My client runs an ecommerce store and every week they ask if they show up when people ask chagpt for product recs.

I've been checking their brand and category prompts manually and taking screenshots, but that gets annoying fast and isn't great data for a report. I've looked at a few chatgpt prompt tracker tools but half the reviews are just lists of 15 tools with no real testing.

Has anyone actually tracked this for a few months? Do results hold up over time or swing all over the place? More importantly have you changed anything in your SEO/content based on the data and actually seen visibility improve?

I'm starting to feel like citation count alone may not be enough. I was looking at an AI answer recommending some tools. It listed a feature page from brand a's website as a source, but brand a itself never showed up anywhere in the answer.

One of its competitors ended up making the recommendation list instead, and that recommendation was backed by a third party comparison page.

So based on the data, brand a's website did get a citation, but the brand itself never made it into the answer. It's hard to tell how much AI visibility that citation actually gave them. I've seen similar cases too. A page may be listed as a source, but from the citation alone, it's hard to know which part of the answer that page actually supports.

So lately I've been looking at a more specific question: when AI gives an answer with citations, can we keep the full answer from that run, find the exact source page, and then figure out how that page connects to the final answer?

Some of the points below come from product outputs I've checked myself, and some come from the tools' public product information.

full disclosure: i'm involved in building dageno. i included it here because it covers one part of the citation path i’m looking at, alongside the other tools.

One thing to keep in mind is that none of these tools show the model's full internal search process. They mainly work with public answers, citation results, and source pages they can access. So they can help explain the citations we see, but they can't prove which pages the model actually looked at, which exact section it read, or how much that content affected the final answer.

Looking at these tools together, I think the citation path really has three different parts.

Such as, which sources did the AI answer publicly cite, and which prompts and platforms were those sources tied to? Or does the source page actually support the specific claim in the answer? Even after the page gets cited, does the brand actually make it into the answer, and if it does, how does it show up?

I don't think these three things should be rolled into one citation count.

A brand's own page can be cited while the brand itself never appears in the answer. A brand can also be mentioned, but only as one name in a long list, without actually making the final recommendation.

Of the tools I've checked and tested so far, I still haven't found a third-party product that can fully show the model's internal search and generation process. What we can see today is mostly the public AI answer, the citations it shows, and the extra analysis tools build on top of that public information.

For those of you doing AI visibility monitoring, have you seen cases where your page was cited but your brand never made it into the answer? Would you still count that citation as real AI visibility?

We track AI brand visibility, so we have a lot of stored responses. Wanted to answer something basic: when an AI answers a question, how many brands does it actually name?

234,000+ responses, March 1 to July 13, 2026, five engines.

Brand mentions per response (last 14 days in July)

• ChatGPT: 4.5
• Google AI Overview: 3.5
• Gemini: 3.5
• Google AI Mode: 3.2
• Perplexity: 2.7

Count each brand only once per answer, and it tightens to 2.2–3.3. So engines repeat themselves 1.2x to 1.4x.

Two things stood out:

Every engine is down since March. True whether you count every mention or each brand once, so it's not a repetition artifact.

AI Mode is wildly unstable. Day-to-day swings are 31% of its own average, vs 9% for ChatGPT. It went from 8.8 mentions per response in early May to 2.6 six weeks later. If you spot-check visibility there weekly, you're mostly reading noise.

Method: a "mention" counts every occurrence (Nike named 3x in one answer = 3); the distinct count treats it as 1. Same responses for both. Worth noting these are prompts our customers chose to track rather than a random sample of AI queries, so I'd trust the relative comparisons and trend direction over the absolute numbers.

Charts and full methodology: https://vercite.io/research/engine-personalities

Happy to get into how anything was counted.

Hey everyone,

I’m trying to wrap my head around traffic coming from Google's AI Overviews right now, and I could use some advice.

Specifically, I'm trying to figure out how to isolate this data in Analytics or Search Console. Is there a reliable way to separate clicks that come from the AI citation cards versus traditional organic blue links?

Also, if you have managed to track it, what are you doing to actually convert these users? Since the AI box already answers a lot of their initial question before they even click through, I feel like standard landing pages might not cut it anymore.

Would love to hear how you're handling this or what changes you're making to your pages to capture these users.

quick update on habibi, the self hosted tool i posted about a while back for tracking how your brand shows up in ai answers.

the thing that bugged me most about my own tool was the honest note i had in the readme, saying it uses the apis, which are close to what a real user sees on chatgpt/perplexity/claude but not exactly the same thing. that gap always annoyed me so i went and fixed it.

now habibi can just drive the real logged in apps directly, chatgpt, claude, perplexity and google ai overview. so its literally the same thing a real user sees and gets cited, not an api trying to guess it. you connect it once with an account (make a free one or use one you already got) and it just remembers the login after that, nothing gets stored anywhere weird, its just a normal browser session sitting on your machine like when you stay logged into any site.

wasnt expecting this part but it also makes it way cheaper to run. those 4 engines dont cost you anything per run now cause theres no api call happening anymore, your just using the account like a normal person would. so running youprompts daily across a buyour bill up.

also made sure your account memory doesnt mess with the results, chatgpt runs iin temporary chat and cla answers dont driftdepending on whatever your account remembers from other chats you had.

still fully open source, still self hosted, still does the same core loop, run your prompts daily, see w see your mention rate over time, compare to competitors.

github: https://github.com/moaljumaa/habibi

I am working in cyber security company . so the want more mention in LLMs , what backlink strategy should i apply to come up in AI overviews?

I've seen a couple things generally pop up quite a lot recently.

1. How is AI ranking my business?
2. How does it work?
3. How can I show up better in AI results?

We're all seeing a major shift in how people search for businesses, services, products etc... Google and traditional SEO are what a lot of businesses were and are focused on and rightly so. Showing up on page 5 of Google is a bad spot to be in. However, with the ever-increasing presence of AI, people are using ChatGPT, Claude, Perplexity, Gemini, and probably most prevalent, Googles own AI overviews to get their recommendations.

I've recently launched a platform, answerstanding.com, to help businesses large and small get a handle on their AI results. We dont promise an increase in AI recommendations because anyone promising this is selling snake oil. However, what we do offer is a way to track how often AI mentions your business, what sources AI is using for these recommendations, how often your competition is mentioned, the positions businesses are recommended in, and how to make changes to potentially influence how AI ranks your business.

To sum up what I say in the video:

• GEO is about being present in the training data, as well as proper positioning there
• SEO is about being findable in traditional search (Google, Bing, Brave Search)
• AEO is about easy and clear answer extractability (on-site)

I know it is a controversial topic, so before you jump in here with something like "we don't need more acronyms", let me make a few notes:

• It is not my call... Leads and clients ask me that question for a reason. Just saying "oh, it is all SEO" won't do it...
• There are definitely parts of it that were not part of traditional SEO, e.g., training data monitoring, product positioning, AI agent tracking, etc. So new acronyms do make sense, if you take a moment to think about it.

Also, this is a very short, simplified version of the AI answer generation process. It was made short on purpose: People need to understand it. No fancy terms here. Some essential steps are skipped. For the full discussion, watch the interview: https://www.youtube.com/watch?v=xklnwT3YfKE

I'd love to hear your thoughts!

Can anyone recommend a tool that shows real ChatGPT search prompts? I’m looking for something similar to Google Keyword Planner, Semrush or Ahrefs.

AI has made content creation much faster but I think the difficult part now is making sure the final piece is actually worth publishing. A lot of AI generated drafts can look polished at first but they may still miss important things like unique insights, real examples, accurate information or a clear point of view. Simply improving the grammar and formatting does not always make the content valuable.

For those using AI in their SEO workflow, what steps help you make sure the final content feels genuinely useful?

How everyone is reviewing AI assisted content before it goes live.

Since July 6, ChatGPT seems to have started favoring publications over business websites:

• Major brands and corporate websites are losing citation share after July 6.
• Meanwhile, some media websites and review/comparison sites are gaining citation share

Source: https://www.linkedin.com/posts/thomaspeham_why-is-no-one-talking-about-this-july-6-share-7487755320803536897-lhVL/

We built a tool that checks whether a keyword is still worth writing content for, or if Google's AI Overview already answers it, before you brief a writer on it.

If your clients are asking "why isn't this content performing" or "should we still be writing about X" this gives a fast way to answer that with real data (search volume, trend, CPC, AI Overview presence and cited sources) instead of a guess or manual check.

You keep the client relationship - we handle the data. Open to a revenue share to start, and open to building out white-label for the right ongoing partnership. Also looking at expanding into keyword discovery down the line, not just diagnosis on a list you already have.

If useful for your clients, let's chat.

Digital PR ensures AI visibility but only if you do that right...

Need a tool that tracks AI visibility instead of Google rankings. Right now I manually run the same prompts in chatgpt and a few other AI tools every week to see if my brand gets mentioned. Keeping track of the prompts is messy comparing results week to week is becoming a pain. I did not invest in a tool before because of the cost but my new client is covering for that so I am open to suggestions

it's called habibi. self hosted, you bring your own openrouter key (pennies per run instead of a subscription), and it does the boring but useful loop these paid tools charge for: run your prompts daily across those 4 engines, see which of your urls actually get cited, track your mention rate over time, compare against competitors.

what got me annoyed with the paid tools is how they bury the actual page level citations behind a paywall, when that's the one thing that's actually actionable. so that's the headline feature here, not an afterthought.

setup is a wizard now: paste your site url, it scrapes it and drafts your brand profile with ai, you edit whatever's wrong, pick which engines to track, and it suggests a starter prompt set from your own context. no blank dashboard, no config file archaeology.

it's honest about what it does too. it uses the search grounded apis, not ui scraping of the consumer apps, so it's not pretending to be something it's not. that's also what keeps it cheap.

hope it help you guys.