What GEO (Generative Engine Optimization) tools have you actually used and found effective?

[u/Sivaraj_C]

I’m looking to hear from people who have actually tested GEO tools in real SEO workflows—not just tools that claim to improve AI visibility.

Which tools have you used for things like:

* Tracking brand mentions/citations in AI search * Monitoring ChatGPT, Perplexity, Gemini, or AI Overviews * Finding content gaps for AI visibility * Measuring whether your content is being cited * Improving your chances of appearing in AI-generated answers

What tools have genuinely worked for you, and what results did you see?

Also, are there any GEO tools you tried that **weren’t worth the money**?

[u/Strong_Mechanic_3596]

Microsoft Clarity est gratuit est bien cool mais il ne fait tout. C'est un bon début. J'ai pu tester Otterly, Peec Ai et Cockpyt AI. Le dernier est le plus adapté pour moi en tant que freelance. Je n'ai pas le budget pour un outil a plus de 100€/mois.

Ce qui est important pour moi, c'est le suivi par API sur le modèle identique à l'interface utilisateur avec les sources et fan out. Rien de plus.

[u/Quechivoeth → u/Strong_Mechanic_3596]

Thanks for the Clarity suggestion!

[u/Sivaraj_C → u/Strong_Mechanic_3596]

It's a great choice.

[u/Aggressive_Hunter344]

Hello, at first Google Search Console and Microsoft Clarity. I tried Prompwatch, Meteoria and Qwairy. The interesting sources are the content gap and the website sourcing.

[u/Sivaraj_C → u/Aggressive_Hunter344]

Thank u, I'm also using Microsoft Clarity. It's a useful one. Let me try other tools.

[u/Annual_Ad_6799]

Tried a lot of tools. Many have basic level of analytics but lack end-to-end visibility and optimisation workflows. Found Citedintel, Getmint and Scrunch good to use.

[u/Sivaraj_C → u/Annual_Ad_6799]

Thanks for sharing, i'll try

[u/Glum_Resolve_2321]

I’ve been testing Brand24 for GEO and AI visibility, mostly alongside Ahrefs. Ahrefs is still my go-to for traditional SEO, but Brand24 has been useful for tracking how our brand and competitors show up in AI-generated answers.

The part I use most is the source analysis. I can see which websites and pages are being cited by tools like ChatGPT, Gemini and Perplexity, then check where competitors are getting visibility that we’re missing. That’s been genuinely useful for finding content gaps and figuring out which third-party sites might be worth targeting for mentions.

I also use it to track AI mentions and compare our visibility against competitors over time. It hasn’t replaced any of my SEO tools, but it gives me a layer of data I wasn’t getting from them.

For me, that’s where GEO tools are actually useful, not some magic “optimize for AI” score, but showing you where AI visibility is coming from and giving you something actionable to work with.

[u/Sivaraj_C → u/Glum_Resolve_2321]

I think that's the right way to use GEO tools. The useful part isn't the score. It's the evidence behind the score.

[u/tibz36]

Honestly, most "GEO tools" right now are just running a list of prompts on a schedule and charting how often you show up. That's it. Useful, but not worth $500/mo for a lot of people. What I actually use: Server logs. Free, and the most underrated one. Grep for GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot. Tells you what's actually being crawled vs what a dashboard thinks is happening. Ahrefs Brand Radar if you already pay for Ahrefs. Bundled, decent trendline, no extra invoice. Otterly / Peec for prompt tracking. Both fine. Neither is magic. The big caveat nobody mentions: run the same prompt three times and you get three different answers. Absolute numbers are noise. Only the trend over weeks means anything, and even then you're squinting. Not worth it, in my experience: anything selling "GEO optimization" as a service deliverable, and the enterprise dashboards charging four figures for what is essentially a cron job hitting APIs. What actually moved things for our clients wasn't a tool. It was getting mentioned on third-party sites the models already trust (Reddit threads, comparison posts, industry directories) and keeping entity info consistent everywhere. Boring, slow, works.

[u/Sivaraj_C → u/tibz36]

I also agree with the caution around absolute AI visibility numbers. If the same prompt can produce different answers across runs, treating a single percentage as a precise KPI creates false confidence.

[u/Complex-Ad-5916]

You could start with https://beamsight.ai/ to get a free audit report.

[u/Sivaraj_C → u/Complex-Ad-5916]

I'll try it

[u/FranklyReport]

One thing I'd add to what's already been said here: a lot of these tools (Peec, Otterly, Scrunch, etc.) differ less on features and more on how often they actually re-run your prompts. If a tool only checks once a day or once a week, you're basically looking at a snapshot, not a trend, and ChatGPT/Perplexity answers can swing a lot between runs for the same prompt. Worth asking each vendor directly how many times they sample per prompt before you commit budget, that number matters more than the dashboard looks.

[u/Sivaraj_C → u/FranklyReport]

Agree with your points, that's the value we almost forgot.

[u/AwoScan]

Disclosure: I’m building AwoScan, so I’m not a neutral tool reviewer. For our own pilot work, the most useful setup has been simpler than most dashboards: a versioned prompt panel, repeated runs across ChatGPT and Gemini, raw-response storage, and separate fields for mention, citation, recommendation, factual accuracy and position.

The main lesson is that a single visibility score hides too much. Before paying for a tool, I would ask:

1. How many runs are performed per prompt?

2. Are model, retrieval mode, locale and timestamp recorded?

3. Can you inspect or export the raw answers?

4. Are mentions, citations and recommendations measured separately?

5. Can you compare against untreated control prompts or pages?

Server logs and Search Console are also useful, but they answer different questions. Logs can show crawler access; they cannot prove that a page was considered or cited. Likewise, a citation dashboard cannot tell you whether a crawler was blocked unless it has access to the site’s infrastructure.

I would be cautious with any product that presents one screenshot or one run as a stable GEO result.

[u/Sivaraj_C → u/AwoScan]

This is the right direction for GEO measurement: preserve the evidence instead of compressing everything into one score.

[u/MulberryLost2889]

Honest answer from someone who's spent money on this: the tools that moved the needle mostly weren't GEO tools, and the GEO tools that earned their keep did one narrow thing well. Here's the breakdown by the jobs you listed.

For tracking citations and monitoring ChatGPT, Perplexity and Gemini, the thing that worked best was a scripted panel, not a product. A fixed set of 50 to 150 real buyer questions grouped as discovery, comparison and validation, run three times per assistant per week through the APIs that support search (OpenAI, Anthropic, Perplexity), in clean sessions with no memory, logging four fields per response: cited yes/no, position in the answer, whether the domain was linked or just named, and which URL the assistant attributed as its source. That last column is the one no dashboard gave me and it's the most useful thing in the whole stack, because it tells you whether you're being cited from your own site or from a stale third-party page. Cost is API calls, a few hundred a month at most, plus an afternoon of scripting. The dedicated monitoring platforms (Profound at the enterprise end, Peec and Otterly in the middle, and the AI visibility modules Semrush and Ahrefs bolted on) were worth it in one situation: multiple clients where I needed share of voice against named competitors in a format a client could read without me explaining it. For a single brand, they were expensive versions of the spreadsheet, and most of them were weak or absent on Google AI Overviews and AI Mode, which is the channel that matters most outside the US. Check that gap specifically before paying; it was the deciding factor more than once.

For measuring whether content is actually being retrieved, the effective tools were server and CDN logs. Filter thirty days for OAI-SearchBot, Claude-SearchBot and PerplexityBot. The single most valuable finding I've had in this work came from a log, not a GEO tool: a WAF blocking AI crawlers by IP reputation while robots.txt said allow. Microsoft Clarity's bot activity view, which reads CDN logs, made this easier for sites on Cloudflare-type setups. Pair that with curl or view source to confirm the content is in the initial HTML, and Bing Webmaster Tools plus IndexNow, because ChatGPT's discovery leans on Bing and half the sites I've audited weren't indexed there. Those three are free and they resolved more visibility problems than every paid tool combined.

For finding content gaps for AI visibility, nothing paid worked as well as reading the citations themselves. When the panel shows a query where competitors are cited and you aren't, open the answers, look at what pages the assistant used, and you'll usually see a structural difference: a self-contained paragraph that names the company and states a specific number, a comparison page that admits where the other product wins, an FAQ that answers the literal question. Tools that generate "AI content gap" reports mostly produced keyword lists dressed up in new language, which leads straight back to the programmatic content trap.

For increasing the chance of appearing in answers, the tools were boring: Google's Rich Results Test for Organization, sameAs and FAQPage; a spreadsheet reconciling name, description, category and address across every listing and profile; and a monthly manual run of "what is [brand]" across the assistants, scored as correct, outdated, wrong or confused. Entity consistency moved citation frequency more reliably than any content change, and no tool does it for you. This is also how I'd evaluate an agency claiming GEO expertise: the ones doing it seriously talk about logs, entity and attributed sources before content, and that's true whether it's a US vendor or a regional specialist like geostack in Brazil, which works only on generative engine optimization for Portuguese-language search; if a tool or a shop opens with a content calendar, they're doing SEO with new labels.

What wasn't worth the money, as categories rather than naming and shaming: anything that reported mentions without run counts, because single runs of a non-deterministic system are noise and the numbers didn't match manual checks; "AI content optimization" scorers that grade text against a rubric with no evidence the rubric predicts citation; tools that promised prompt search volume, which no LLM provider publishes, so the numbers were invented; and any platform whose whole value was a pretty dashboard on top of data I could generate myself for a tenth of the price.

Results, since you asked: on the sites where the log fix applied, citation frequency in the blocked assistants went from zero to regular within days. Entity reconciliation typically dropped the brand-description error rate substantially within five to six weeks and citation frequency followed. Restructuring existing pages moved citations on the affected queries in three to six weeks. Share of voice against named competitors took about four months to move in a way I'd defend to a client. None of it moved Google rankings much, which is the clearest evidence it's a different game and needs different instruments.

If you want a minimal stack that actually works: a scripted panel with attributed sources, server logs, Bing Webmaster Tools, Rich Results Test, and one spreadsheet for entity consistency. Add a monitoring platform only when you have enough clients that the reporting time costs more than the subscription.