Throughout 60,000+ web sites we observe day by day analytics for, ChatGPT sends 8-9x the referral site visitors of the following main AI-first platform, Perplexity.
Simply final month, OpenAI CEO Sam Altman revealed that greater than 800 million folks use the platform every week.
However what does it take to get talked about and cited in its responses?
Our newest analysis into top-of-the-funnel queries reveals that lately up to date “greatest X” lists have been probably the most outstanding web page sort in ChatGPT sources, together with these the place beneficial manufacturers ranked themselves in first place.
There was additionally a correlation between a model positioning extremely in third-party lists and being extra more likely to characteristic in responses.
Does that conclusively imply you need to be publishing these lists your self? Earlier than I share the method we’re taking, let’s take a look at the information in full.
I analyzed ChatGPT responses throughout 750 top-of-the-funnel prompts in three classes: software program, merchandise, and company suggestions (e.g., ‘one of the best internet design businesses in London’).
Whereas that quantity won’t sound like a lot, it took dozens of hours to manually categorize responses to make sure accuracy.
What I used to be searching for: How typically “greatest” lists present up as citations
For software program, I used to be phrases like “greatest crm software program for enterprise” and “greatest undertaking administration software program”.
For merchandise, I analysed prompts round queries resembling “greatest entry-level DSLR” and “greatest house treadmill”.
Within the company class, I checked out phrases associated to businesses providing companies overlaying web optimization, social media, promoting, branding, common advertising and marketing, and internet design.
In conventional web optimization, these phrases are estimated to be looked for a whole lot of hundreds of occasions per month.
That stated, it’s seemingly that the phrases folks enter into Google won’t be the right illustration of what’s entered in a chat platform. Sadly, AI platforms don’t present that knowledge instantly.
It’s additionally seemingly {that a} notable proportion of suggestions are given as the results of a multi-query dialog, somewhat than a single immediate.
Because of this, I haven’t appeared into probably the most beneficial manufacturers or the top-cited domains general, however somewhat into the forms of content material sourced from these websites.
One other intention with this research is to set a benchmark for what we’re seeing throughout the board, which we will evaluate in opposition to and enhance upon over time.
Sidenote.
For extra particular particulars about this analysis and its methodology, I’ve created a supplemental Google Doc that shares classes realized and concepts for future analysis based mostly on my findings.
The desk beneath covers the commonest web page sorts we noticed throughout all three classes.
It contains each first-party mentions—when a beneficial model or product’s personal web site is cited—and third-party mentions.
The vast majority of web page sorts we analysed must be self-explanatory, however for these which are probably the most outstanding, right here’s some extra clarification:
- Weblog record: An inventory of suggestions in a weblog publish format, resembling this publish on “The 8 Finest AI Detectors, Examined and In contrast” by our personal Ryan Legislation
- Non-Weblog Checklist: Platforms like G2 (software program) or Clutch (company), which rank suggestions however not in a weblog publish model format
- Touchdown web page: Common pages like a selected service an company affords, or a market a SaaS firm has an answer e.g., this page on Siege Media displaying they provide internet design companies
- Social media: This covers websites like Reddit, Fb, Instagram, and LinkedIn
Hyperlinks might seem inline with suggestions, or as supply hyperlinks, which have been used for analysis however require an extra click on to view.
Every first-party point out was manually categorized.
For third-party mentions, totaling 10,000+ particular person URLs, we used a semi-automated method.
We arrange dozens of guide filters to enhance accuracy. For instance, the study.g2.com subdomain hosts content material sorts very totally different from normal G2 class pages.
For the remaining URLs, we categorized them with OpenAI’s GPT-5 mannequin with customized directions.
Lastly, we hung out going over every group of URLs and improved tagging the place vital, although we have been pleased with 95% of what we initially noticed.
In some classes there’s a transparent shift during which web page sort featured prominently. Touchdown pages are generally cited when searching for one of the best software program or company, however hardly ever present up when researching merchandise.
Common weblog posts on product web sites carried out much better than within the software program and company suggestions area.
For every of the classes in query, we took 250 “greatest” weblog lists from ChatGPT’s responses (750 in complete) to find out the place a selected model was featured when that record was sourced alongside it.
This was all accomplished by hand, as automation wouldn’t be as correct. For instance, many lists declare they’ve a sure variety of gadgets, after they typically have extra and easily haven’t up to date their title or headline.
Automation to find out the place a model featured in an inventory will be much more advanced. Particularly as they’re not all the time introduced in a clear record of numbered headings.
Within the instance beneath, you’ll be able to see that Asana options as the highest spot in their very own record of one of the best undertaking administration software program:
In the same article on Zapier’s web site, Asana is proven because the second suggestion:
Each pages have been used as a supply in a ChatGPT response.
Taking all 750 lists into consideration, right here’s the distribution of the place a talked about product, model, or service supplier was featured in an related “greatest” record.
Whereas there’s a transparent suggestion that being positioned extremely will increase suggestions, there’s additionally some bias right here.
Not each record has 10 or extra gadgets, so there’ll all the time be extra suggestions at increased record positions.
To assist resolve this, we will take a look at record distribution and what number of suggestions fall into the highest, center, or backside third of an inventory, no matter its dimension.
As we will see from the general distribution, there’s nonetheless a robust pattern in the direction of firms and merchandise that ranked increased within the related record.
I needed to do one higher than that and likewise share a chart centered on a separate set of lists with 10 or extra gadgets. There we see a much less outstanding outcome, but it surely’s trending in the identical path:
Another elements is perhaps in play right here, as coated within the aforementioned supplemental doc.
One conclusion we would rapidly soar to is that LLMs decide earlier sections of the information given to them, and thus they’re “prioritizing” a number of the high suggestions.
I spoke briefly with Dan Petrovic from DEJAN web optimization, who has accomplished in depth analysis on this area, and recommended that may not be the case. A few of his analysis reveals that roughly content material will be extracted relying on the area or web page being sourced.
We’re nonetheless finding out this, so I hesitate to provide a definitive conclusion, however even when AI weren’t a factor, you’d logically wish to characteristic increased on an inventory of beneficial software program, merchandise or service suppliers in your business.
I took an equal pattern of weblog lists from our three classes and checked to see after they have been revealed or final up to date. After filtering out these with out clear publish or modified dates, I used to be left with a clear record of 1,100 URLs to research.
79.1% have been final up to date in 2025, and 26% have been final up to date previously two months alone.
This accounts for those who have been both revealed for the primary time or later modified within the respective timeframe.
Curiously, extra articles had been up to date since publication (57.1%) than these revealed and left as is.
Retaining articles updated might assist them carry out higher in conventional search, however our knowledge reveals AI assistants favor even more energizing content material.
Spend a while reviewing the sources ChatGPT makes use of and it’s clear they aren’t all the time probably the most reliable web sites.
Many lack any human presence and look nearly totally like they have been constructed for hyperlink constructing and / or quotation functions.
Whereas the bar for high quality must be increased in the event that they’re utilizing Google and Bing as their reference sources, our personal Louise Linehan discovered that 28% of ChatGPT’s most-cited pages have zero natural visibility.
My very own research discovered that many questionable websites carry out properly in Bing however not as properly in Google.
Whereas Ahrefs Area Score isn’t an ideal indicator of web site high quality, if I take 1,000 cited greatest lists throughout every class (3,000 in complete), I discovered that a good portion have been revealed on domains with low authority.
In easy phrases, they’ve fewer high-quality websites linking to their personal.
As Glenn Gabe coated in his wonderful article, Google’s personal AI solutions ought to have fewer points selling reliable websites, however different AI search platforms will seemingly have to develop stronger belief and high quality scoring going ahead.
I count on we’ll see the left aspect of this chart decline over time.
Whereas the vast majority of this research was centered on ChatGPT, the prominence of those comparability articles isn’t unique to OpenAI’s platform
In truth, they have been barely extra outstanding in Google’s AI Overviews:
It’s not simply top-of-the-funnel queries the place they present up both.
Trying on the high 1,000 most-cited pages throughout every platform by way of Ahrefs Model Radar, all included comparability listicles. And that’s throughout 150M+ complete prompts.
The way in which ChatGPT recommends businesses and merchandise differs from the way it at the moment recommends software program.
Whenever you’re searching for an company, you’ll be able to typically click on instantly on that company’s identify to come out a sidebar and study extra about it.
Sadly, for the needs of analyzing totally different classes, this isn’t all the time the case.
As you’ll be able to see beneath, there was no direct web site hyperlink within the sidebar for Charle, however there was a hyperlink to their web site within the textual content beneath their identify.
Sidenote.
In ChatGPT 5.1 these sidebars appear to now not seem for businesses, so it’s lucky that we didn’t give attention to mentions in them.
On account of this inconsistency, for agency-focused prompts we determined to give attention to the hyperlink related to a model, somewhat than the hyperlink which will seem of their sidebar.
This should not have any impression on stats for issues like Weblog Lists or Non-Weblog Lists, however it could have technically allowed us to search out much more first-party homepages in our evaluation.
Whereas weblog lists have been extremely outstanding throughout all sources, when a model’s personal web site was listed as the primary suggestion, an inner touchdown web page was extra more likely to seem than its homepage or greatest weblog record.
The desk beneath reveals the proportion of prompts that first-party mentions confirmed up in, by web page sort.
| Software program | Company | Merchandise | |
|---|---|---|---|
| Common Touchdown Pages | 37.2% | 30.4% | 0.4% |
| Weblog Checklist | 34% | 17.2% | 4% |
| Homepage | 15.6% | 14% | |
| Documentation (incl .PDF) | 7.6% | 0.4% | 0.8% |
| Weblog Publish | 4.8% | 0.4% | 12.4% |
| Product Web page | 0.4% | 87.2% |
Sidenote.
We aren’t anticipating columns so as to add as much as 100%, since a number of web page sorts can seem in a single response.
A simple clarification for touchdown pages outperforming weblog lists within the software program and company classes is that firms are much more more likely to have created touchdown pages overlaying the companies and options they provide, than to have made a self-serving weblog record.
Although they weren’t probably the most outstanding first-party web page sort, a self-promotional weblog record nonetheless confirmed up in additional than a 3rd of ChatGPT responses within the software program class when its writer was beneficial.
I discovered they have been even more prominent in Google SERPs,
Throughout 250 “greatest X software program”-style SERPs, 169 (67.6%) featured an inventory during which the corporate writing the article ranks itself primary.
Carry out any sort of “greatest [seo / web design / branding] company” search in Google and there’s a robust likelihood you’ll see a self-promotional record rating properly.
Within the merchandise class, it was uncommon for a corporation’s personal weblog record to seem, just because a lot of product firms don’t publish them.
You gained’t see a web page on Nike.com recommending Reebok, however they are going to publish an article on “The Best Winter Sneakers” and promote Nike’s personal footwear all through.
There isn’t something new about creating pages to cowl the markets you serve and the options you supply, however you would possibly wish to be certain these pages are precious and as much as date.
All the knowledge factors to a transparent reply: Businesses and SaaS firms ought to publish self-promotional “greatest” lists.
Numerous well-liked manufacturers like Shopify, Slack, Salesforce, HubSpot, and Superside have written them, and there seems to be no draw back from a conventional rating or AI quotation perspective.
There’s additionally an argument for being pleased with what you create, and for serving to guests navigate extremely saturated markets.
That stated, knowledge is just one a part of the equation.
Throughout my very own analysis, I’ve typically been annoyed by the lists I come throughout. Many are overly self-promotional, or just don’t hyperlink out to the options they advocate.
Whereas his feedback have been aimed toward creating dangerous person experiences on the whole, somewhat than concentrating on self-serving weblog lists, Mark Williams-Cook dinner made a great point on LinkedIn that poor person indicators would possibly meet up with you sooner or later.
Siege Media founder Ross Hudgens agrees these indicators are necessary, however argues you’ll be able to place your personal model first and nonetheless present worth.
Company proprietor Wil Reynolds, whom I’ve revered for years, had another opinion:
Any marketer price a rattling is aware of itemizing your self on the high of an inventory hosted in your web site doesn’t construct belief with consumers.
It wasn’t a standard incidence, however I did discover examples of firms that includes decrease down their very own lists.
DoorLoop positioned itself seventh on this record of rental administration software program suppliers
Whereas it’s admirable as somebody with no connection to the enterprise, there’s additionally the argument that they’re simply serving to opponents with their very own advertising and marketing.
You’ll need to determine which method is sensible for your enterprise, however let me not less than share our present take.
At Ahrefs, our considering is straightforward: We might publish extra comparability posts as we roll out new options or enter new markets, however they’ll proceed to make up lower than half a % of our complete weblog content material.
We’re not going to create them for each instrument or potential use case.
We gained’t all the time put ourselves within the high spot, as is already the case.
We’ll proceed to make it clear that we are the Ahrefs being beneficial.
(Nearly each firm selling itself does so within the third particular person, as in the event that they’re subtly making an attempt to miss that they’re writing about their very own enterprise.)
And we’ll hold linking on to various options so guests can analysis them on their personal.
One change we are making due to this analysis is to rejoice extra of our wins.
There have been many circumstances the place manufacturers have been talked about alongside constructive firm updates, as proven beneath for Monday.com.
In one other case, when health club administration software program Kilo was talked about, it was alongside their announcement of incomes an award from Capterra.
We might do a significantly better job there, with the potential added good thing about giving LLMs engaging commentary to make use of with any mentions.
Our main focus will proceed to be on issues which have naturally gotten us talked about on the lists of others, like consistently updating our product with new options, sharing unique knowledge and analysis, and being energetic the place our viewers is.
Mentions from manufacturers like Zapier are all the time good to see
As we’ve accomplished once we spent $400,000 operating an occasion, $1M+ sponsoring creators, or revealing how we determine the enterprise potential of latest weblog posts, we’ll hold you within the loop about how our method to AI search visibility evolves.
Keep tuned for some behind-the-scenes updates I’m engaged on there.
In case you have any ideas on how I might enhance the following iteration of this research or the rest you desire to me to dive into, please let me know over on LinkedIn or X.
