When testing an AI model, it’s hard to tell if it is reasoning or just regurgitating answers from its training data. Xbench, a new benchmark developed by the Chinese venture capital firm HSG, or HongShan Capital Group, might help to sidestep that issue. That’s thanks to the way it evaluates models not only on the ability to pass arbitrary tests, like most other benchmarks, but also on the ability to execute real-world tasks, which is more unusual. It will be updated on a regular basis to try to keep it evergreen.
This week the company is making part of its question set open-source and letting anyone use for free. The team has also released a leaderboard comparing how mainstream AI models stack up when tested on Xbench. (ChatGPT o3 ranked first across all categories, though ByteDance’s Doubao, Gemini 2.5 Pro, and Grok all still did pretty well, as did Claude Sonnet.)
Development of the benchmark at HongShan began in 2022, following ChatGPT’s breakout success, as an internal tool for assessing which models are worth investing in. Since then, led by partner Gong Yuan, the team has steadily expanded the system, bringing in outside researchers and professionals to help refine it. As the project grew more sophisticated, they decided to release it to the public.
Xbench approached the problem with two different systems. One is similar to traditional benchmarking: an academic test that gauges a model’s aptitude on various subjects. The other is more like a technical interview round for a job, assessing how much real-world economic value a model might deliver.
Xbench’s methods for assessing raw intelligence currently include two components: Xbench-ScienceQA and Xbench-DeepResearch. ScienceQA isn’t a radical departure from existing postgraduate-level STEM benchmarks like GPQA and SuperGPQA. It includes questions spanning fields from biochemistry to orbital mechanics, drafted by graduate students and double-checked by professors. Scoring rewards not only the right answer but also the reasoning chain that leads to it.
DeepResearch, by contrast, focuses on a model’s ability to navigate the Chinese-language web. Ten subject-matter experts created 100 questions in music, history, finance, and literature—questions that can’t just be googled but require significant research to answer. Scoring favors breadth of sources, factual consistency, and a model’s willingness to admit when there isn’t enough data. A question in the publicized collection is “How many Chinese cities in the three northwestern provinces border a foreign country?” (It’s 12, and only 33% of models tested got it right, if you are wondering.)
On the company’s website, the researchers said they want to add more dimensions to the test—for example, aspects like how creative a model is in its problem solving, how collaborative it is when working with other models, and how reliable it is.
The team has committed to updating the test questions once a quarter and to maintain a half-public, half-private data set.
To assess models’ real-world readiness, the team worked with experts to develop tasks modeled on actual workflows, initially in recruitment and marketing. For example, one task asks a model to source five qualified battery engineer candidates and justify each pick. Another asks it to match advertisers with appropriate short-video creators from a pool of over 800 influencers.
The website also teases upcoming categories, including finance, legal, accounting, and design. The question sets for these categories have not yet been open-sourced.
ChatGPT-o3 again ranks first in both of the current professional categories. For recruiting, Perplexity Search and Claude 3.5 Sonnet take second and third place, respectively. For marketing, Claude, Grok, and Gemini all perform well.
“It is really difficult for benchmarks to include things that are so hard to quantify,” says Zihan Zheng, the lead researcher on a new benchmark called LiveCodeBench Pro and a student at NYU. “But Xbench represents a promising start.”
Large language models such as ChatGPT generate answers to prompts by querying massive, publicly available training data. The queries address the initial prompt plus additional info likely relevant to users’ needs and then consolidate the findings into a single, comprehensive response.
The additional queries extend beyond the literal text of the prompt. Hence Google coined the term “fan-out queries” earlier this year to describe the tactic.
Knowing the fan-out queries associated with an initial prompt helps publishers understand the platform’s interpretations and priorities.
Two new tools reveal those queries in ChatGPT. These tools work only for ChatGPT’s web searches and only in Google Chrome.
The SEO Pub
The SEO Pub is a newsletter and community from Mike Friedman, a search engine optimizer and owner of Clicked Consulting. His “ChatGPT Search Reasoning and Query Extractor” is a free Chrome bookmarklet to access the platform’s fan-out web queries and reasoning when compiling an answer.
For example, for a prompt of “best headphones for running,” ChatGPT’s fan-out searches, per the bookmarklet, were:
“Shokz OpenRun Pro 2 review running 2025”
“Beats Fit Pro 2025 review running”
“Jabra Elite 8 Active review sweatproof”
“Soundcore Sport X20 earbuds review”
“Bose Ultra Open Earbuds running review”
“best running headphones 2025 Runner’s World”
“AirPods Pro USB-C 2nd gen running sweat test review”
“Sony LinkBuds S running comfort review 2024”
“JLab Go Air Sport review running 2024.”
And ChatGPT’s reasoning was enlightening, especially for content marketers and product developers:
The user is asking for a comparison of the best headphones for running. This likely means recommending models with features like a secure fit, being sweatproof, and having a transparency mode. I’ll need to gather the latest info for 2025 models. It’s not location-specific, but it feels like a shopping query, so I should focus on up-to-date reviews and comparison of features, pricing, and performance. I’ll browse for the most current models to include in the recommendation.
The bookmarklet enables users to view and export the searches and reasoning on an easy-to-read page.
Users can view and export ChatGPT’s fan-out searches and reasoning. Click image to enlarge.
To install the bookmarklet,
Create a new bookmark in Chrome.
Assign a name such as “ChatGPT Extractor” or similar
Replace the URL field with the code on the SEO Pub page
Go to ChatGPT and perform a search that triggers a web search
Once you have results, click the bookmarklet. It will open a new tab showing ChatGPT’s searches and reasoning.
Fan-out Helper
Another free tool, a Chrome extension called “ChatGPT Search Fan-out Helper,” saves ChatGPT’s fan-out queries and sources, providing the URLs, titles, and descriptions.
Jill Whalen, a true SEO pioneer, recently passed away. Although she has been retired for over ten years, her influence continues in the marketing-first SEO practices she advocated that are gradually gaining ground thirty years after she first championed that approach to ranking websites.
Contributions To SEO
As part of the first wave of SEO, her contribution to search marketing was to prove that a marketing-first approach was sustainable as a long-term strategy. While that style of SEO is described as white hat, that term has lost meaning as many of the SEOs with the biggest and whitest hats tended to be algorithm chasers jumping from strategy to strategy, something Whalen was not.
Many of the second-wave SEOs from my generation focused on testing the limits of search engine algorithms and reading research papers to better understand how search engines worked. Whalen remained steadily focused on creating the kind of content search engines were trying to rank and used responsible link building to promote it, which turned out to be a winning strategy.
Screenshot Of Jill Whalen On SEO Pioneers Show
Left to right: Jill Whalen, Shelley Walsh
Her approach may have felt old-fashioned to some in the industry at the time, but she recently observed in an interview on Shelley Walsh’s SEO Pioneers show that she felt vindicated after Google’s Panda and Penguin algorithms, which rocked the search marketing industry but left her clients’ top-ranked websites untouched. Indeed, the entire SEO industry is coming around to Jill’s approach to SEO.
Whalen retired in 2013 and turned her attention to subjects that mattered to her, but her influence has always been felt through the thousands of SEOs who learned from her and who continue to pass those traditions on.
How Jill Whalen Influenced Top SEOs
Christine Churchill
Christine Churchill (LinkedIn profile), a leading search marketer, explains how she met Jill Whalen and how she influenced her life and career.
“Wow, this loss really stings! I first met Jill at a speakers’ gathering that I almost skipped because I was dreading feeling out of place. I told myself to just go for five minutes, and when I walked in, I spotted Jill right away – the only other woman there. She flashed me a warm smile, and I found my way over to the bar where she was sitting. I was so nervous, but I was completely taken aback when she mentioned she had seen me speak at an earlier conference and actually knew who I was!
We ended up chatting until the bar closed, and from that night on, we bonded instantly. Jill had this incredible gift of helping us believe in ourselves and encouraging us to shine. Because of her, I also met amazing people like Debra Mastaler, Scottie Claibourne, Karon Thackston, Kim Krause Berg and so many more kindred spirits. We all became friendly faces in the crowd, supporting each other in countless ways.
Jill truly changed my life, and I got to travel the world alongside her! Even when she retired and we didn’t see each other as much, I always knew that if I needed a friend, she’d be just a call away.
I still remember that one conference (I think it was in Pennsylvania) where we met this fascinating guy who talked to ghosts. We ended up staying at the bar yet again, discussing spirits and the signs our departed loved ones send us. It feels like Jill is with all of us now, saying goodbye and cheering us on to keep blooming.
Thank you, Jill, for your incredible friendship and support. I’ll cherish my memories of you forever!”
Debra Mastaler
My good friend Debra Mastaler (LinkedIn profile) was one of Whalen’s early collaborators, handling link building. Debra shares how Jill was instrumental in shaping her career in SEO:
“I’ve been involved with the SEO industry since 1999, I started by owning a directory of organic food and clothing. When I started to rank well for a large number of money terms, business owners advertising in my directory asked if I could I help them “optimize” their sites. I had no clue what that meant so I started looking around for information and met Jill.
Jill took the time to explain what I was doing was called link building and how important it was. One thing led to another and she hired me to do all her link work and got me on the speaking circuit. About a year later, I felt confident enough to work on my own and I launched Alliance-Link.
Over the years, we traveled together, went to conferences, ran an SEO forum, published content together, shared family vacations and spoke almost every day. We drifted after she left the SEO industry but her mark on my life has never faded.”
Left to right: Debra Mastaler, Christine Churchill, Jill Whalen
Michael Bonfils
Multilingual International SEO Michael Bonfils (LinkedIn profile), also an SEO pioneer himself, nce before SEO described who she was and how she influenced him.
“Twenty five years ago while attending one of the first SES (Search Engine Strategies) conferences in San Francisco, I noticed this incredibly enthusiastic lady who was leading a roundtable discussion about content. There were three things that struck me that I never forget.
First, she was one of the few women in a sea of nerdy dudes but as nerdy as she was, she fit perfectly in with everyone else.
Second, she was nervous about speaking, she didn’t say it, but I can see it. I could feel it. It made me happy to know that I wasn’t alone and it was that nervousness that drew me to be one of the first few that sat around her roundtable.
Third, she explained the power of content in SEO better than anyone else. While everyone was focused on tricking the search engines, she was focused on feeding the search engines exactly what they wanted (I was working for a search engine at the time, so this was important for me to hear.)
From the beginning of her career, I’ve had so much respect for Jill that her and I over the decades would often talk about the good old days when everyone and everything in SEO was so uncertain. When she retired, I told her how bummed I was and then I of course accused her of faking it.
I am really going to miss Jill and just broken hearted to learn of her passing. She was truly a legend.”
Duane Forrester
Duane Forrester (LinkedIn profile, formerly of Bing) described how Jill Whalen helped him understand how to explain complex ideas in ways that were understandable to a wide audience.
“Yeah, safe to say that Jill influenced my sense of direction. I mean, I knew it was about working for/with the algorithms, but there had to be a balance. Not just in terms of the work, but how we explained it. Jill helped set me, personally, on a path of trying to explain the complex in ways that everyday business people could understand and adapt to.
Jill was adept at looking through the complex and finding ways forward that not only worked, but were approachable by a wide variety of people with various skills and skill levels. She had a sharp mind and managed to recall volumes of relevant information seemingly effortlessly.
It was always a highlight of any conference to cross paths with Jill. We lost a treasure and I, and I’m sure many, will miss her.”
Bill Hartzer
Bill Hartzer (LinkedIn profile), one of the sharpest technical SEOs I know, remembered her as a centering voice, one who brought balance back to SEO.
He shared:
“She definitely was an influence, as she was more the “voice of reason” so to speak, when I was always trying to test the limits, test that “fine line” between white hat SEO and gray hat SEO.
She consistently advocated for doing SEO “the right way,” which is with integrity, transparency, and a focus on long-term value. Her work through High Rankings became a trusted symbol of ethical search marketing, long before it became the norm.”
Brett Tabke
Brett Tabke (LinkedIn profile), one of the leading founders of modern SEO, remembered her as a positive influence.
“She was always so nice. Had a smile on her face 90% of the time you were with her. I can’t remember a time when she didn’t appear happy to be with her friends. Even when she was presenting, she always made you feel good about what we were doing.”
Watch The SEO Pioneers Interview With Jill Whalen
Featured Image/Screenshot from SEO Pioneers interview
OpenAI CEO Sam Altman says ChatGPT has moved beyond being a Google alternative. Instead, the platform is increasingly focused on helping users complete complex tasks and workflows.
“For a long time ChatGPT was like a Google replacement… it still felt like a more advanced version of search.”
Now, he said, users can ask the AI to perform complex work like a junior employee.
“You can really give a task to code interpreter for example or to deep research… and come back to you with like a proposal.”
This shift signals a new direction for ChatGPT that could affect how businesses and marketers use AI.
Not Just Search Anymore
Altman emphasized that ChatGPT is no longer just about retrieving information. The goal now is to help users get work done.
Altman said:
“It’s like a very junior employee that can work on something for like a short period of time.”
While the platform gets considerable traffic, Altman said ChatGPT.com is now the fifth most visited site in the world, he downplayed the idea that it’s competing with Google Search.
Instead, OpenAI is building a tool that can connect to user data, complete tasks, and act proactively.
Memory & Persistent AI Assistants
A step toward this vision is ChatGPT’s memory feature. Altman called it his favorite feature so far this year.
This lets the AI remember previous conversations and user preferences, acting more like a personal assistant than a chatbot.
“I think memory is the first time where people can sort of see that coming.”
Altman described a future where the assistant knows when to notify users and when to take action automatically.
Reasoning & Workflow Automation
New models like GPT-4o and O3 are designed to handle more complex reasoning and workflows.
“Right now we’re in an interesting time where the product overhang relative to what the models are capable of is here…”
Altman said the technology is moving faster than most businesses can adapt to it. He sees untapped potential in how AI could support work like marketing, data analysis, and content development.
Balancing the Vision
While Altman outlined an ambitious vision, there’s reason to be cautious.
Tools like ChatGPT face limitations like hallucinated outputs, lack of persistent memory across all contexts, and occasional reasoning failures. This is all detailed in OpenAI’s own reports.
That means, even with tools like Code Interpreter or GPT-4o, complex tasks still require hands-on oversight.
The shift away from search competition may also reflect the difficulty of challenging Google’s market dominance. Instead, OpenAI may be trying to define a new space for AI-powered task automation.
Looking Ahead
As AI tools like ChatGPT gain new features, they may change how marketers, developers, and everyday users complete tasks.
However, much of this vision depends on overcoming current limitations and delivering reliable performance across different use cases.
Altman shared that ChatGPT will soon support the Model Context Protocol (MCP). This allows it to pull data directly from tools and platforms businesses already use.
These integrations further support ChatGPT’s positioning as an assistant platform rather than a search engine alternative.
For now, marketers should focus on utilizing AI tools alongside, not instead of, traditional platforms like search engines. The two can serve different purposes in the same strategy.
Listen to the full interview with Sam Altman below:
YouTube is rolling out updates to its Advanced Mode analytics in YouTube Studio.
The changes are designed to make data easier to access and interpret, particularly for creators and marketers who may not use these tools regularly.
Among the new features are custom report saving and a simplified interface that reduces visual clutter without removing functionality.
YouTube’s Advanced Analytics: What’s New?
New Interface
YouTube’s analytics team walked through the updates in a recent video, which you can see below:
The redesigned layout includes a new sidebar that puts filters, breakdowns, and metric selectors in one place. This allows you to make changes from any analytics page.
Save Your Favorite Reports
You can now save custom report configurations. This feature eliminates the need to reset filters and metrics every time you check the same data.
After configuring a report, click the Save button and assign a name to the report. Saved reports are accessible from the top navigation and are private to the logged-in user on that channel.
For example, a creator monitoring traffic sources for long-form content can save that specific setup and return to it without rebuilding the report.
Smarter Search & Filtering
The update improves how you find and sort content in Advanced mode:
Search by title: Quickly locate specific videos within analytics.
New sorting options: Sort by video length or publish date.
Multi-metric selection: Add or remove several metrics at once.
Hide chart view: Focus on data tables without visual distractions.
The updated breakdown picker includes options like geography, content type, and revenue sources. New filters help narrow down data to the most useful metrics.
Easier Access to Common Reports
YouTube has added shortcuts to frequently used reports. These include:
First 24 Hours: Compare video performance during the first day after publishing.
Audience Retention: Access viewer engagement data more easily.
Comparison tools: Compare metrics, videos, content groups, or audience segments like age and gender.
Like other reports, these can also be saved for future use.
Why This Matters
These changes make it easier to track performance without needing to reconfigure data views.
For example, the ability to compare playlists and demographic groups can support more targeted content planning. Saved reports help streamline recurring tasks like client reporting or internal reviews.
Teams can also experiment with formats and strategies more efficiently by using the built-in comparison tools to analyze what works best.
Availabilitiy
The updates are rolling out to creators gradually. Once available, the redesigned Advanced Mode can be accessed from any analytics page in YouTube Studio.
The meta description summarizes a page’s content and presents it to users in the search results. It’s one of the first things people will likely see when searching for something, so optimizing it is crucial for SEO. It’s your chance to persuade users to click on your result! This post will show you the characteristics of a good meta description and how Yoast SEO can help you get it right.
The meta description is an HTML tag you can set for a post or page of your website. In it, you can use roughly 155 characters to describe what your page is about. If you’re lucky, Google will show it beneath your page’s title in the search results. It allows you to convince search engine users that your page will offer what they are looking for.
In Google’s search results, this is where it can be displayed:
A meta description from yoast.com as seen in the search results
And this is what it looks like in the HTML code of the page:
The purpose of a meta description is simple: it needs to get someone searching with a search term on Google to click your link. In other words, meta descriptions are there to generate click-throughs from search engines.
Search engines say there is no direct SEO benefit from the meta description – they don’t use it in their ranking algorithm. But there is an indirect benefit: Google uses click-through rate (CTR) to determine whether you’re a good result. If more people click on your result, Google considers you to be a good result and will, based on your position, move you up the rankings. This is why optimizing your meta description is important, as is optimizing your titles.
Here’s a list of elements you need to write a good meta description:
Keep it up to 155 characters
Use an active voice and make it actionable
Include a call to action
Use your focus keyphrase
Show specifications when needed
Make sure it matches the content of the page
Make it unique
Let’s go over them in detail!
1. Keep it up to 155 characters
The right length doesn’t exist; it depends on the message you want to convey. You should take enough space to convey the message, but keep it short and snappy. However, if you check the search results in Google, you’ll mostly see snippets of 120 to 156 characters, like in the example below. Google says you can make your meta descriptions as long as you want, but there is a limit to what we can see in the SERPs — and that’s around 155 characters; anything longer will get truncated.
This search result from a Yoast SEO user shows a succinct meta description in Google
Unfortunately, you can’t fully control what Google displays in the search results. Sometimes, it shows the meta description, and sometimes, it just grabs some sentences of your copy or generates something itself. Either way, your best bet is to keep it short. That way, if Google does decide to show the description you’ve written, it won’t be cut short.
2. Use active voice and make it actionable
If you see the meta description as an invitation to visit your page, you have to think about your user and their (possible) motivation to visit your page. Ensure your description isn’t dull, difficult, or too cryptic. People need to know what they can expect to find on your page.
The example in the image below is the description you should strive to write. It’s active, speaks to you, and addresses you directly. You know what you’ll get if you click on the link!
Make people want to click your search result
3. Include a call-to-action
“Hello, we have a new product, and you want it. Find out more!” This overlaps with what we said about the active voice, but we wanted to emphasize it again. The meta description is your sales text. In this case, the “product” you are trying to sell is the linked page. Invitations like Learn more, Get it now, Try for free come in handy, and we use them too.
Get people to click on your link
4. Use your focus keyword
If the search keyword matches a part of the text in the meta description, Google will be more inclined to use it and highlight it in the search results. This will make the link to your site even more inviting. Google sometimes even highlights synonyms. In the example below, both the Academy Awards and Oscars are highlighted. Getting your results emphasized like that makes them stand out even more.
A listing for the Academy Awards on Google
5. Show specifications, where possible
If you have a product in your Shopify or WooCommerce store aimed at the tech-savvy, it can be a good idea to focus on the technical specs. For example, you can include the manufacturer, SKU, price, etc. If the visitor specifically seeks that product, you won’t have to convince them. Can the watch help us stay fit? Sign us up; that’s all we need to know. Note that to optimize your result in this manner, you should work on getting rich snippets.
Make it spark
6. Make sure it matches the content of the page
This is an important one. Google will find out if you use meta descriptions to trick visitors into clicking on your results. They might even penalize you if you do it. But besides that, misleading descriptions will also increase your bounce rate. Which will also lower people’s trust in your company. It’s a bad idea for that reason alone. That is why you want the meta description to match the content on the page.
7. Make it unique
Adding the date to the snippet preview
People often ask questions about the date shown in the Google preview of our Yoast SEO plugin. We’ve added this because search engines may display a date with your snippet. So it’s important to factor it in when you decide on the right length of your meta description. Unfortunately, there’s no way to directly control whether this date is shown or not, but you can try to manage the dates they use in the search results.
If your meta description is the same as those for other pages, the user experience in Google will be hampered. Although your page titles might vary, all pages will appear the same because all the descriptions are identical. Instead of creating duplicate meta descriptions, you’d better leave them blank. Google will pick a snippet from the page containing the keyword used in the query. That being said, writing a unique meta description for every page you want to rank is always the best practice.
Adding a meta description is easy if you’re on WordPress or Shopify and using Yoast SEO. Firstly, you can write it in the Search appearance preview section of Yoast SEO. But Yoast SEO also gives you feedback on it in the SEO analysis. The plugin checks the meta description length and whether you’ve used your focus keyphrase. So, let’s see how the plugin helps you and what you can do with it.
Using AI to generate meta descriptions in Yoast SEO Premium
Yoast SEO Premium has our Yoast AI Generate features, which include AI-powered meta description generation. This meta description generator brings the power of generative AI to your fingertips, producing engaging and SEO-optimized meta descriptions with just one click. Using advanced algorithms and machine learning techniques, it generates creative and appealing meta descriptions, captivating your audience while meeting search engine standards.
Creating meta descriptions with a little help from generative AI in Yoast SEO Premium
This feature simplifies your meta description optimization process and fully complies with best SEO practices. It enhances user experience, amplifies your website’s visibility, and effortlessly directs high-quality, organic traffic to your site. With this outstanding AI generator, effortlessly elevate your SEO performance and generate outstanding meta descriptions that set you apart.
You can edit your meta description in Yoast SEO
You can edit your meta description in Yoast SEO for Shopify
What does the keyphrase in meta description assessment in Yoast SEO do?
This check is all about using the keyphrase in the meta description. A focus keyphrase is the search term you want a page to rank for. When people use that term, you want them to find your page. You base your keyphrase on keyword research. After your research, you should end up with a combination of words that most of your audience will likely search for. We’ve already discussed that when you use your keyphrase in the meta description, Google will likely highlight it. That makes it easier for people to see they’ve found what they are looking for.
Yoast SEO checks if and how often you use the words from your focus keyphrase in the meta description text. In addition, if you use Yoast SEO Premium, it also considers the synonyms you enter. If you overdo it, the plugin advises you to limit the use of your focus keyphrase.
What a green bullet looks like in Yoast SEO
What a green bullet looks like in Yoast SEO for Shopify
How to get a green traffic light for the keyphrase in meta description
You’ll get a red traffic light if you don’t mention the keyphrase in the meta description. So, make sure to write one. But don’t stuff your meta description with your keyphrase because that will also get you a red traffic light. And make sure to mention all the words from your keyphrase near each other. Search engines are pretty smart nowadays, but you must clarify what your page is about.
Yoast SEO Premium plugin considers the synonyms you’ve added when it performs its analysis. This allows you to write more naturally, resulting in a more pleasant text. Moreover, it’s easier to score a green traffic light this way. Use it to your advantage!
Unlock all features in Yoast SEO Premium
Save time on your SEO and get access to all of our SEO courses.
What does the meta description length assessment do?
This meta description length assessment measures whether your description is too short (less than 120 characters) or too long (more than 156 characters). You’ll get a green traffic light when your meta description has the right length. If it’s too long or too short, you’ll get an orange traffic light in the SEO analysis of Yoast SEO (or red if you’ve marked your article as cornerstone content).
What the check looks like in the Yoast SEO sidebar
A green bullet in the Yoast SEO for Shopify app
How to write a concise meta description
A good meta description convinces people that your page offers the best result for their query. But, to be the best result, you must know what people seek. What is their search intent? Are they looking for an answer to a question? If they are, try to give them the most complete answer. Are they looking for a product? Write down what makes your product stand out and why they would best buy it in your store. Be concise and convincing!
You get real-time feedback on the meta description length in the Search appearance section in the Yoast SEO sidebar or meta box. Click “Search appearance” in the Yoast SEO sidebar to write a meta description. This will open the snippet editor, and you’ll see input fields for editing the SEO title, the slug, and the meta description. When you start typing in the meta description input field, the snippet preview at the top of the Search appearance editor will immediately show your new text. Underneath the input field, there is a bar. It’s orange when you start typing and will become green when you’ve added enough information. When you add too much text, it will turn orange again.
The bar will change color when your go over the limit
Checking the Google preview in Yoast SEO for Shopify
Writing or editing your meta description in the Yoast SEO meta box underneath your post editor is also possible. Go to the SEO tab in the meta box (if it’s not on this tab by default), and you can start typing in the field under Meta description immediately.
What to do if you need meta descriptions for a lot of pages?
After reading this, do you need to change all your meta descriptions? But are you not sure how to fit that into your schedule? Google has the answer:
“If you don’t have time to create a description for every single page, try to prioritize your content; at the very least, create a description for the critical URLs like your home page and popular pages.“
If you prefer to write a unique description for each page and have much to get through, you can use the Bulk editor tool in Yoast SEO for WordPress. Head to the Tools page, click ‘Bulk editor’, then select the ‘Description’ tab. You’ll be able to see any meta descriptions already set for your pages, and you can quickly add new ones without opening each page individually. However, with this tool, you won’t get warnings if your description is too short/long, or if the focus keyword is missing.
Preventing snippets with Yoast SEO
Yoast SEO provides an easy way to control search result snippets using the nosnippet meta tag feature. This setting lets you prevent Google from displaying any snippet for particular pages, giving you control over what appears in search results. It’s especially useful when you want to prioritize privacy or ensure that content is not shown without its full context. With the nosnippet tag, you have another way to manage snippet creation and to align everything with your content strategy.
Yoast SEO lets you easily add the nosnippets robots tag in the Advanced settings
Do you have Yoast SEO? Check the Social media appearance in the Yoast SEO sidebar or social tab in the Yoast SEO meta box below your post or page. You can add a separate description for your social media channels there. In Yoast SEO Premium, you even have social previews that show you what your post or page will look like when shared on social media.
Conclusion to meta descriptions
Meta descriptions are a crucial yet often underestimated component of SEO — even if these are not fully in your control. It serves as a brief advertisement for your content in search results, influencing click-through rates and user engagement. Crafting clear, compelling, and keyword-rich meta descriptions can significantly enhance your online visibility. In return, it could attract more targeted traffic to your website. While they may not directly impact rankings, their role in driving clicks and conversions is undeniable.
A well-crafted meta description is not just about SEO; it’s about creating a better user experience by providing searchers with a clear, concise preview of what to expect on your page. Of course, Google might think it knows better than you, but that doesn’t mean you shouldn’t put your best foot forward!
Edwin is an experienced strategic content specialist. Before joining Yoast, he worked for a top-tier web design magazine, where he developed a keen understanding of how to create great content.
Google AI Mode, which officially launched in May 2025 and is now available to all U.S. users without a waitlist, represents a significant step forward in how we engage with search.
Powered by Gemini 2.5, this new interface moves beyond AI Overviews by introducing a persistent, conversational assistant that blends AI-generated insights with traditional search results.
Users can toggle between classic results and AI-driven summaries, follow up on queries, and explore longer, more exploratory conversations, all within a single interface.
Unlike AI Overviews or the earlier Search Generative Experience (SGE), which provided a single AI-generated answer for a traditional search query, AI Mode is more similar to ChatGPT in that it fosters a conversational approach to finding answers.This marks a change in how people interact with search, moving from short, isolated keywords to more natural prompts that sound like how we talk and think.
AI Mode supports rich interactions and longer queries, encouraging a deeper and more nuanced engagement with information. And when user behavior shifts, advertisers must adapt how they reach users with relevant solutions and offers.
We’re now at another junction where advertisers and Google must work together to evolve how we operate to remain successful. That means reconsidering everything from targeting and attribution to monetization and ad design.
AI Mode Interface (Screenshot from Google, June 2025)
In this post, I share my thoughts on what AI Mode signals for the future of search, how it challenges long-standing digital advertising models, and why marketers need to adapt fast or risk being left behind.
Strategic Motives: Innovation Vs. Defense
Is Google pushing AI Mode because it sees an opportunity or because it’s responding to pressure from OpenAI and others? The answer is likely both.
Google’s technical leadership is well-established.
DeepMind, a Google company, helped invent the transformer model that underpins GPT. Its Gemini family of models has matured rapidly.
At Google Marketing Live 2025, Sundar Pichai stated that Gemini had taken the lead as the top-performing model, a claim supported by LM Arena’s leaderboard.
Still, Google moves cautiously. As a market leader under regulatory scrutiny, it can’t afford missteps.
The innovation is real, but so is the strategy to protect its dominance by making AI part of its core products before others can take the lead.
I believe Google’s technology is among the best in the world. However, as the company is in the spotlight, they have to be more measured.
Regulatory scrutiny, scale, and legacy expectations mean it can’t move as fast as emerging players, but that doesn’t mean it will always be chasing the lead.
Prompt Complexity And Memory: The Challenge Of Targeting
How users like to find answers is changing from clicking around on a search results page to interacting with an AI assistant.
This evolution from search engine to answer engine introduces a new layer of complexity for advertisers. Prompts in AI Mode aren’t just text; they’re conversations rich with personal context and memory.
Take a user engaging in a long session with AI Mode. Their conversation might include several prompts in a row like this:
“I’m running my first marathon in LA and need good shoes. What do you recommend?”
“By the way, I have plantar fasciitis. I’m not trying to break records, I just need something that won’t wreck my knees.”
“I’m not a fan of bland colors. What brands have something more vibrant in their current line-up?”
The assistant understands the goal and tailors responses to match medical considerations, intent, and emotional tone.
It might include surface stability shoes, recommended inserts, and even factor in training timelines or the expected weather in the city where the marathon will take place.
Now contrast that with a short prompt: “running shoes.”
Simple on the surface, except the assistant remembers that just yesterday, I was at the Adidas store talking to a clerk about shoe fit via my bee.computer wearable, and I used my Ray-Ban Meta glasses to snap a few images of colors I liked.
While this use case is not quite there yet in the real world, I am personally using this technology now, and it’s just a matter of time until all the pieces are connected and the advertiser scenario I described will become real.
Then we’ll see the assistant pick up right where I left off, using multimodal memory to enrich the response with past conversations and visual preferences.
Neither of these interactions can be matched with traditional keyword-based targeting. The assistant’s memory and personalization turn every query into a unique moment.
For advertisers, it’s not just about what was typed; it’s about what the assistant knows.
This creates a richer opportunity for advertisers, but there is a challenge related to targeting because Google Ads was built for keyword advertising, not prompt advertising – and this creates a disconnect.
From Keywords To Prompts: Why The Old Model No Longer Fits
Advertisers bid on terms users might type into the search bar (like “running shoes” or “cheap flights”), and the system will serve relevant ads based on those inputs.
But AI Mode is changing the language of search. Instead of short, isolated keywords, users are starting to use full, conversational prompts that reflect how they naturally speak.
These prompts are often longer, more specific, and packed with nuance that the original ad system wasn’t designed to handle.
To keep things running, Google has introduced a behind-the-scenes workaround: “synthetic keywords.”
These are machine-generated representations that attempt to map modern prompts back into the keyword framework advertisers still rely on. It’s a clever patch, but ultimately a temporary one.
As prompts continue to evolve in complexity and variety, and as memory and personalization shape every query, the keyword as a stable targeting anchor is becoming harder to rely on.
That puts pressure on the entire ad ecosystem. The old model is still functioning, but it’s increasingly out of sync with how people search.
A new system, one built natively for prompts, context, and memory, will eventually need to take its place.
Rethinking Ads In AI Mode: What Comes After Clicks?
The shift toward AI-assisted browsing brings another major challenge: fewer clicks.
If users get what they need from the assistant itself, the need to visit websites diminishes, weakening the foundations of the cost-per-click (CPC) business model.
Slide by Microsoft at Accelerate Roadshow LA, June 2025
But clicks will be more relevant because, unlike in the past, where a click was a user’s initial exploration of your offer, they will now be better informed and further along in their research by the time they visit your site for the first time.
Microsoft research found that purchasing behaviors increased by 53% within 30 minutes of a Copilot interaction, underscoring just how powerful, timely, and AI-embedded suggestions can be.
To stay relevant, ads must feel like part of the conversation. They can’t be disruptive or detached. They need to be embedded, responsive, and helpful, appearing when and where they make the most sense.
Newer performance data shows that ad engagement doubled in some formats when served through Copilot, especially in PMax-powered Shopping and Multimedia Ads.
Crucially, Microsoft has dialed back the volume of ad impressions in Copilot, choosing instead to show ads only when they’re predicted to be highly relevant and useful.
The result? Fewer, better-placed ads that drive stronger outcomes, a model that hints at where Google AI Mode could be headed.
Google has done this before. Its introduction of AdWords transformed ads from flashy banners into useful information. AI Mode demands a similar evolution, one that turns helpfulness into performance.
So, if the traditional way Google makes money becomes broken, let’s look at some options for how they might bridge the gap.
Conversion Inside The Conversation: The Rise Of Affiliate Models And Agents
The most frustrating part for consumers using AI agents to find something to buy is the final step after determining what they want.
Now, they need to hunt for where to buy it, enter a credit card, and deal with the usual minutiae of buying something online.
A better user experience, especially for smaller purchases, would be to tell the agent, “I like it, buy it!” and have the item arrive at your doorstep the next day.
While this zero-click scenario is the best user experience, it is also the most problematic in a CPC world.
This opens the door for reconsidering affiliate and commission-based advertising models. Instead of paying for attention, advertisers pay for action.
Ads become decision-making partners, not just traffic generators. It’s a better fit for how assistants work: focused, efficient, and user-first.
While this wouldn’t be Google’s first attempt at commission-based monetization (previous efforts, such as Buy on Google, Shopping Actions, and Google Express, ultimately shut down due to limited merchant adoption and weak consumer uptake), those models lacked the personalized context that AI Mode now enables.
Even vertical-specific experiments like commission bidding for Hotel Price Ads (retired in 2024) followed the same pattern: strong in theory, but missing the behavioral depth to sustain engagement.
With memory-driven prompts, real-time user needs, and multimodal signals in play, the conditions may finally be right for performance-based pricing to scale in a meaningful, consumer-aligned way.
Monetization Models: Why Subscriptions Aren’t The Future
Monetizing AI-powered search is a hot topic. Startups like Neeva by Sridhar Ramaswamy (Former Google Ads Chief) attempted to replace ads with subscriptions, but user adoption fell short.
Even OpenAI, with its paid ChatGPT Pro tier, sees a vast majority of users opting for free access.
The pattern is clear: Most users won’t pay for general-purpose search tools. Even companies leading in AI anticipate that advertising will remain the dominant revenue stream.
Google’s ad model, tested and refined for decades, is still the best-positioned approach – if it can evolve to match the new user behavior.
Ads In AI Mode
Google has already said it will have ads in AI mode.
To maximize the likelihood of your ads appearing in this environment, it’s advisable to utilize Google’s AI-centric tools, including AI Max in search campaigns, Performance Max, and Demand Gen.
Employing broad match keywords is also crucial, as they facilitate connections with conversational prompts rather than traditional keywords.
However, with the potential decrease in click-through rates, a pertinent question arises: Can fewer clicks on ads sustain the revenue model?
Despite this challenge, I anticipate that advertising will remain the primary revenue stream, even within AI Mode.
It’s noteworthy that OpenAI’s CEO, Sam Altman, has expressed reservations about incorporating ads into AI experiences.
“Currently, I am more excited to figure out how we can charge people a lot of money for a really great automated software engineer or other kind of agent than I am making some number of dimes with an advertising-based model… I kinda just don’t like ads that much.”
Similarly, Google’s co-founders, Larry Page and Sergey Brin, initially opposed the idea of advertising on their search engine. In their 1998 research paper, “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” they wrote:
“We expect that advertising-funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers.”
Despite these initial reservations, both OpenAI and Google have recognized the practicalities of monetization. Google makes nearly 78% of its revenue from ads as of 2024, illustrating its evolution from the original stance of its founders.
So, while the methods and philosophies around advertising in AI experiences have evolved, the necessity for effective monetization strategies remains paramount.
Conclusion: Betting On AI-Powered Ad Innovation
Soon, helping consumers at the moment of relevance won’t be about search and keywords anymore; it’ll be about context, and AI-powered interactions driven by memory, intent, and dialogue.
The early signals are promising: Users respond better when ads are useful, not intrusive.
Microsoft’s experience with Copilot shows that when generative systems deliver fewer but more relevant ads, engagement and conversions rise.
Google’s opportunity is to take those lessons further, baking utility and timing into its AI-native monetization engine.
It’s not about building the flashiest assistant; it’s about earning trust at the moments that matter.
If the assistant can deliver value and drive outcomes without breaking the flow, that’s the model that wins.
I have no doubt that Google and other ad platforms will find ways to appropriately monetize these advertising opportunities, even if there will be fewer impressions for each consumer journey.
The fundamentals of advertising at the moment of relevance haven’t changed, but our tactics will need to evolve fast. Prompts, not keywords, are the new starting point – and that changes the game.
As emerging technologies, particularly AI, reshape B2B marketing strategies, many organizations are shifting resources toward digital transformation to remain competitive.
However, sidelining traditional marketing tactics to prioritize innovation can be a costly misstep.
Traditional channels such as print, direct mail, billboards, and events have considerable value, particularly when they are thoughtfully integrated with digital strategies and real-time demand intelligence.
Combining traditional and digital approaches offers a unique advantage, namely the ability for a brand to stand out in the sea of sameness.
Experiences that blend the old with the new are more likely to capture attention, foster trust, and drive meaningful engagement.
By aligning traditional media with digital insights and delivery systems, marketers can create a cohesive brand-to-demand experience – one that resonates with today’s self-directed, risk-averse buyers.
Here are five high-impact ways to integrate traditional and digital marketing for a more personalized and effective buyer experience.
1. Intent Data Intelligence + One-To-One Conversations
When fueled by intent data intelligence, the cold calls of yesterday become the insight-driven conversations of tomorrow.
Intent data empowers organizations to identify where prospects are within the buyer’s journey and to gauge their level of interest in specific solutions.
This approach transcends cold outreach, enabling marketers and sales teams to engage with prospects who are actively exhibiting buying intent signals.
Before initiating outreach, Go-To-Market (GTM) teams can use intent data to identify:
Prospects actively researching or seeking a solution.
Competing vendors under consideration.
Behavioral signals that reveal sales readiness or indicate the need for a longer nurture path.
Current challenges, questions, and priority search topics shaping buyer decisions.
Organizations can begin capturing meaningful intent signals directly from their own client relationship manager (CRM) and digital ecosystem.
Key first-party intent signals include:
Visits to solution-specific or pillar pages on your website.
Keyword searches aligned with your offerings.
Email engagement metrics, particularly open and click-through rates.
Once foundational tracking is established, GTM teams should consider enhancing their database with firmographic and technographic data.
When integrated thoughtfully into your GTM strategy, intent intelligence allows you to engage buyers with relevant messaging, transforming passive prospects into sales-ready opportunities.
2. Print Media + Deep Media Nurturing
The most effective B2B marketers are meeting the demands of cautious, self-directed buying groups by orchestrating deep media presence that aligns with how prospects prefer to research and engage.
Yet, according to our own Q4 2024 market research, only 22% of marketing teams prioritize the creation of buyer enablement materials, highlighting a significant gap between awareness-building efforts and buyer-centric strategies that support purchase decisions.
The most progressive strategies integrate AI-powered targeting, first-party intent data, and omnichannel delivery systems to ensure buyers receive value at every stage of their journey.
We know that on average, 33-50% of buyers go through seven or more pieces of content during the purchase process. Print media offers a distinct opportunity to break through this noise and command attention.
When informed by behavioral insights and demand intelligence, print media can be strategically activated in niche publications consumed by your target buying groups, delivering a high return on investment.
Here is how B2B buyer intelligence enhances print media experiences:
Predictive analytics and intent signals identify which accounts are most likely to purchase, enabling marketers to prioritize them for print media activation.
Generative AI enables personalization at scale by adapting core messaging across different print formats and channels.
QR codes integrated into compelling print advertisements bridge the physical and digital experience, allowing for trackable engagement and follow-up opportunities.
Print-on-demand and programmatic print technologies make it possible to deliver hyper-personalized physical content with the same agility and precision as digital campaigns.
For marketers focused on brand-to-demand integration, combining technology-enabled media strategies with high-trust formats, such as print, provides a unique and differentiated way to capture buyer attention.
3. Events + ABX
Ensuring that key accounts receive a personalized follow-up experience through an Account-Based Experience (ABX) strategy is an effective way to bridge traditional event marketing with modern, buyer-centric engagement.
ABX enables marketers to connect with prospects before, during, and after an event, creating a cohesive journey that adds value at every stage.
Before the event, contacts can be engaged with targeted nurture streams that build interest and provide relevant insights, effectively “priming” them with content that addresses common pain points, frequently asked questions, or industry trends.
This not only enhances their readiness to engage at the event, but also empowers them with the context to have more meaningful conversations on-site.
For example, if a prospect receives content around B2B buyer advocacy in pre-event nurture, they may arrive at the booth with a deeper understanding of the topic and specific questions in mind.
This creates an opportunity for sales to engage in more relevant, high-value discussions, transforming a standard booth interaction into strategically qualified engagement.
By extending the event experience beyond the show floor, ABX ensures that traditional marketing efforts are amplified through intent-driven, personalized interactions.
This leads to stronger relationships, clearer value exchange, and accelerated pipeline progression.
4. Billboards/Posters + Geotargeting + Nurture
To maximize the effectiveness of traditional advertising platforms such as billboards and posters, marketers can integrate geotargeting to bridge physical impressions with digital engagement.
Geotargeting enables the delivery of tailored follow-up content based on a viewer’s location, allowing billboard placements to align strategically with key account locations, such as near a corporate headquarters or an industry event venue.
When paired with compelling creatives and a clear call to action, such as a short, memorable URL or QR code, billboards can guide viewers to personalized landing pages that extend the message and encourage deeper interaction.
These landing pages can be tailored by industry, buyer stage, or intent signals, further enhancing relevance and conversion potential.
At a more advanced level, mobile location data can be used to identify devices that have passed by a billboard.
This type of geotargeting enables marketers to retarget those individuals with personalized digital nurture campaigns, reinforcing the original message across multiple touchpoints.
By combining location-specific placement with digital activation, billboards evolve from static awareness tools into measurable components of a modern ABX strategy that drives engagement and accelerates pipeline.
5. Direct Mail + Buyer Intelligence
When executed with precision and relevance, direct mail can be a powerful tool for re-engaging prospects who have become unresponsive to digital touchpoints.
A well-timed physical asset can prompt renewed interest, particularly when guided by demand and buyer intelligence.
Technology can play a critical role in elevating direct mail from a generic outreach method in the following ways:
Intent data and predictive analytics, together forming deep data intelligence about the prospect or account, identify when a buying group is entering an active research or purchasing stage, ensuring that direct mail is sent at the most strategic moment.
AI-driven personalization enables messaging tailored to a recipient’s industry, role, behavior patterns, or known tech stack.
Programmatic print technology allows for scalable, real-time production of customized assets such as postcards, letters, or dimensional mailers, triggered by specific prospect actions or buying signals.
Integrated measurement platforms unify physical and digital engagement data, allowing marketers to continuously optimize campaigns.
QR codes and custom landing pages extend the journey, creating a seamless transition from physical to digital.
If five follow-up emails have failed to elicit a response, a sixth is unlikely to succeed. However, a timely and thoughtful piece of direct mail, such as a handwritten note, a tailored infographic, or a personalized token of value, can break through resistance and reinitiate dialogue.
Beyond performance metrics, direct mail also builds trust. When buyers feel recognized and understood, they are more inclined to engage, respond, and move forward in their buying journey.
As part of a broader demand strategy, direct mail plays a key role in creating high-impact, memorable moments that differentiate your brand from the competition.
Key Takeaways
Intent data intelligence turns cold outreach into warm conversations by leveraging behavioral signals to prioritize high-value prospects and boost efficiency.
ABX transforms events into full-funnel experiences through pre-nurture, contextual engagement, and tailored follow-up.
Direct mail, enhanced by demand intelligence and personalization, cuts through digital noise and re-engages prospects with targeted, tangible touchpoints.
With geotargeting, personalization, and integrated measurement, even traditional media becomes seamlessly trackable and conversion-ready.
Retail media has become a significant revenue stream for enterprise-level merchants, but for some, selling ads to suppliers has altered the traditional relationship.
“Because of retail media, the power dynamics have shifted a little bit,” said Drew Cashmore, chief strategy officer at Vantage, a retail media management platform, during an interview.
Retail media has, in some cases, transformed suppliers into advertising clients, forcing retailers to compete for those marketing budgets.
Amazon launched “Product Ads” in 2008, pioneering the practice of online merchants selling advertisements to suppliers, now called “retail media.”
Co-op Advertising
Suppliers have long provided retailers with “cooperative advertising” rebates to promote the suppliers’ products.
Co-op ad budgets are typically 2-3% of a retailer’s total purchases. So a chain that bought $1 million worth of products from a given supplier might receive a rebate of $20,000 or $30,000 to spend on advertising.
Co-op rebates can be a point of negotiation. The buyer at a retailer could, in effect, obtain a discount on product purchases via a higher co-op amount.
Suppliers certainly have input into how retailers employ co-op dollars, including evidence that the merchant spent the funds on advertising. But retailers are typically in charge.
This model gives retailers leverage. Retailers control how funds are spent, and suppliers have limited insight into performance.
But the balance changes with retail media. Suppliers purchasing ads expect transparency, outcomes, and accountability, creating both a challenge and an opportunity for retailers to build stronger, performance-based partnerships.
Retail Media
Co-op ads have not created retail media. Amazon was the catalyst with its 2008 launch of “Product Ads,” followed by a few other ecommerce sites. However, thanks to co-op monies, many traditional retailers seized the opportunity to earn revenue beyond selling goods to consumers.
When it uses cooperative advertising funds to buy magazine ads, a retailer benefits from increased sales, presumably.
If, however, it published a magazine, the retailer could use the same co-op dollars to buy space there. Effectively, this is retail media.
A more formal definition is something like, “Retail media is advertising that retailers sell on their own websites, publications, and in their physical stores.”
Regardless, large merchants view retail media as a way to have cake and eat it, too. The advertising drives the companies’ product sales while generating non-merchandising revenue.
A side effect of moving co-op advertising dollars to retail media is performance.
This shift is significant because it elevates expectations. Suppliers increasingly view retail media as part of their broader digital advertising strategy. They compare it to search, social, and programmatic buys and expect the same level of reporting, targeting, and performance. For retailers, meeting these expectations is key to retaining and growing suppliers’ budgets.
The Dilemma
As Vantage’s Cashmore put it, “The monies that used to go into the retail space … are going to go away unless there’s mutually beneficial value.”
Retailers must prove that their media channels are as effective as competing options. Hence many retailers now act like advertising networks. They provide the tools — reporting, analytics, dashboards — that media buyers at consumer brands are accustomed to receiving, or risk losing the revenue.
Benefits of Winning
Conversely, merchants that excel in retail media can position themselves as critical growth partners to suppliers, strengthening loyalty and unlocking incremental spend that supports both merchandising and marketing goals.
Winning at retail media promises to have several benefits:
Incremental revenue. Retail media generates high-margin income that complements product sales. Once platforms and processes are in place, the ads deliver recurring revenue with low incremental costs.
Increased sales. Retail media can help sell more products.
Strong supplier relationships. Winning at retail media positions the merchant as a key marketing partner, which, in turn, strengthens loyalty and encourages suppliers to allocate larger portions of their advertising budgets to that merchant.
Competitive moat. A well-executed retail media program helps a seller defend its market position against both rival merchants and digital ad networks.
Actionable insights. Retail media provides data on shopper behavior, campaign performance, and category trends. Retailers can utilize these insights to enhance their merchandising, pricing strategies, promotions, and supplier negotiations.
Shopper experience. Thoughtfully targeted retail media offers timely and relevant ads and recommendations, helping to build long-term shopper loyalty.
Living comes with a side effect: aging. Despite what you might hear on social media or in advertisements, there are no drugs that are known to slow or reverse human aging. But there’s some evidence to support another approach: cutting back on calories.
Caloric restriction (reducing your intake of calories) and intermittent fasting (switching between fasting and eating normally on a fixed schedule) can help with weight loss. But they may also offer protection against some health conditions. And some believe such diets might even help you live longer—a finding supported by new research out this week. (Longevity enthusiast Bryan Johnson famously claims to eat his last meal of the day at 12pm.)
But the full picture is not so simple. Weight loss isn’t always healthy and neither is restricting your calorie intake, especially if your BMI is low to begin with. Some scientists warn that, based on evidence in animals, it could negatively impact wound healing, metabolism and bone density. This week let’s take a closer look at the benefits—and risks—of caloric restriction.
Eating less can make animals live longer. This remarkable finding has been published in scientific journals for the last 100 years. It seems to work in almost every animal studied—everything from tiny nematode worms and fruit flies to mice, rats, and even monkeys. It can extend the lifespan of rodents by between 15% and 60%, depending on which study you look at.
The effect of caloric restriction is more reliable than the leading contenders for an “anti-aging” drug. Both rapamycin (an immunosuppressive drug used in organ transplants) and metformin (a diabetes drug) have been touted as potential longevity therapeutics. And both have been found to increase the lifespans of animals in some studies.
But when scientists looked at 167 published studies of those three interventions in research animals, they found that caloric restriction was the most “robust.” According to their research, published in the journal Aging Cell on Wednesday, the effect of rapamycin was somewhat comparable, but metformin was nowhere near as effective.
“That is a pity for the many people now taking off-label metformin for lifespan extension,” David Clancy, lecturer in biogerontology at Lancaster University, said in a statement. “Let’s hope it doesn’t have any or many adverse effects.” Still, for caloric restriction, so far so good.
At least it’s good news for lab animals. What about people? Also on Wednesday, another team of scientists published a separate review of research investigating the effects of caloric restriction and fasting on humans. That review assessed 99 clinical trials, involving over 6,500 adults. (As I said, caloric restriction has been an active area of research for a long time.)
Those researchers found that, across all those trials, fasting and caloric restriction did seem to aid weight loss. There were other benefits, too—but they depended on the specific approach to dieting. Fasting every other day seemed to help lower cholesterol, for example. Time-restricted eating, where you only eat within a specific period each day (à la Bryan Johnson), by comparison, seemed to increase cholesterol, the researchers write in the BMJ. Given that elevated cholesterol in the blood can lead to heart disease, it’s not great news for the time-restricted eaters.
Cutting calories could also carry broader risks. Dietary restriction seems to impair wound healing in mice and rats, for example. Caloric restriction also seems to affect bone density. In some studies, the biggest effects on lifespan extension are seen when rats are put on calorie-restricted diets early in life. But this approach can affect bone development and reduce bone density by 9% to 30%.
It’s also really hard for most people to cut their caloric intake. When researchers ran a two-year trial to measure the impact of a 25% reduction in caloric intake, they found that the most their volunteers could cut was 12%. (That study found that caloric restriction reduces markers of inflammation, which can be harmful when it’s chronic, and had only a small impact on bone density.)
Unfortunately, there’s a lot we still don’t really understand about caloric restriction. It doesn’t seem to help all animals live longer—it seems to shorten the lifespan of animals with certain genetic backgrounds. And we don’t know whether it extends the lifespan of people. It isn’t possible to conduct a randomized clinical trial in which you deprive people of food from childhood and then wait their entire lives to see when they die.
It is notoriously difficult to track or change your diet. And given the unknowns surrounding caloric restriction, it’s too soon to make sweeping recommendations, particularly given that your own personal biology will play a role in any benefits or risks you’ll experience. Roll on the next round of research.
This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.
