u/Fun-Training9232

Hey everyone,

I am currently trying to get my head around tracking our visibility in AI search engines like ChatGPT, Perplexity, and Google Overviews. Traditional rank tracking obviously does not cut it anymore since everything is moving toward AEO and getting cited by LLMs.

I have not pulled the trigger on any platforms yet, but I keep seeing a few specific tools floating around for this. Here is what I am looking at:

Similarweb: Everyone still swears by them for deep traffic analytics. I have heard incredible things about their data accuracy and market intelligence. It feels like the safest, most robust bet for seeing where traffic is actually moving across the web right now.

Otterly AI: I keep seeing this one mentioned for tracking brand mentions and overall AI share of voice across different LLMs.

Airefs: This one promises to map out citation sources specifically for AI engines.

SE Visible: Supposedly good for granular tracking of how often you pop up in AI answers.

Since these newer niche tools are relatively fresh, it is hard to tell what is actually worth the budget. Can a powerhouse like Similarweb give me the granular, prompt level AI citation tracking I need, or should I be pairing it with one of these smaller platforms?

If you have actually integrated an AEO tracking workflow this year, what does your tech stack look like are you just leveraging classic heavy hitters like Similarweb to reverse engineer where the LLM traffic is coming from, or are you using something else entirely?

Would love some honest feedback before I jump into sales demos. Thanks!

We track digital performance of companies before making investment decisions. been doing it manually, pulling web traffic reports, app intelligence data, visitor stats from different sources and trying to stitch it together

the problem is by the time the data hits the deck it is already stale. two weeks old minimum. and in fast moving sectors that gap matters, had a situation last quarter where a competitor had already spotted a traffic trend on a retail stock we were watching. they moved earlier. we had the same data just slower

now looking for something that pulls real time web and app intelligence into one place for stock research. something that tracks digital market share, traffic trends and consumer demand shifts without a three tool workflow.

Annual renewal. Carrier completely rewrote the identity section. They wanted specifics: what percentage of privileged accounts have phishing-resistant MFA, what is our access review completion rate, what is our documented offboarding SLA for contractor accounts, how do we detect compromised credentials beyond what our IdP ships by default. Previous years this was a general yes/no section. This year it was operational detail they clearly expected us to have measured and documented.  We answered honestly where we had data and estimated where we didn't. Premium went up. Underwriter's notes were specific about which gaps drove the increase  completion rate on access reviews and the contractor offboarding answer. Both of those are things I've been trying to get resources for internally. The questionnaire essentially produced an external audit of our identity posture that I couldn't get internally. Frustrating way to learn which gaps matter most, but it worked. Has anyone used the insurance questionnaire process strategically to build the internal business case for identity investment? Feels like there's a playbook here I'm missing.

Ran seo for b2b saas clients and like most was fixating on rank position for ai citations. pushed schema and structured data everywhere thinking more positions equals more wins.

then started segmenting ga4 by page traffic and revenue attribution. turns out 80 percent of ai referral value came from 12 pages that already had 200 plus sessions a month. the rest was noise.

new rule: only touch pages with over 100 monthly sessions or proven close rate above 5 percent. fixed 8 of those first. three months in citations up 40 percent on those, traditional rankings held steady.

heres the quick filter i use now:

1. Pull top 50 pages by traffic in ga4
2. Cross with revenue from form fills or calls
3. Score by session volume times conversion rate
4. Fix top 20 only

still testing if this kills long tail opportunity but short term revenue from ai traffic doubled.

anyone running similar filters or am i underweighting something

how do you balance ai fixes vs core seo when client asks for both.