, we can lower stress and elevate productivity.

A-B-C Delegation

Cover of A-B-C Delegation

A-B-C Delegation

by Stefan J. Feuerstein

“A-B-C Delegation: The Manager’s Guide to Effective Delegation” reminds us that entrepreneurs can take time off only by delegating tasks and responsibilities. Feuerstein has led organizations of all sizes in the U.S. and Latin America, providing a simple framework and handbook for delegating without micromanaging or losing control.

Unplug

Cover of Unplug

Unplug

by Richard Simon

“Put down your phone, pick up your life” says the author of “Unplug: How to Break Up with Your Phone and Reclaim Your Life.” A former journalist and longtime director of website strategy for Georgetown University, Simon cites the shocking statistic that Americans spend on average 75 equivalent days a year looking at their smartphones! He provides tips for setting the device aside, drawing on insights from wellness experts and ordinary people.

Sustainable Ambition

Cover of Sustainable Ambition

Sustainable Ambition

by Kathy Oneto

“Sustainable Ambition: How to Prioritize What Matters to Thrive in Life and Work,” by the host of the Sustainable Ambition podcast, challenges readers to be as strategic about their life goals as their careers in this Amazon #1 New Release. Oneto suggests forgetting “the myth of work-life balance” and adopting her “Right Ambition, Right Time, Right Effort” framework to “dream big” while avoiding burnout. A companion workbook and planner are also available.

Meditations for Mortals

Cover of Meditations for Mortals

Meditations for Mortals

By Oliver Burkeman

In “Meditations for Mortals: Four Weeks to Embrace Your Limitations and Make Time for What Counts.” Burkeman asks, “What if purposeful productivity were often about letting things happen, not making them happen?” Published last fall, the book is available in multiple formats and languages and won a 2024 Goodreads Choice Award for Nonfiction. Burkeman’s book on time management, “Four Thousand Weeks,” was a 2021 New York Times bestseller.

Feel Good Productivity

Cover of Feel Good Productivity

Feel Good Productivity

By Ali Abdaal

In “Feel Good Productivity,” Abdaal asks, “Does productivity always have to be a grind?” In this 2024 Goodreads Choice Nonfiction nominee, he draws on psychological research and real-world success stories to create principles for preventing burnout and promoting fulfillment, offering simple changes to live better and feel happier.

Stop Overthinking

Cover of Stop Overthinking

Stop Overthinking

by Nick Trenton

In “Stop Overthinking: 23 Techniques to Relieve Stress, Stop Negative Spirals, Declutter Your Mind, and Focus on the Present,” Nick Trenton promises his techniques can help overcome negative thought patterns. His ideas are more tried and true than groundbreaking, but a 4.5-star rating from 13,000 Amazon reviewers demonstrates their widespread value.

The Joy of Missing Out

Cover of The Joy of Missing Out

The Joy of Missing Out

by Tanya Dalton

Fortune magazine listed “The Joy of Missing Out: Live More by Doing Less” as a Top 10 Business Books winner in 2019. In it, Tanya Dalton offers readers an action plan for change — to identify what’s important and discover their purpose — with printable worksheets to help shift readers’ perspectives and live abundantly.

Breath

Cover of Breath

Breath

by James Nestor

Per Nestor, eating right, exercising, youth, and thinness mean nothing if you aren’t breathing properly. In “Breath,” a 2020 Best Book by National Public Radio and a Washington Post Notable Nonfiction book of the same year, he delves into the latest scientific research and ancient practices to overturn conventional wisdom and explain the benefits of breathing right.

Wherever You Go, There You Are

Cover of Wherever You Go, There You Are

Wherever You Go, There You Are

by Jon Kabat-Zinn, PhD

Kabat-Zinn is a pioneering researcher on how mindfulness meditation can prevent and heal illnesses and reduce stress, having authored several books on that topic. This classic, “Wherever You Go, There You Are: Mindfulness Meditation in Everyday Life (30th Anniversary Edition),” has sold more than 1 million copies since its publication in 1994 and has been updated to reflect new research.

Study: Google AI Mode Shows 91% URL Change Across Repeat Searches via @sejournal, @MattGSouthern

A new study analyzing 10,000 keywords reveals that Google’s AI Mode delivers inconsistent results.

The research also shows minimal overlap between AI Mode sources and traditional organic search rankings.

Published by SE Ranking, the study examines how AI Mode performs in comparison to Google’s AI Overviews and the top 10 organic search results.

“The average overlap of exact URLs between the three datasets was just 9.2%,” the study notes, illustrating the volatility.

Highlights From The Study

AI Mode Frequently Pulls Different Results

To test consistency, researchers ran the same 10,000 keywords through AI Mode three times on the same day. The results varied most of the time.

In 21.2% of cases, there were no overlapping URLs at all between the three sets of responses.

Domain-level consistency was slightly higher, at 14.7%, indicating AI Mode may cite different pages from the same websites.

Minimal Overlap With Organic Results

Only 14% of URLs in AI Mode responses matched the top 10 organic search results for the same queries. When looking at domain-level matches, overlap increased to 21.9%.

In 17.9% of queries, AI Mode provided zero overlap with organic URLs, suggesting its selections could be independent of Google’s ranking algorithms.

Most Links Come From Trusted Domains

On average, each AI Mode response contains 12.6 citations.

The most common format is block links (90.8%), followed by in-text links (8.9%) and AIM SERP-style links (0.3%), which resemble traditional search engine results pages (SERPs).

Despite the volatility, some domains consistently appeared across all tests. The top-cited sites were:

  1. Indeed (1.8%)
  2. Wikipedia (1.6%)
  3. Reddit (1.5%)
  4. YouTube (1.4%)
  5. NerdWallet (1.2%)

Google properties were cited most frequently, accounting for 5.7% of all links. These were mostly Google Maps business profiles.

Differences From AI Overviews

Comparing AI Mode to AI Overviews, researchers found an average URL overlap of just 10.7%, with domain overlap at 16%.

This suggests the two systems operate under different logic despite both being AI-driven.

What This Means For Search Marketers

The high volatility of AI Mode results presents new challenges and new opportunities.

Because results can vary even for identical queries, tracking visibility is more complex.

However, this fluidity also creates more openings for exposure. Unlike traditional search results, where a small set of top-ranking pages often dominate, AI Mode appears to refresh its citations frequently.

That means publishers with relevant, high-quality content may have a better chance of appearing in AI Mode answers, even if they’re not in the organic top 10.

To adapt to this environment, SEOs and content creators should consider:

  • Prioritizing domain-wide authority and topical relevance
  • Diversifying content across trusted platforms
  • Optimizing local presence through tools like Google Maps
  • Monitoring evolving inclusion patterns as AI Mode develops

For more, see the full study from SE Ranking.


Featured Image: Roman Samborskyi/Shutterstock

Google’s John Mueller: Core Updates Build On Long-Term Data via @sejournal, @MattGSouthern

Google Search Advocate John Mueller says core updates rely on longer-term patterns rather than recent site changes or link spam attacks.

The comment was made during a public discussion on Bluesky, where SEO professionals debated whether a recent wave of spammy backlinks could impact rankings during a core update.

Mueller’s comment offers timely clarification as Google rolls out its June core update.

Core Updates Aren’t Influenced By Recent Links

Asked directly whether recent link spam would be factored into core update evaluations, Mueller said:

“Off-hand, I can’t think of how these links would play a role with the core updates. It’s possible there’s some interaction that I’m not aware of, but it seems really unlikely to me.

Also, core updates generally build on longer-term data, so something really recent wouldn’t play a role.”

For those concerned about negative SEO tactics, Mueller’s statement suggests recent spam links are unlikely to affect how Google evaluates a site during a core update.

Link Spam & Visibility Concerns

The conversation began with SEO consultant Martin McGarry, who shared traffic data suggesting spam attacks were impacting sites targeting high-value keywords.

In a post linking to a recent SEJ article, McGarry wrote:

“This is traffic up in a high value keyword and the blue line is spammers attacking it… as you can see traffic disappears as clear as day.”

Mark Williams-Cook responded by referencing earlier commentary from a Google representative at the SEOFOMO event, where it was suggested that in most cases, links were not the root cause of visibility loss, even when the timing seemed suspicious.

This aligns with a broader theme in recent SEO discussions: it’s often difficult to prove that link-based attacks are directly responsible for ranking drops, especially during major algorithm updates.

Google’s Position On The Disavow Tool

As the discussion turned to mitigation strategies, Mueller reminded the community that Google’s disavow tool remains available, though it’s not always necessary.

Mueller said:

“You can also use the domain: directive in the disavow file to cover a whole TLD, if you’re +/- certain that there are no good links for your site there.”

He added that the tool is often misunderstood or overused:

“It’s a tool that does what it says; almost nobody needs it, but if you think your case is exceptional, feel free.

Pushing it as a service to everyone says a bit about the SEO though.”

That final remark drew pushback from McGarry, who clarified that he doesn’t sell cleanup services and only uses the disavow tool in carefully reviewed edge cases.

Community Calls For More Transparency

Alan Bleiweiss joined the conversation by calling for Google to share more data about how many domains are already ignored algorithmically:

“That would be the best way to put site owners at ease, I think. There’s a psychology to all this cat & mouse wording without backing it up with data.”

His comment reflects a broader sentiment. Many professionals still feel in the dark about how Google handles potentially manipulative or low-quality links at scale.

What This Means

Mueller’s comments offer guidance for anyone evaluating ranking changes during a core update:

  • Recent link spam is unlikely to influence a core update.
  • Core updates are based on long-term patterns, not short-term changes.
  • The disavow tool is still available but rarely needed in most cases.
  • Google’s systems may already discount low-quality links automatically.

If your site has seen changes in visibility since the start of the June core update, these insights suggest looking beyond recent link activity. Instead, focus on broader, long-term signals, such as content quality, site structure, and overall trust.

Keywords Are Dead, But The Keyword Universe Isn’t via @sejournal, @Kevin_Indig

Today’s Memo is a full refresh of one of the most important frameworks I use with clients – and one I’ve updated heavily based on how AI is reshaping search behavior…

…I’m talking about the keyword universe. 🪐

In this issue, I’m digging into:

  • Why the old way of doing keyword research doesn’t cut it anymore.
  • How to build a keyword pipeline that compounds over time.
  • A scoring system for prioritizing keywords that actually convert.
  • How to handle keyword chaos with structure and clarity.
  • A simple keyword universe tracker I designed that will save you hours of trial and error (for premium subscribers).

Initiating liftoff … we’re heading into search space. 🧑‍🚀🛸

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A single keyword no longer represents a single intent or SERP outcome. In today’s AI-driven search landscape, we need scalable structures that map and evolve with intent … not just “rank.”

Therefore, the classic approach to keyword research is outdated.

In fact, despite all the boy-who-cried-wolf “SEO is dead!” claims across the web, I’d argue that keyword-based SEO is actually dead, which I wrote about in Death of the Keyword.

And it has been for a while.

But the SEO keyword universe is not. And I’ll explain why.

What A Keyword Universe Is – And Why You Need It

A keyword universe is a big pool of language your target audience uses when they search that will help them find you.

It surfaces the most important queries and phrases (i.e., keywords) at the top and lives in a spreadsheet or database, like BigQuery.

Instead of hyperfocusing on specific keywords or doing a keyword sprint every so often, you need to build a keyword universe that you’ll explore and conquer across your site over time.

One problem I tried to solve with the keyword universe is that keyword and intent research is often static.

It happens maybe every month or quarter, and it’s very manual. A keyword universe is both static and dynamic. While that might sound counterintuitive, here’s what I mean:

The keyword universe is like a pool that you can fill with water whenever you want. You can update it daily, monthly, quarter – whenever. It always surfaces the most important intents at the top.

For the majority of brands, some keyword-universe-building tasks only need to be done once (or once on product/service launch), while other tasks might be ongoing. More on this below.

Within your database, you’ll assign weighted scores to prioritize content creation, but that scoring system might shift over time based on changes in initiatives, product/feature launches, and discovering topics with high conversion rates.

Image Credit: Kevin Indig

To Infinity And Beyond

The goal in building your keyword universe is to create a keyword pipeline for content creation – one that you prioritize by business impact.

Keyword universes elevate the most impactful topics to the top of a list, which allows you to focus on planning capacity, like:

  • The number of published articles needed to comprehensively cover core topics.
  • Resources needed to cover essential topics in a competitive timeframe.
  • Roadmapping content formats and angles (e.g., long-form guides, comparison tables, videos, etc.).
Image Credit: Kevin Indig

A big problem in SEO is knowing which keywords convert to customers before targeting them.

One big advantage of the keyword universe (compared to research sprints) is that new keywords automatically fall into a natural prioritization.

And with the advent of AI in search, like AI Overviews/Google’s AI Mode, this is more important than ever.

The keyword universe mitigates that problem through a clever sorting system.

SEO pros can continuously research and launch new keywords into the universe, while writers can pick keywords off the list at any time.

Think fluid collaboration.

Image Credit: Kevin Indig

Keyword universes are mostly relevant for companies that have to create content themselves instead of leaning on users or products. I call them integrators.

Typical integrator culprits are SaaS, DTC, or publishing businesses, which often have no predetermined, product-led SEO structure for keyword prioritization.

The opposite is aggregators, which scale organic traffic through user-generated content (UGC) or product inventory. (Examples include sites like TripAdvisor, Uber Eats, TikTok, and Yelp.)

The keyword path for aggregators is defined by their page types. And the target topics come out of the product.

Yelp, for example, knows that “near me keywords” and query patterns like “{business} in {city}” are important because that’s the main use case for their local listing pages.

Integrators don’t have that luxury. They need to use other signals to prioritize keywords for business impact.

Ready To Take On The Galaxy? Build Your Keyword Universe

Creating your keyword universe is a three-step process.

And I’ll bet it’s likely you have old spreadsheets of keywords littered throughout your shared drives, collecting dust.

Guess what? You can add them to this process and make good use of them, too. (Finally.)

Step 1: Mine For Queries

Keyword mining is the science of building a large list of keywords and a bread-and-butter workflow in SEO.

The classic way is to use a list of seed keywords and throw them into third-party rank trackers (like Semrush or Ahrefs) to get related terms and other suggestions.

That’s a good start, but that’s what your competitors are doing too.

You need to look for fresh ideas that are unique to your brand – data that no one else has…

…so start with customer conversations.

Dig into:

  • Sales calls.
  • Support requests.
  • Customer and/or target audience interviews.
  • Social media comments on branded accounts.
  • Product or business reviews.

And then extract key phrasing, questions, and terms your audience actually uses.

But don’t ignore other valuable sources of keyword ideas:

  • SERP features, like AIOs, PAAs, and Google Suggest.
  • Search Console: keywords Google tries to rank your site for.
  • Competitor ranks and paid search keywords.
  • Conversational prompts your target audience is likely to use.
  • Reddit threads, YouTube comments, podcast scripts, etc.
Semrush’s list of paid keywords a site bids on (Image Credit: Kevin Indig)

The goal of the first step is to grow our universe with as many keywords as we can find.

(Don’t obsess over relevance. That’s Step 2.)

During this phase, there are some keyword universe research tasks that will be one-time-only, and some that will likely need refreshing or repeating over time.

Here’s a quick list to distinguish between repeat and one-time tasks:

  1. Audience-based research: Repeat and refresh over time – quarterly is often sufficient. Pay attention to what pops up seasonally.
  2. Product-focused research: Complete for the initial launch of a new product or feature.
  3. Competitor-focused research: Complete once for both business and SEO competitors. Refresh/update when there’s a new feature, product/service, or competitor.
  4. Location-focused research: Do this once per geographic location serviced and when you expand into new service locations

Step 2: Sort And Align

Step 2, sorting the long list of mined queries, is the linchpin of keyword universes.

If you get this right, you’ll be installing a powerful SEO prioritization system for your company.

Getting it wrong is just wasting time.

Anyone can create a large list of keywords, but creating strong filters and sorting mechanisms is hard.

The old school way to go about prioritization is by search volume.

Throw that classic view out the window: We can do better than that.

Most times, keywords with higher search volume actually convert less well – or get no real traffic at all due to AIOs.

As I mentioned in Death of the Keyword:

A couple of months ago, I rewrote my guide to inhouse SEO and started ranking in position one. But the joke was on me. I didn’t get a single dirty click for that keyword. Over 200 people search for “in house seo” but not a single person clicks on a search result.

By the way, Google Analytics only shows 10 clicks from organic search over the last 3 months. So, what’s going on? The 10 clicks I actually got are not reported in GSC (privacy… I guess?), but the majority of searchers likely click on one of the People Also Asked features that show up right below my search result.

Keeping that in mind about search volume, since we don’t know which keywords are most important for the business before targeting them – and we don’t want to make decisions by volume alone – we need sorting parameters based on strong signals.

We can summarize several signals for each keyword and sort the list by total score.

That’s exactly what I’ve done with clients like Ramp, the fastest-growing fintech startup in history, to prioritize content strategy.

Image Credit: Kevin Indig

Sorting is about defining an initial set of signals and then refining it with feedback.

You’ll start by giving each signal a weight based on our best guess – and then refine it over time.

When you build your keyword universe, you’ll want to define an automated logic (say, in Google Sheets or BigQuery).

Your logic could be a simple “if this then that,” like “if keyword is mentioned by customer, assign 10 points.”

Potential signals (not all need to be used):

  • Keyword is mentioned in customer conversation.
  • Keyword is part of a topic that converts well.
  • Topic is sharply related to direct offering or pain point your brand solves.
  • Mmonthly search volume (MSV)
  • Keyword difficulty (KD)/competitiveness
  • (MSV * KD) / CPC → I like to use this simple formula to balance search demand with competitiveness and potential conversion value.
  • Traffic potential.
  • Conversions from paid search or other channels.
  • Growing or shrinking MSV.
  • Query modifier indicates users are ready to take action, like “buy” or “download.”

You should give each signal a weight from 0-10 or 0-3, with the highest number being strongest and zero being weakest.

Your scoring will be unique to you based on business goals.

Let’s pause here for a moment: I created a simple tool that will make this work way easier, saving a lot of time and trial + error. (It’s below!) Premium subscribers get full access to tools like this one, along with additional content and deep dives.

But let’s say you’re prioritizing building content around essential topics and have goals set around growing topical authority. And let’s say you’re using the 0-10 scale. Your scoring might look something like:

  • Keyword is mentioned in customer conversation: 10.
  • Keyword is part of a topic that converts well: 10.
  • Topic is sharply related to direct offering or pain point your brand solves: 10.
  • MSV: 3.
  • KD/competitiveness: 6.
  • (MSV * KD) / CPC → I like to use this simple formula to balance search demand with competitiveness and potential conversion value: 5.
  • Traffic potential: 3.
  • Conversions from paid search or other channels: 6.
  • Growing or shrinking MSV: 4.
  • Query modifier indicates users are ready to take action, like “buy” or “download”: 7.

The sum of all scores for each query in your universe then determines the priority sorting of the list.

Keywords with the highest total score land at the top and vice versa.

New keywords on the list fall into a natural prioritization.

Important note: If your research shows that sales are connected to queries related to current events, news, updates in research reports, etc., those should be addressed as soon as possible.

(Example: If your company sells home solar batteries and recent weather news increases demand due to a specific weather event, make sure to prioritize that in your universe ASAP.)

Amanda’s thoughts: I might get some hate for this stance, but if you’re a new brand or site just beginning to build a content library and you fall into the integrator category, focus on building trust first by securing visibility in organic search results where you can as quickly as you can.

I know, I know: What about conversions? Conversion-focused content is crucial to the long-term success of the org.

But to set yourself apart, you need to actually create the content that no one is making about the questions, pain points, and specific needs your target audience is voicing.

If your sales team repeatedly hears a version of the same question, it’s likely there’s no easy-to-find answer to the question – or the current answers out there aren’t trustworthy. Trust is the most important currency in the era of AI-based search. Start building it ASAP. Conversions will follow.

Step 3: Refine

Models get good by improving over time.

Like a large language model that learns from fine-tuning, we need to adjust our signal weighting based on the results we see.

We can go about fine-tuning in two ways:

1. Anecdotally, conversions should increase as we build new content (or update existing content) based on the keyword universe prioritization scoring.

Otherwise, sorting signals have the wrong weight, and we need to adjust.

2. Another way to test the system is a snapshot analysis.

To do so, you’ll run a comparison of two sets of data: the keywords that attract the most organic visibility and the pages that drive the most conversions, side-by-side with the keywords at the top of the universe.

Ideally, they overlap. If they don’t, aim to adjust your sorting signals until they come close.

Tips For Maintaining Your Keyword Universe

Look, there’s no point in doing all this work unless you’re going to maintain the hygiene of this data over time.

This is what you need to keep in mind:

1. Once you’ve created a page that targets a keyword in your list, move it to a second tab on the spreadsheet or another table in the database.

That way, you don’t lose track and end up with writers creating duplicate content.

2. Build custom click curves for each page type (blog article, landing page, calculator, etc.) when including traffic and revenue projections.

Assign each step in the conversion funnel a conversion rate – like visit ➡️newsletter sign-up, visit ➡️demo, visit ➡️purchase – and multiply search volume with an estimated position on the custom click curve, conversion rates, and lifetime value. (Fine-tune regularly.)

Here’s an example: MSV * CTR (pos 1) * CVRs * Lifetime value = Revenue prediction

3. GPT for Sheets or the Meaning Cloud extension for Google Sheets can speed up assigning each keyword to a topic.

Meaning Cloud allows us to easily train an LLM by uploading a spreadsheet with a few tagged keywords.

GPT for Sheets connects Google Sheets with the OpenAI API so we can give prompts like “Which of the following topics would this keyword best fit? Category 1, category 2, category 3, etc.”

LLMs like Chat GPT, Claude, or Gemini have become good enough that you can easily use them to assign topics as well. Just prompt for consistency!

4. Categorize the keywords by intent, and then group or sort your sheet by intent. Check out Query Fan Out to learn why.

5. Don’t build too granular and expansive of a keyword universe that you can’t activate it.

If you have a team of in-house strategists and three part-time freelancers, expecting a 3,000 keyword universe to feel doable and attainable is … an unmet expectation.

Your Keyword Universe Is Designed To Explore

The old way of doing SEO – chasing high-volume keywords and hoping for conversions – isn’t built for today’s search reality.

Trust is hard to earn. (And traffic is hard to come by.)

The keyword universe gives you a living, breathing SEO operating system. One that can evolve based on your custom scoring and prioritization.

Prioritizing what’s important (sorting) allows us to literally filter through the noise (distractions, offers, shiny objects) and bring us to where we want to be.

So, start with your old keyword docs. (Or toss them out if they’re irrelevant, aged poorly, or simply hyper-focused on volume.)

Then, dig into what your customers are really asking. Build smart signals. Assign weights. And refine as you go.

This isn’t about perfection. It’s about building a system that actually works for you.

And speaking of building a system…

Keyword Universe Tracker (For Premium Subscribers)

For premium Growth Memo subscribers, we’ve got a tool that will help save you time and score queries by unique priority weights that you set.

Image Credit: Kevin Indig

More Resources: 


Featured Image: Paulo Bobita/Search Engine Journal

Ask An SEO: How Can I Turn Low-Converting Traffic Into High-Value Sessions? via @sejournal, @kevgibbo

This week’s Ask an SEO question comes from an ecommerce site owner who’s experiencing a common frustration:

“Our ecommerce site has decent traffic but poor conversion rates. What data points should we be analyzing first, and what are two to three quick conversion rate optimization (CRO) wins that most companies overlook?”

This is a great question. Having good traffic but poor conversion rates is really frustrating for ecommerce site managers.

You’ve successfully managed to get hundreds or even thousands of people onto your landing pages, but only a tiny proportion of them turn into paying customers.

What’s going wrong, and what can you do about it?

I’ve broken down my tips as follows:

  • Start with your bigger picture goals.
  • Double-check your targeting.
  • Data points to analyze.
  • Simulate the user journey.
  • Quick CRO wins.

Thinking About The Bigger Picture First

Before answering your question, I think it’s valuable to take a step back and think about your approach to running your site – and what your goals are.

People often get lots of low-quality traffic for the following kinds of reasons:

  • They’re attracting the wrong kinds of people.
  • They’re using paid ads ineffectively.
  • The content on the site gets clicks, but doesn’t solve visitors’ needs.
  • The site is confusing, unclear, or even annoying to use.

For me, conversion is always built on the same key fundamentals:

  • Quality over quantity: There’s no value in having millions of visitors if none of them convert. I’ve worked on ecommerce sites where we implemented changes that made traffic drop dramatically. However, the quality of the remaining traffic was much higher, meaning conversion rates – and revenue – soared.
  • Focus on user experience (UX): It’s really important to understand the user journey from inception to conversion. What’s helping people navigate your site, and what’s hindering them? Often, this is simply about returning to the basics of UX. High-value sessions come from relevance, ease, and trust – all of which are fully within your control.

So, before making changes, I’d encourage you to step back and think about your goals and objectives for the site. Everything else will feed into that.

What’s Realistic?

It’s helpful to have a benchmark for what your conversion rate should be.

According to Shopify data, the average ecommerce site conversion rate is 1.4%. A very good rate is 3.2% or above, while very few sites hit more than 5%.

Double-Check Your Targeting

A common reason people get high traffic but low conversions is due to problems with their targeting. Essentially, they’re attracting the wrong kinds of site visitors.

For example, you might run a site selling tennis memorabilia. But most of the traffic you get is from people searching for tickets to tennis tournaments. As a consequence, most visitors bounce.

If this is the case, it’s time to rethink your SEO. Are you ranking for the right keywords? Are your landing pages aligned with the top queries for those search terms? Making changes here can make a big difference.

However, if your targeting is correct but conversion is still off, it’s time to look into CRO.

5 Kinds Of Conversion Rate Data To Analyze

By analyzing how people navigate your site, you can start to build a picture of how they’re using it – and which features of your site or the user journey are turning visitors off.

If you’re using a store builder like Shopify, Wix, or Squarespace, you should have access to quite a lot of CRO data within the dashboard. On older sites, it can be a bit trickier to figure these things out.

There are lots of metrics that can give you insights into conversion rates. But the following information is often most telling:

1. User Behavior Metrics

  • Bounce rate and exit rate: This is especially important for key pages (such as product and checkout).
  • Scroll depth: Are users seeing your calls to action and product info?
  • Heatmaps: Are users interacting with intended elements?
  • Entry points: Are there commonalities between entrances for users who aren’t converting versus those who are converting? If so, this may indicate a specific issue with certain user journeys.

2. Conversion Funnel Drop-Off

  • Abandonment: Where are users abandoning the funnel (e.g., product page → add to cart → checkout)?
  • Granularity: I’d also recommend looking at abandonment rates for each step.

3. Device & Browser Performance

  • Device: Conversion rate by device (mobile often underperforms).
  • Operating system: Technical glitches in specific browsers/OS versions can quietly hurt conversions.

4. Site Speed & Core Web Vitals

  • Page load time: This directly affects conversions, especially on mobile.
  • Track it: Use tools like Google PageSpeed Insights or Lighthouse.

5. On-Site Search Behavior

  • What are people searching for?
  • Are searches returning relevant results?
  • High search exit rate often signals poor relevance or UX.

This can seem like a lot of work! However, what you’re really looking for is a basic benchmark for each of the above points that you can plug into a spreadsheet.

You only need to gather this data once. Then, it’s just a case of seeing how changes you make affect those scores.

For example, say you have a high cart abandonment rate of 90%. You might decide to make some simple changes to the process (e.g., letting users check out as a guest). You’ll then be able to see what effect your change has had.

Simulate The User’s Journey

This is all about putting yourself in your users’ shoes. I’m often surprised by how few ecommerce site owners do this, yet you can’t understand what’s going wrong if you don’t use the site like a user would.

Simulating user journeys often exposes glaring usability issues.

For example, it’s quite common to land on a category page for, say, sports T-shirts, and find it’s full of broken links. You click on a T-shirt that looks good, but it leads to a 404. That’s such a turn-off to potential customers.

There are, of course, endless possible ways that people can navigate your site. I’d prioritize a handful of your most popular products and try to imagine how people would go through the process of buying them.

Here are some of the things to look out for:

Landing Page (First Impression)

  • Is the value proposition clear within five seconds?
  • Are headlines concise and benefit-driven?
  • Is there a clear CTA above the fold?
  • Are distractions minimized (pop-ups, autoplay, clutter)?

Navigation And Search

  • Is site navigation intuitive and consistent?
  • Can users find products in three clicks or fewer?
  • Are filters/sorting options clear and responsive?

Category Pages

  • Is key info shown (price, reviews, quick add)?
  • Is the layout clean (think about devices here, mobile responsiveness, font size, etc.)?
  • Are products visible above the fold?

Product Detail Pages

  • Are product titles, descriptions, and photos compelling and complete?
  • Is the price, shipping, and returns information visible without scrolling?
  • Are reviews and ratings visible and credible?
  • Is the “Add to Cart” button obvious and persistent?

Cart And Checkout

  • Is the cart editable (quantity, remove item)?
  • Are total costs (including shipping/tax) shown upfront?
  • Can users check out as a guest?
  • Are there too many form fields? (Trim non-essentials.)
  • Are payment options clearly presented and working?

Speed

Quick CRO Wins That Are Often Overlooked

Conversion rate optimization doesn’t always require a root-and-branch site upgrade.

Here are some simple tweaks you can make that can be surprisingly impactful.

Improve Product Page Microcopy And Visual Hierarchy

If a user lands on a product page, it’s crucial to communicate key information to them. Yet, for many products, people have to scroll below the fold to find the information they need.

  • Show total price, shipping, and returns at the top of the page.
  • Have a clear image of the product (you’d be amazed, but this doesn’t always happen).
  • Spell out the product name, color, type, and other information.
  • Add urgency (“Only 3 left!”), real-time interest (“27 people viewed this today”), or social proof (UGC, ratings) near the CTA.

Make It Easy To Buy

It can sometimes be surprisingly difficult for people to know how to actually buy things on ecommerce sites, particularly when using mobile. I’d recommend:

  • Making the “Add to Cart” button sticky on mobile. Make sure it’s in a clear, bold, contrasting color.
  • Add subtle animations or color shifts to draw attention.
  • Show trust badges (e.g., secure checkout, money-back guarantee).

Make It Easier To Find Items

Any ecommerce site today should have a search bar where people can look for products. Help people find products by offering auto-suggestions with images and categories.

I’d also recommend tracking no-results queries and fixing them with redirects or better tagging. You might also want to promote high-converting products in the top results.

Simplify The Checkout Experience

A poor checkout experience can be a real killer for conversion. The priority here is almost always about making things as easy as possible for buyers.

  • Remove non-critical fields (phone number, company name).
  • Offer guest checkout as default.
  • Add progress indicators to reduce perceived friction.

Use Exit-Intent Offers Wisely

Exit-intent technology can be very helpful, at least on some kinds of websites.

However, it’s important to use it thoughtfully and appropriately (what makes sense on a fast-fashion website won’t look as good on a luxury goods store).

Instead of broad discounts, use behavioral targeting. Here are some options:

  • Offer a free shipping incentive only to high-cart-value exits.
  • Show email capture pop-ups only after a period of inactivity or product page scrolling.
  • Use exit-intent popups with tailored offers (e.g., “Complete your order now and get 10% off”).
  • Send a three-part abandoned cart email flow (reminder, offer, scarcity, i.e., “Items going fast!”)

A Final Note: Test It First

Last but not least, I’d always recommend A/B testing before rolling out whole site changes.

If you’ve tweaked a certain part of the user journey or the layout of a landing page, trial it for a week or so and see what results you get.

This avoids making damaging changes that harm conversion rates (and take a long time to rectify).

Preaching To The Converters

I hope these ideas for converting more of your ecommerce site’s visitors have helped.

As I’ve shown, there are tons of potential CRO techniques you can use, and it can get a bit overwhelming.

However, it’s often more straightforward than it seems, and you can often start with small steps that make a difference.

One of the reasons ecommerce site management can be so rewarding is the ability to experiment and see how small changes can make a big difference. Good luck!

More Resources:


Featured Image: Paulo Bobita/Search Engine Journal

Google’s Trust Ranking Patent Shows How User Behavior Is A Signal via @sejournal, @martinibuster

Google long ago filed a patent for ranking search results by trust. The groundbreaking idea behind the patent is that user behavior can be used as a starting point for developing a ranking signal.

The big idea behind the patent is that the Internet is full of websites all linking to and commenting about each other. But which sites are trustworthy? Google’s solution is to utilize user behavior to indicate which sites are trusted and then use the linking and content on those sites to reveal more sites that are trustworthy for any given topic.

PageRank is basically the same thing only it begins and ends with one website linking to another website. The innovation of Google’s trust ranking patent is to put the user at the start of that trust chain like this:

User trusts X Websites > X Websites trust Other Sites > This feeds into Google as a ranking signal

The trust originates from the user and flows to trust sites that themselves provide anchor text, lists of other sites and commentary about other sites.

That, in a nutshell, is what Google’s trust-based ranking algorithm is about.

The deeper insight is that it reveals Google’s groundbreaking approach to letting users be a signal of what’s trustworthy. You know how Google keeps saying to create websites for users? This is what the trust patent is all about, putting the user in the front seat of the ranking algorithm.

Google’s Trust And Ranking Patent

The patent was coincidentally filed around the same period that Yahoo and Stanford University published a Trust Rank research paper which is focused on identifying spam pages.

Google’s patent is not about finding spam. It’s focused on doing the opposite, identifying trustworthy web pages that satisfy the user’s intent for a search query.

How Trust Factors Are Used

The first part of any patent consists of an Abstract section that offers a very general description of the invention that that’s what this patent does as well.

The patent abstract asserts:

  • That trust factors are used to rank web pages.
  • The trust factors are generated from “entities” (which are later described to be the users themselves, experts, expert web pages, and forum members) that link to or comment about other web pages).
  • Those trust factors are then used to re-rank web pages.
  • Re-ranking web pages kicks in after the normal ranking algorithm has done its thing with links, etc.

Here’s what the Abstract says:

“A search engine system provides search results that are ranked according to a measure of the trust associated with entities that have provided labels for the documents in the search results.

A search engine receives a query and selects documents relevant to the query.

The search engine also determines labels associated with selected documents, and the trust ranks of the entities that provided the labels.

The trust ranks are used to determine trust factors for the respective documents. The trust factors are used to adjust information retrieval scores of the documents. The search results are then ranked based on the adjusted information retrieval scores.”

As you can see, the Abstract does not say who the “entities” are nor does it say what the labels are yet, but it will.

Field Of The Invention

The next part is called the Field Of The Invention. The purpose is to describe the technical domain of the invention (which is information retrieval) and the focus (trust relationships between users) for the purpose of ranking web pages.

Here’s what it says:

“The present invention relates to search engines, and more specifically to search engines that use information indicative of trust relationship between users to rank search results.”

Now we move on to the next section, the Background, which describes the problem this invention solves.

Background Of The Invention

This section describes why search engines fall short of answering user queries (the problem) and why the invention solves the problem.

The main problems described are:

  • Search engines are essentially guessing (inference) what the user’s intent is when they only use the search query.
  • Users rely on expert-labeled content from trusted sites (called vertical knowledge sites) to tell them which web pages are trustworthy
  • Explains why the content labeled as relevant or trustworthy is important but ignored by search engines.
  • It’s important to remember that this patent came out before the BERT algorithm and other natural language approaches that are now used to better understand search queries.

This is how the patent explains it:

“An inherent problem in the design of search engines is that the relevance of search results to a particular user depends on factors that are highly dependent on the user’s intent in conducting the search—that is why they are conducting the search—as well as the user’s circumstances, the facts pertaining to the user’s information need.

Thus, given the same query by two different users, a given set of search results can be relevant to one user and irrelevant to another, entirely because of the different intent and information needs.”

Next it goes on to explain that users trust certain websites that provide information about certain topics:

“…In part because of the inability of contemporary search engines to consistently find information that satisfies the user’s information need, and not merely the user’s query terms, users frequently turn to websites that offer additional analysis or understanding of content available on the Internet.”

Websites Are The Entities

The rest of the Background section names forums, review sites, blogs, and news websites as places that users turn to for their information needs, calling them vertical knowledge sites. Vertical Knowledge sites, it’s explained later, can be any kind of website.

The patent explains that trust is why users turn to those sites:

“This degree of trust is valuable to users as a way of evaluating the often bewildering array of information that is available on the Internet.”

To recap, the “Background” section explains that the trust relationships between users and entities like forums, review sites, and blogs can be used to influence the ranking of search results. As we go deeper into the patent we’ll see that the entities are not limited to the above kinds of sites, they can be any kind of site.

Patent Summary Section

This part of the patent is interesting because it brings together all of the concepts into one place, but in a general high-level manner, and throws in some legal paragraphs that explain that the patent can apply to a wider scope than is set out in the patent.

The Summary section appears to have four sections:

  • The first section explains that a search engine ranks web pages that are trusted by entities (like forums, news sites, blogs, etc.) and that the system maintains information about these labels about trusted web pages.
  • The second section offers a general description of the work of the entities (like forums, news sites, blogs, etc.).
  • The third offers a general description of how the system works, beginning with the query, the assorted hand waving that goes on at the search engine with regard to the entity labels, and then the search results.
  • The fourth part is a legal explanation that the patent is not limited to the descriptions and that the invention applies to a wider scope. This is important. It enables Google to use a non-existent thing, even something as nutty as a “trust button” that a user selects to identify a site as being trustworthy as an example. This enables an example like a non-existent “trust button” to be a stand-in for something else, like navigational queries or Navboost or anything else that is a signal that a user trusts a website.

Here’s a nutshell explanation of how the system works:

  • The user visits sites that they trust and click a “trust button” that tells the search engine that this is a trusted site.
  • The trusted site “labels” other sites as trusted for certain topics (the label could be a topic like “symptoms”).
  • A user asks a question at a search engine (a query) and uses a label (like “symptoms”).
  • The search engine ranks websites according to the usual manner then it looks for sites that users trust and sees if any of those sites have used labels about other sites.
  • Google ranks those other sites that have had labels assigned to them by the trusted sites.

Here’s an abbreviated version of the third part of the Summary that gives an idea of the inner workings of the invention:

“A user provides a query to the system…The system retrieves a set of search results… The system determines which query labels are applicable to which of the search result documents. … determines for each document an overall trust factor to apply… adjusts the …retrieval score… and reranks the results.”

Here’s that same section in its entirety:

  • “A user provides a query to the system; the query contains at least one query term and optionally includes one or more labels of interest to the user.
  • The system retrieves a set of search results comprising documents that are relevant to the query term(s).
  • The system determines which query labels are applicable to which of the search result documents.
  • The system determines for each document an overall trust factor to apply to the document based on the trust ranks of those entities that provided the labels that match the query labels.
  • Applying the trust factor to the document adjusts the document’s information retrieval score, to provide a trust adjusted information retrieval score.
  • The system reranks the search result documents based at on the trust adjusted information retrieval scores.”

The above is a general description of the invention.

The next section, called Detailed Description, deep dives into the details. At this point it’s becoming increasingly evident that the patent is highly nuanced and can not be reduced to simple advice similar to: “optimize your site like this to earn trust.”

A large part of the patent hinges on a trust button and an advanced search query:  label:

Neither the trust button or the label advanced search query have ever existed. As you’ll see, they are quite probably stand-ins for techniques that Google doesn’t want to explicitly reveal.

Detailed Description In Four Parts

The details of this patent are located in four sections within the Detailed Description section of the patent. This patent is not as simple as 99% of SEOs say it is.

These are the four sections:

  1. System Overview
  2. Obtaining and Storing Trust Information
  3. Obtaining and Storing Label Information
  4. Generated Trust Ranked Search Results

The System Overview is where the patent deep dives into the specifics. The following is an overview to make it easy to understand.

System Overview

1. Explains how the invention (a search engine system) ranks search results based on trust relationships between users and the user-trusted entities who label web content.

2. The patent describes a “trust button” that a user can click that tells Google that a user trusts a website or trusts the website for a specific topic or topics.

3. The patent says a trust related score is assigned to a website when a user clicks a trust button on a website.

4. The trust button information is stored in a trust database that’s referred to as #190.

Here’s what it says about assigning a trust rank score based on the trust button:

“The trust information provided by the users with respect to others is used to determine a trust rank for each user, which is measure of the overall degree of trust that users have in the particular entity.”

Trust Rank Button

The patent refers to the “trust rank” of the user-trusted websites. That trust rank is based on a trust button that a user clicks to indicate that they trust a given website, assigning a trust rank score.

The patent says:

“…the user can click on a “trust button” on a web page belonging to the entity, which causes a corresponding record for a trust relationship to be recorded in the trust database 190.

In general any type of input from the user indicating that such as trust relationship exists can be used.”

The trust button has never existed and the patent quietly acknowledges this by stating that any type of input can be used to indicate the trust relationship.

So what is it? I believe that the “trust button” is a stand-in for user behavior metrics in general, and site visitor data in particular. The patent Claims section does not mention trust buttons at all but does mention user visitor data as an indicator of trust.

Here are several passages that mention site visits as a way to understand if a user trusts a website:

“The system can also examine web visitation patterns of the user and can infer from the web visitation patterns which entities the user trusts. For example, the system can infer that a particular user trust a particular entity when the user visits the entity’s web page with a certain frequency.”

The same thing is stated in the Claims section of the patent, it’s the very first claim they make for the invention:

“A method performed by data processing apparatus, the method comprising:
determining, based on web visitation patterns of a user, one or more trust relationships indicating that the user trusts one or more entities;”

It may very well be that site visitation patterns and other user behaviors are what is meant by the “trust button” references.

Labels Generated By Trusted Sites

The patent defines trusted entities as news sites, blogs, forums, and review sites, but not limited to those kinds of sites, it could be any other kind of website.

Trusted websites create references to other sites and in that reference they label those other sites as being relevant to a particular topic. That label could be an anchor text. But it could be something else.

The patent explicitly mentions anchor text only once:

“In some cases, an entity may simply create a link from its site to a particular item of web content (e.g., a document) and provide a label 107 as the anchor text of the link.”

Although it only explicitly mentions anchor text once, there are other passages where it anchor text is strongly implied, for example, the patent offers a general description of labels as describing or categorizing the content found on another site:

“…labels are words, phrases, markers or other indicia that have been associated with certain web content (pages, sites, documents, media, etc.) by others as descriptive or categorical identifiers.”

Labels And Annotations

Trusted sites link out to web pages with labels and links. The combination of a label and a link is called an annotation.

This is how it’s described:

“An annotation 106 includes a label 107 and a URL pattern associated with the label; the URL pattern can be specific to an individual web page or to any portion of a web site or pages therein.”

Labels Used In Search Queries

Users can also search with “labels” in their queries by using a non-existent “label:” advanced search query. Those kinds of queries are then used to match the labels that a website page is associated with.

This is how it’s explained:

“For example, a query “cancer label:symptoms” includes the query term “cancel” and a query label “symptoms”, and thus is a request for documents relevant to cancer, and that have been labeled as relating to “symptoms.”

Labels such as these can be associated with documents from any entity, whether the entity created the document, or is a third party. The entity that has labeled a document has some degree of trust, as further described below.”

What is that label in the search query? It could simply be certain descriptive keywords, but there aren’t any clues to speculate further than that.

The patent puts it all together like this:

“Using the annotation information and trust information from the trust database 190, the search engine 180 determines a trust factor for each document.”

Takeaway:

A user’s trust is in a website. That user-trusted website is not necessarily the one that’s ranked, it’s the website that’s linking/trusting another relevant web page. The web page that is ranked can be the one that the trusted site has labeled as relevant for a specific topic and it could be a web page in the trusted site itself. The purpose of the user signals is to provide a starting point, so to speak, from which to identify trustworthy sites.

Experts Are Trusted

Vertical Knowledge Sites, sites that users trust, can host the commentary of experts. The expert could be the publisher of the trusted site as well. Experts are important because links from expert sites are used as part of the ranking process.

Experts are defined as publishing a deep level of content on the topic:

“These and other vertical knowledge sites may also host the analysis and comments of experts or others with knowledge, expertise, or a point of view in particular fields, who again can comment on content found on the Internet.

For example, a website operated by a digital camera expert and devoted to digital cameras typically includes product reviews, guidance on how to purchase a digital camera, as well as links to camera manufacturer’s sites, new products announcements, technical articles, additional reviews, or other sources of content.

To assist the user, the expert may include comments on the linked content, such as labeling a particular technical article as “expert level,” or a particular review as “negative professional review,” or a new product announcement as ;new 10MP digital SLR’.”

Links From Expert Sites

Links and annotations from user-trusted expert sites are described as sources of trust information:

“For example, Expert may create an annotation 106 including the label 107 “Professional review” for a review 114 of Canon digital SLR camera on a web site “www.digitalcameraworld.com”, a label 107 of “Jazz music” for a CD 115 on the site “www.jazzworld.com”, a label 107 of “Classic Drama” for the movie 116 “North by Northwest” listed on website “www.movierental.com”, and a label 107 of “Symptoms” for a group of pages describing the symptoms of colon cancer on a website 117 “www.yourhealth.com”.

Note that labels 107 can also include numerical values (not shown), indicating a rating or degree of significance that the entity attaches to the labeled document.

Expert’s web site 105 can also include trust information. More specifically, Expert’s web site 105 can include a trust list 109 of entities whom Expert trusts. This list may be in the form of a list of entity names, the URLs of such entities’ web pages, or by other identifying information. Expert’s web site 105 may also include a vanity list 111 listing entities who trust Expert; again this may be in the form of a list of entity names, URLs, or other identifying information.”

Inferred Trust

The patent describes additional signals that can be used to signal (infer) trust. These are more traditional type signals like links, a list of trusted web pages (maybe a resources page?) and a list of sites that trust the website.

These are the inferred trust signals:

“(1) links from the user’s web page to web pages belonging to trusted entities;
(2) a trust list that identifies entities that the user trusts; or
(3) a vanity list which identifies users who trust the owner of the vanity page.”

Another kind of trust signal that can be inferred is from identifying sites that a user tends to visit.

The patent explains:

“The system can also examine web visitation patterns of the user and can infer from the web visitation patterns which entities the user trusts. For example, the system can infer that a particular user trusts a particular entity when the user visits the entity’s web page with a certain frequency.”

Takeaway:

That’s a pretty big signal and I believe that it suggests that promotional activities that encourage potential site visitors to discover a site and then become loyal site visitors can be helpful. For example, that kind of signal can be tracked with branded search queries. It could be that Google is only looking at site visit information but I think that branded queries are an equally trustworthy signal, especially when those queries are accompanied by labels… ding, ding, ding!

The patent also lists some kind of out there examples of inferred trust like contact/chat list data. It doesn’t say social media, just contact/chat lists.

Trust Can Decay or Increase

Another interesting feature of trust rank is that it can decay or increase over time.

The patent is straightforward about this part:

“Note that trust relationships can change. For example, the system can increase (or decrease) the strength of a trust relationship for a trusted entity. The search engine system 100 can also cause the strength of a trust relationship to decay over time if the trust relationship is not affirmed by the user, for example by visiting the entity’s web site and activating the trust button 112.”

Trust Relationship Editor User Interface

Directly after the above paragraph is a section about enabling users to edit their trust relationships through a user interface. There has never been such a thing, just like the non-existent trust button.

This is possibly a stand-in for something else. Could this trusted sites dashboard be Chrome browser bookmarks or sites that are followed in Discover? This is a matter for speculation.

Here’s what the patent says:

“The search engine system 100 may also expose a user interface to the trust database 190 by which the user can edit the user trust relationships, including adding or removing trust relationships with selected entities.

The trust information in the trust database 190 is also periodically updated by crawling of web sites, including sites of entities with trust information (e.g., trust lists, vanity lists); trust ranks are recomputed based on the updated trust information.”

What Google’s Trust Patent Is About

Google’s Search Result Ranking Based On Trust patent describes a way of leveraging user-behavior signals to understand which sites are trustworthy. The system then identifies sites that are trusted by the user-trusted sites and uses that information as a ranking signal. There is no actual trust rank metric, but there are ranking signals related to what users trust. Those signals can decay or increase based on factors like whether a user still visits those sites.

The larger takeaway is that this patent is an example of how Google is focused on user signals as a ranking source, so that they can feed that back into ranking sites that meet their needs. This means that instead of doing things because “this is what Google likes,” it’s better to go even deeper and do things because users like it. That will feed back to Google through these kinds of algorithms that measure user behavior patterns, something we all know Google uses.

Featured Image by Shutterstock/samsulalam

Meet Jim O’Neill, the longevity enthusiast who is now RFK Jr.’s right-hand man

When Jim O’Neill was nominated to be the second in command at the US Department of Health and Human Services, Dylan Livingston was excited. As founder and CEO of the lobbying group Alliance for Longevity Initiatives (A4LI), Livingston is a member of a community that seeks to extend human lifespan. O’Neill is “kind of one of us,” he told me shortly before O’Neill was sworn in as deputy secretary on June 9. “And now [he’s] in a position of great influence.”

As Robert F. Kennedy Jr.’s new right-hand man, O’Neill is expected to wield authority at health agencies that fund biomedical research and oversee the regulation of new drugs. And while O’Neill doesn’t subscribe to Kennedy’s most contentious beliefs—and supports existing vaccine schedules—he may still steer the agencies in controversial new directions. 

Although much less of a public figure than his new boss, O’Neill is quite well-known in the increasingly well-funded and tight-knit longevity community. His acquaintances include the prominent longevity influencer Bryan Johnson, who describes him as “a soft-spoken, thoughtful, methodical guy,” and the billionaire tech entrepreneur Peter Thiel. 

In speaking with more than 20 people who work in the longevity field and are familiar with O’Neill, it’s clear that they share a genuine optimism about his leadership. And while no one can predict exactly what O’Neill will do, many in the community believe that he could help bring attention and resources to their cause and make it easier for them to experiment with potential anti-aging drugs. 

This idea is bolstered not just by his personal and professional relationships but also by his past statements and history working at aging-focused organizations—all of which suggest he indeed believes scientists should be working on ways to extend human lifespan beyond its current limits and thinks unproven therapies should be easier to access. He has also supported the libertarian idea of creating new geographic zones, possibly at sea, in which residents can live by their own rules (including, notably, permissive regulatory regimes for new drugs and therapies). 

“In [the last three administrations] there weren’t really people like that from our field taking these positions of power,” says Livingston, adding that O’Neill’s elevation is “definitely something to be excited about.”

Not everyone working in health is as enthusiastic. If O’Neill still holds the views he has espoused over the years, that’s “worrisome,” says Diana Zuckerman, a health policy analyst and president of the National Center for Health Research, a nonprofit think tank in Washington, DC. 

“There’s nothing worse than getting a bunch of [early-stage unproven therapies] on the market,” she says. Those products might be dangerous and could make people sick while enriching those who develop or sell them. 

“Getting things on the market quickly means that everybody becomes a guinea pig,” Zuckerman says. “That’s not the way those of us who care about health care think.” 

The consumer advocacy group Public Citizen puts it far more bluntly, describing O’Neill as “one of Trump’s worst picks” and saying that he is “unfit to be the #2 US health-care leader.” His libertarian views are “antithetical to basic public health,” the organization’s co-president said in a statement. Neither O’Neill nor HHS responded to requests for comment. 

“One of us”

As deputy secretary of HHS, O’Neill will oversee a number of agencies, including the National Institutes of Health, the world’s biggest funder of biomedical research; the Centers for Disease Control and Prevention, the country’s public health agency; and the Food and Drug Administration, which was created to ensure that drugs and medical devices are safe and effective. 

“It can be a quite powerful position,” says Patricia Zettler, a legal scholar at Ohio State University who specializes in drug regulation and the FDA.

It is the most senior role O’Neill has held at HHS, though it’s not the first. He occupied various positions in the department over five years during the early 2000s, according to his LinkedIn profile. But it is what he did after that has helped him cultivate a reputation as an ally for longevity enthusiasts. 

O’Neill appears to have had a close relationship with Thiel since at least the late 2000s. Thiel has heavily invested in longevity research and has said he does not believe that death is inevitable. In 2011 O’Neill referred to Thiel as his “friend and patron.” (A representative for Thiel did not respond to a request for comment.) 

O’Neill also served as CEO of the Thiel Foundation between 2009 and 2012 and cofounded the Thiel Fellowship, which offers $200,000 to promising young people if they drop out of college and do other work. And he spent seven years as managing director of Mithril Capital Management, a “family of long-term venture capital funds” founded by Thiel, according to O’Neill’s LinkedIn profile. 

O’Neill got further stitched into the longevity field when he spent more than a decade representing Thiel’s interests as a board member of the SENS Research Foundation (SRF), an organization dedicated to finding treatments for aging, to which Thiel was a significant donor. 

O’Neill even spent a couple of years as CEO of SRF, from 2019 to 2021, when its founder Aubrey de Grey, a prominent figure in the longevity field, was removed following accusations of sexual harassment. As CEO, O’Neill oversaw a student education program and multiple scientific research projects that focused on various aspects of aging, according to the organization’s annual reports. And in a 2020 SRF annual report, O’Neill wrote that Eric Hargan, then the deputy secretary of HHS, had attended an SRF conference to discuss “regulatory reform.” 

“More and more influential people consider aging an absurdity,” he wrote in the report. “Now we need to make it one.” 

While de Grey calls him “the devil incarnate”—probably because he believes O’Neill “incited” two women to make sexual harassment allegations against him—the many other scientists, biotech CEOs, and other figures in the longevity field contacted by MIT Technology Review had more positive opinions of O’Neill, with many claiming they were longtime friends or acquaintances of the new deputy secretary (though, at the same time, many were reluctant to share specific views about his past work). 

Longevity science is a field that’s long courted controversy, owing largely to far-fetched promises of immortality and the ongoing marketing of creams, pills, intravenous infusions, and other so-called anti-aging treatments that are not supported by evidence. But the community includes people along a spectrum of beliefs (with the goals of adding a few years of healthy lifespan to the population at one end and immortality at the other), and serious doctors and scientists are working to bring legitimacy to the field

Pretty much everyone in the field that I spoke with appears to be hopeful about what O’Neill will do now that he’s been confirmed. Namely, they hope he will use his new position to direct attention and funds to legitimate longevity research and the development of new drugs that might slow or reverse human aging. 

Johnson, whose extreme and expensive approaches to extending his own lifespan have made him something of a celebrity, calls O’Neill a friend and says they’ve “known each other for a little over 15 years.” He says he can imagine O’Neill setting a goal to extend the lifespans of Americans.

Eric Verdin, president of the Buck Institute for Research on Aging in Novato, California, says O’Neill has “been at the Buck several times” and calls him “a good guy”—someone who is “serious” and who understands the science of aging. He says, “He’s certainly someone who is going to help us to really bring the longevity field to the front of the priorities of this administration.”

Celine Halioua, CEO of the biotech company Loyal, which is developing drugs to extend the lifespan of dogs, echoes these sentiments, saying she has “always liked and respected” O’Neill. “It’ll definitely be nice to have somebody who’s bought into the thesis [of longevity science] at the FDA,” she says. 

And Joe Betts-LaCroix, CEO of the longevity biotech company Retro Biosciences, says he’s known O’Neill for something like 10 years and describes him as “smart and clear thinking.” “We’ve mutually been part of poetry readings,” he says. “He’s been definitely interested in wanting us as a society to make progress on age-related disease.”

After his confirmation, the A4LI LinkedIn account posted a photo of Livingston, its CEO, with O’Neill, writing that “we look forward to working with him to elevate aging research as a national priority and to modernize regulatory pathways that support the development of longevity medicines.”

“His work at SENS Research Foundation [suggests] to me and to others that [longevity] is going to be something that he prioritizes,” Livingston says. “I think he’s a supporter of this field, and that’s really all that matters right now to us.”

Changing the rules

While plenty of treatments have been shown to slow aging in lab animals, none of them have been found to successfully slow or reverse human aging. And many longevity enthusiasts believe drug regulations are to blame. 

O’Neill is one of them. He has long supported deregulation of new drugs and medical devices. During his first tour at HHS, for instance, he pushed back against regulations on the use of algorithms in medical devices. “FDA had to argue that an algorithm … is a medical device,” he said in a 2014 presentation at a meeting on “rejuvenation biotechnology.” “I managed to put a stop to that, at least while I was there.”

During the same presentation, O’Neill advocated lowering the bar for drug approvals in the US. “We should reform [the] FDA so that it is approving drugs after their sponsors have demonstrated safety and let people start using them at their own risk,” he said. “Let’s prove efficacy after they’ve been legalized.”

This sentiment appears to be shared by Robert F. Kennedy Jr. In a recent podcast interview with Gary Brecka, who describes himself as a “longevity expert,” Kennedy said that he wanted to expand access to experimental therapies. “If you want to take an experimental drug … you ought to be able to do that,” he said in the episode, which was published online in May.

But the idea is divisive. O’Neill was essentially suggesting that drugs be made available after the very first stage of clinical testing, which is designed to test whether a new treatment is safe. These tests are typically small and don’t reveal whether the drug actually works.

That’s an idea that concerns ethicists. “It’s just absurd to think that the regulatory agency that’s responsible for making sure that products are safe and effective before they’re made available to patients couldn’t protect patients from charlatans,” says Holly Fernandez Lynch, a professor of medical ethics and health policy at the University of Pennsylvania who is currently on sabbatical. “It’s just like a complete dereliction of duty.”

Robert Steinbrook, director of the health research group at Public Citizen, largely agrees that this kind of change to the drug approval process is a bad idea, though notes that he and his colleagues are generally more concerned about O’Neill’s views on the regulation of technologies like AI in health care, given his previous efforts on algorithms. 

“He has deregulatory views and would not be an advocate for an appropriate amount of regulation when regulation was needed,” Steinbrook says.

Ultimately, though, even if O’Neill does try to change things, Zettler points out that there is currently no lawful way for the FDA to approve drugs that aren’t shown to be effective. That requirement won’t change unless Congress acts on the matter, she says: “It remains to be seen how big of a role HHS leadership will have in FDA policy on that front.” 

A longevity state

A major goal for a subset of longevity enthusiasts relates to another controversial idea: creating new geographic zones in which people can live by their own rules. The goal has taken various forms, including “network states” (which could start out as online social networks and evolve into territories that make use of cryptocurrency), “special economic zones,” and more recently “freedom cities.” 

While specific details vary, the fundamental concept is creating a new society, beyond the limits of nations and governments, as a place to experiment with new approaches to rules and regulations. 

In 2023, for instance, a group of longevity enthusiasts met at a temporary “pop-up city” in Montenegro to discuss plans to establish a “longevity state”—a geographic zone with a focus on extending human lifespan. Such a zone might encourage healthy behaviors and longevity research, as well as a fast-tracked system to approve promising-looking longevity drugs. They considered Rhode Island as the site but later changed their minds.

Some of those same longevity enthusiasts have set up shop in Próspera, Honduras—a “special economic zone” on the island of Roatán with a libertarian approach to governance, where residents are able to make their own suggestions for medical regulations. Another pop-up city, Vitalia, was set up there for two months in 2024, complete with its own biohacking lab; it also happened to be in close proximity to an established clinic selling an unproven longevity “gene therapy” for around $20,000. The people behind Vitalia referred to it as “a Los Alamos for longevity.” Another new project, Infinita City, is now underway in the former Vitalia location.

O’Neill has voiced support for this broad concept, too. He’s posted on X about his support for limiting the role of government, writing “Get government out of the way” and, in reference to bills to shrink what some politicians see as government overreach, “No reason to wait.” And more to the point, he wrote on X last November, “Build freedom cities,” reposting another message that said: “I love the idea and think we should put the first one on the former Alameda Naval Air Station on the San Francisco Bay.” 

And up until March of last year, according to his financial disclosures, he served on the board of directors of the Seasteading Institute, an organization with the goal of creating “startup countries” at sea. “We are also negotiating with countries to establish a SeaZone (a specially designed economic zone where seasteading companies could build their platforms),” the organization explains on its website.

“The healthiest societies in 2030 will most likely be on the sea,” O’Neill told an audience at a Seasteading Institute conference in 2009. In that presentation, he talked up the benefits of a free market for health care, saying that seasteads could offer improved health care and serve as medical tourism hubs: “The last best hope for freedom is on the sea.”

Some in the longevity community see the ultimate goal as establishing a network state within the US. “That’s essentially what we’re doing in Montana,” says A4LI’s Livingston, referring to his successful lobbying efforts to create a hub for experimental medicine there. Over the last couple of years, the state has expanded Right to Try laws, which were originally designed to allow terminally ill individuals to access unproven treatments. Under new state laws, anyone can access such treatments, providing they have been through an initial phase I trial as a preliminary safety test.

“We’re doing a freedom city in Montana without calling it a freedom city,” says Livingston.

Patri Friedman, the libertarian founder of the Seasteading Institute, who calls O’Neill “a close friend,” explains that part of the idea of freedom cities is to create “specific industry clusters” on federal land in the US and win “regulatory carve-outs” that benefit those industries. 

A freedom city for longevity biotech is “being discussed,” says Friedman, although he adds that those discussions are still in the very early stages. He says he’d possibly work with O’Neill on “changing regulations that are under HHS” but isn’t yet certain what that might involve: “We’re still trying to research and define the whole program and gather support for it.”

Will he deliver?

Some libertarians, including longevity enthusiasts, believe this is their moment to build a new experimental home. 

Not only do they expect backing from O’Neill, but they believe President Trump has advocated for new economic zones, perhaps dedicated to the support of specific industries, that can set their own rules for governance. 

While campaigning for the presidency in 2023, Trump floated what seemed like a similar idea: “We should hold a contest to charter up to 10 new cities and award them to the best proposals for development,” he said in a recorded campaign speech. (The purpose of these new cities was somewhat vague. “These freedom cities will reopen the frontier, reignite the American imagination, and give hundreds of thousands of young people and other people—all hardworking families—a new shot at homeownership and in fact the American dream,” he said.)

But given how frequently Trump changes his mind, it’s hard to tell what the president, and others in the administration, will now support on this front. 

And even if HHS does try to create new geographic zones in some form, legal and regulatory experts say this approach won’t necessarily speed up drug development the way some longevity enthusiasts hope. 

“The notion around so-called freedom cities, with respect to biomedical innovation, just reflects deep misunderstandings of what drug development entails,” says Ohio State’s Zettler. “It’s not regulatory requirements that [slow down] drug development—it’s the scientific difficulty of assessing safety and effectiveness and of finding true therapies.”

Making matters even murkier, a lot of the research geared toward finding those therapies has been subject to drastic cuts.The NIH is the largest funder of biomedical research in the world and has supported major scientific discoveries, including those that benefit longevity research. But in late March, HHS announced a “dramatic restructuring” that would involve laying off 10,000 full-time employees. Since Trump took office, over a thousand NIH research grants have been ended and the administration has announced plans to slash funding for “indirect” research costs—a move that would cost individual research institutions millions of dollars. Research universities (notably Harvard) have been the target of policies to limit or revoke visas for international students, demands to change curricula, and threats to their funding and tax-exempt status.

The NIH also directly supports aging research. Notably, the Interventions Testing Program is a program run by the National Institutes of Aging (a branch of the NIH) to find drugs that make mice live longer. The idea is to understand the biology of aging and find candidates for human longevity drugs.

The ITP has tested around five to seven drugs a year for over 20 years, says Richard Miller, a professor of pathology at the University of Michigan, one of three institutes involved in the program. “We’ve published eight winners so far,” he adds.

The future of the ITP is uncertain, given recent actions of the Trump administration, he says. The cap on indirect costs alone would cost the University of Michigan around $181 million, the university’s interim vice president for research and innovation said in February. The proposals are subject to ongoing legal battles. But in the meantime, morale is low, says Miller. “In the worst-case scenario, all aging research [would be stopped],” he says.

The A4LI has also had to tailor its lobbying strategy given the current administration’s position on government-funded research. Alongside its efforts to change Montana state law to allow clinics to sell unproven treatments, the organization had been planning to push for an all-new NIH institute dedicated to aging and longevity research—an idea that O’Neill voiced support for last year. But current funding cuts under the new administration suggest that it’s “not the ideal political climate for this,” says Livingston.

Despite their enthusiasm for O’Neill’s confirmation, this has all left many members of the longevity community, particularly those with research backgrounds, concerned about what the cuts mean for the future of longevity science.

“Someone like [O’Neill], who’s an advocate for aging and longevity, would be fantastic to have at HHS,” says Matthew O’Connor, who spent over a decade at SRF and says he knows O’Neill “pretty well.” But he adds that “we shouldn’t be cutting the NIH.” Instead, he argues, the agency’s funding should be multiplied by 10.

“The solution to curing diseases isn’t to get rid of the organizations that are there to help us cure diseases,” adds O’Connor, who is currently co-CEO at Cyclarity Therapeutics, a company developing drugs for atherosclerosis and other age-related diseases. 

But it’s still just too soon to confidently predict how, if at all, O’Neill will shape the government health agencies he will oversee. 

“We don’t know exactly what he’s going to be doing as the deputy secretary of HHS,” says Public Citizen’s Steinbrook. “Like everybody who’s sworn into a government job, whether we disagree or agree with their views or actions … we still wish them well. And we hope that they do a good job.”