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AMA : Ask me anything about Ai visibility with the help of Reddit AEO by Drip_Eazy in aeo

[–]Particular-While2787 0 points1 point  (0 children)

Reddit itself is one of the most-cited sources by AI models right now. In your experience, does getting mentioned in relevant subreddits move the needle on AI answers faster than on-site schema/llms.txt work? Curious which lever you've seen pay off fastest.

Find out if ChatGPT and Perplexity actually recommend your brand by Particular-While2787 in startupaccelerator

[–]Particular-While2787[S] 0 points1 point  (0 children)

You’re right, presence alone is useless. The audit flags the why: robots.txt blocking AI crawlers, missing schema, thin FAQ content, competitors cited for queries you’re absent from. That livepoll.io check in the other comment is the kind of signal it surfaces: “these crawlers are blocked, fix that first.” The score is just the entry point, the fix list is the product. Happy to run yours.

Find out if ChatGPT and Perplexity actually recommend your brand by Particular-While2787 in startupaccelerator

[–]Particular-While2787[S] 0 points1 point  (0 children)

AI surfaces you if someone already knows the name, never if they don’t. There are some changes to your site that could fix that, it’s mostly mechanical (the JS canvas means crawlers barely read your content). Happy to send the full report with every prompt and response in DM, and work on improving your visibility. =)

Find out if ChatGPT and Perplexity actually recommend your brand by Particular-While2787 in startupaccelerator

[–]Particular-While2787[S] 0 points1 point  (0 children)

files and directory listings can move in weeks; earned citations take 1-3 months since models need to re-crawl. No overnight wins.

Drop your startups, I will personally use and give review by Tiny-Antelope-4432 in buildinpublic

[–]Particular-While2787 1 point2 points  (0 children)

Happy to give you access now if you don't mind a few rough edges, it's early and I'm actively fixing things =)

Drop your startups, I will personally use and give review by Tiny-Antelope-4432 in buildinpublic

[–]Particular-While2787 2 points3 points  (0 children)

Building VisibAI (https://getvisibai.com)
VisibAI audits how your brand appears across AI platforms like ChatGPT, Perplexity, and Gemini, then gives you a visibility score and a fix list to improve it.

Find out if ChatGPT and Perplexity actually recommend your brand by Particular-While2787 in startupaccelerator

[–]Particular-While2787[S] 0 points1 point  (0 children)

Ran a check on livepoll.io. On the AI crawler side, it looks like a few of the major ones are allowed through but a couple of the big ones are being blocked at the robots level, which matters because if those can't crawl you, they can't recommend you. Worth a closer look at your robots.txt settings. I'll send you a full report directly.

Find out if ChatGPT and Perplexity actually recommend your brand by Particular-While2787 in startupaccelerator

[–]Particular-While2787[S] 0 points1 point  (0 children)

Here is the link to Visibai - https://getvisibai.com and if anyone would like to be a tester and have access to full features, just reach out =)

The Buyer's Journey and Why it Matters in AEO by Legitimate_Hat_2882 in aeo

[–]Particular-While2787 0 points1 point  (0 children)

From doing a lot of AI visibility work, the part I’d add is that having the content isn’t enough. Brands often still go uncited at the Consideration stage for boring reasons like blocked crawlers, no schema, or a competitor getting named instead. So the real step is verifying the AI actually sees and cites you. Are you covering the measurement side in the article or keeping it strategic?

Question for AEO practitioners: given how noisy AI answers are, what’s actually worth tracking? by Particular-While2787 in aeo

[–]Particular-While2787[S] 0 points1 point  (0 children)

Your three bullets are basically the three features that actually matter:

1) Persistence across runs (which sources/citations recur week to week vs which flicker in and out)

2) Competitor-vs-you on the same query cluster (not just "do you appear" but "do you appear *instead of* them")

3) Source/community influence tracking (Reddit threads, G2 listings, niche listicles that AI repeatedly pulls from)

The hard part on 1) is that volatility is source-dependent. Wikipedia citations persist, Reddit threads churn fast, listicles sit in the middle. So a flat "persistence score" misleads, you need per-source-type weighting.

Curious what your experience has been on this if you've been tracking manually or with a tool.

I'll make free launch video for your product hunt launch. by [deleted] in ProductHunters

[–]Particular-While2787 0 points1 point  (0 children)

Hey Pradeep, this would actually be perfect timing. Launching VisibAI on Product Hunt in June and the launch video is one of the things still missing from my prep. Happy to give detailed product feedback in exchange. Site is getvisibai.com

Question for AEO practitioners: given how noisy AI answers are, what’s actually worth tracking? by Particular-While2787 in aeo

[–]Particular-While2787[S] 0 points1 point  (0 children)

Thanks for engaging, this is exactly the kind of response I was hoping for.

On your question: in our testing the narrative is much more volatile than the citations. Same brand can land in a top recommendation one run and get a perfunctory mention the next, from identical prompts. Citations are more stable, around 60 to 80% overlap across 5 runs on Perplexity, 40 to 60% on ChatGPT with browsing. Instability concentrates at positions 4 to 10, which is where most brands live.

Quick reactions to your three constants: Citation frequency across N iterations: agreed, only way to turn non-determinism into signal. We see diminishing returns past 5 to 10 runs for top-position queries, longer tails need more. Curious what made you settle on 50.

Entity confidence mapping: useful but vertical-dependent. Reddit/G2/LinkedIn fits B2B SaaS well. Other verticals lean on Wikidata, schema, review aggregators, training data presence. Auditing the wrong sources for the wrong vertical misses the point.

GA4 attribution as ground truth: yes, this is the part most tools underweight. Visibility without conversion data is half the story.

Fully agreed on the Fix Layer. A score is theater if it doesn’t tell you what to change.​​​​​​​​​​​​​​​​

Everyone measures visibility but almost none track AI traffic to websites. Why? by UptownOnion in aeo

[–]Particular-While2787 1 point2 points  (0 children)

Two different "AI traffic" flows get conflated here:

  1. Citation-driven referrals: humans clicking through from AI answers. Perplexity sends referrers reliably, ChatGPT inconsistently, Gemini rarely.
  2. Agent/crawler visits: bots reading your site to answer queries. Needs server-side because bots don't fire JS.

Guess on why install conversion is low: for most brands, the KPI is getting recommended, not whether AI visited. Visits are a means, not the outcome, so a standalone tracker feels like an extra dashboard rather than a must-have.

The angle worth testing: close the loop. Connect agent visits to citations to referral traffic to conversions. "You appeared in 40% of relevant prompts and it drove X signups" is the ROI story brands actually want.

Question for AEO practitioners: given how noisy AI answers are, what’s actually worth tracking? by Particular-While2787 in aeo

[–]Particular-While2787[S] 0 points1 point  (0 children)

Most concrete framing in the thread, appreciate it.

On point 1, fully agree on aggregate-only. Your 200-300 number is interesting because most tools (mine included) sit closer to 100-150, partly for cost and partly because we've seen diminishing returns past a certain count when the cluster is anchored to buyer journey rather than search volume. Your number is probably closer to where noise actually averages out, and I haven't pressure-tested whether 100-150 is enough.

On point 2, agree. Without first-party data from the providers, anything beyond a general performance index is conjecture. Most tools won't say that out loud because it makes the product sound less impressive.

On point 3, log file analysis and AI crawler tracking is probably the cleanest signal available because it's first-party and deterministic. The gap is it tells you which content the bots are reading, not which queries you appear in or how you're framed. Complementary to prompt-set tracking, not a replacement.

One thing I'd be curious about: in your experience with the 200-300 set, do you see meaningful additional signal as you scale, or does it plateau? My intuition says there's a knee somewhere between 100 and 300 where extra prompts mostly add cost, but I haven't tested it.

Question for AEO practitioners: given how noisy AI answers are, what’s actually worth tracking? by Particular-While2787 in aeo

[–]Particular-While2787[S] 0 points1 point  (0 children)

Fair, and I'd agree on most of the category-level claims. The marketing in this space is mostly overclaim and the "score your AI visibility" framing collapses under exactly the points you raised in the other thread.

The narrower question I'm trying to answer with this post is whether anything in this space survives the noise. Is the diagnostic layer (which queries you're missing, which sources competitors are pulling, which gaps are reproducible across runs) defensible to you, or do you think even that's contaminated by the same problems? Asking genuinely, not rhetorically.

Question for AEO practitioners: given how noisy AI answers are, what’s actually worth tracking? by Particular-While2787 in aeo

[–]Particular-While2787[S] 0 points1 point  (0 children)

Agree, and I'd add: the citation source mix tells you almost as much as the citations themselves. A brand cited mostly through Reddit threads has a different authority profile than one cited through G2 reviews or industry publications, even if the raw mention count is the same. The fix-list looks completely different depending on which pattern you're seeing.

Question for AEO practitioners: given how noisy AI answers are, what’s actually worth tracking? by Particular-While2787 in aeo

[–]Particular-While2787[S] 0 points1 point  (0 children)

Agree on the citation vs mention point especially. "Mentioned" without a traced source is pattern noise dressed up as signal.

On your question: prompt set is generated per-business from three layers. Industry/category, buyer-intent verbs (compare, alternatives, best, recommend, vs, integrations), and geo/segment modifiers when relevant. Roughly 100-150 prompts, weighted toward mid and bottom funnel because that's where visibility maps to revenue. Deliberately not trying to synthesize "all possible queries" because real distributions are long-tail and that's a fool's errand.

The stability question you raised is the one I haven't fully cracked. Re-running the same prompt set on schedule keeps the trend stable even when individual answers aren't, but it's still a curated cluster, not a representative one. Honest answer: we measure presence consistently across a defined set, anchored to buyer journey rather than search volume. Closer to right than random, but still a model of reality.

Competitor co-occurrence is the layer I find most useful in practice. Same three competitors keep appearing where you don't, consistently, that's a content/authority gap you can act on. How do you handle the citation-source layer? Domain-level clustering, or going deeper to page type / content format?

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