How I Used AI SEO Radar to Track My Clients’ LLM Visibility — And What Actually Happened
CASE STUDY
Razim Arje
• Freelance SEO Consultant, 6 years experience
• Austin, TX
• April 2026
AI Search Visibility GEO / AEO LLM Citation Tracking Freelance Agency
TL;DR
I manage 9 client websites and needed a way to track LLM visibility without manually Googling brands in ChatGPT every week. I trialed AI SEO Radar for 6 weeks. The citation gap detection is legitimately useful and saved me roughly 4 hours per week. The UX needs work. It is not a replacement for a full SEO stack. But for solo operators and agencies trying to have credible AI search conversations with clients, it earns its keep.
Who I Am and Why I Tried This
I have been doing SEO consulting for six years. My client roster sits at nine mid-market websites across e-commerce and B2B SaaS. I use Ahrefs for backlink and keyword research, SE Ranking for rank tracking, and Google Search Console for everything else. My monthly tool budget sits somewhere between $300 and $800 depending on the quarter.
Three clients had been asking the same question for months: “Why is our traffic flat even though we rank on page one?” The answer kept pointing back to AI Overviews. Google was answering queries directly, and competitor brands were getting cited inside those AI-generated answers while my clients were invisible. Traditional rank tracking showed green across the board. That felt increasingly disconnected from reality.
“I was spending 20 minutes per client per week manually Googling their brand in ChatGPT and Perplexity, screenshotting results, and pasting them into a Google Doc. That is not a workflow. That is desperation.”
I needed something built specifically for LLM visibility — not a bolt-on feature tacked onto an existing SEO suite.
How I Found AI SEO Radar
A Reddit thread in r/SEO surfaced the platform after its launch. The marketing pitch — a “5-Bot AI Indexing Pipeline” that validates content across frontier models, tracking what they call “Synthetic Authority” — caught my eye, even if the language felt a bit dense. The core product promise was straightforward enough: track whether your brand gets cited in AI-generated answers across ChatGPT, Perplexity, Gemini, and Google AI Overviews.
I signed up on a Tuesday afternoon. No sales call was required. Onboarding took 12 minutes. First good sign.
First Week: What I Actually Experienced
Day 1: Added three client domains. The dashboard populated within a few hours with an initial AI Share of Voice score for each. My first reaction: the numbers felt alarmingly low. But after cross-checking manually in ChatGPT, I realized they were probably accurate, not a bug.
Day 2: The LLM Citation Gap report surfaced 14 competitor URLs that were being cited in ChatGPT for exact keywords my clients rank for on Google. Finding those manually would have taken hours. This was the moment I thought: okay, there is something real here.
Day 4: Tried setting up a custom prompt monitoring workflow for a client’s 30 key buying queries. Hit a wall immediately — the UI for entering prompts is functional but clunky, with no bulk import option. Had to enter each prompt manually, one by one. Took 45 minutes for a task that should take two.
Day 7: Pulled the first client report. The PDF export was clean enough to send directly without reformatting. Small win, but a real one — I billed for 30 minutes of reporting time I did not actually spend.
Results After 6 Weeks
41mCitation Gaps Found, across 3 client sites
+11% AI Share of Voice Lift best-performing client
~4 hrs Hours Saved / Weekvs. manual monitoring
The most concrete, attributable win came from the citation gap report. It revealed that a competitor’s FAQ page was being cited inside Perplexity for a high-intent query that one of my clients owns on Google page one. I rewrote the client’s equivalent page with structured Q&A formatting, added FAQ schema markup, and submitted it for re-indexing.
Within three weeks, that page started appearing in AI-generated answers alongside the competitor. The client’s AI Share of Voice score in the platform jumped 11 percentage points for that keyword cluster.
Important caveat: It is genuinely hard to attribute this improvement solely to AI SEO Radar. The content changes I made based on the tool’s insights could have driven improvement regardless of which tool surfaced them. The platform is a signal detector, not a magic button. You still have to do the work.
Feature Ratings
Citation gap reports 8.5/10
AI share of voice 7.5/10
Prompt monitoring 6/10
Reporting / exports 7/10
Onboarding UX 6.5/10
Value for price 7.2/10
Honest Pros and Cons
What Works
+ Citation gap detection — genuinely novel, not available in Ahrefs or SE Ranking
+ Multi-model coverage: ChatGPT, Perplexity, Gemini, and Google AI Overviews
+ Fast self-serve setup — no sales call, onboarded in under 15 minutes
+ Client-ready PDF exports that don't need reformatting
+ Competitor citation alerts when rivals’ scores jump
+ Shows which URLs get cited, not just brand name mentions
What Needs Work
− Prompt entry is tedious — no bulk import, had to add 30 prompts one by one
− Data feels thin for niche B2B verticals (limited crawl depth)
− Monitoring only — no built-in content recommendations or fixes
− Historical data capped at 30 days on the base plan
− Support response time was 48+ hours on both tickets I submitted
− Buzzword-heavy marketing makes it hard to evaluate pre-signup
How It Compares to Alternatives I Looked At
I evaluated three other tools before settling on AI SEO Radar for the trial period:
Ahrefs Brand Radar: Already covered through my existing subscription but the Brand Radar add-on costs $199/month and, at the time I tested, had no citation source detection.
Writesonic GEO: Excellent all-in-one platform but starts at $199/month for the full GEO suite, which felt like overkill for a solo operator managing small-to-mid-size clients.
Otterly AI: Lightweight and affordable at $29/month, but felt more like a brand mentions tracker than a true citation gap tool. Useful for beginners.
AI SEO Radar sat in a useful middle ground: more focused than Otterly, more affordable than Writesonic at this stage, and filling a gap that Ahrefs had not yet closed properly.
Who Should and Should Not Use This
This tool is a strong fit if you are:
A freelance SEO consultant or small agency managing multiple client sites who needs to show up to calls with something smarter than a screenshot from ChatGPT
An in-house marketer at a brand that is starting to lose organic traffic to AI Overviews and needs to understand why
An early adopter who wants to get ahead of the GEO/AEO shift before larger agencies catch up and commoditize the service
Skip this tool if you are:
An enterprise team that needs API access, deep historical data, or white-label reporting — the platform is not there yet
Looking for actionable content recommendations built into the tool — it tells you what is happening, not what to do about it
Primarily focused on traditional SEO with no client demand for AI visibility reporting
Recommended — with honest caveats
AI SEO Radar is a legitimate tool solving a real and growing problem. It is not a silver bullet, and the interface still has the rough edges you would expect from an early-stage product. But the core citation gap tracking actually works, and for a solo consultant or small agency trying to have credible conversations with clients about AI search visibility, it earns its place in the stack.
If you are expecting Ahrefs-level polish and data depth, you will be frustrated. If you are expecting “something better than Googling my own brand in ChatGPT every Monday morning,” you will be satisfied. For what it costs, it replaced a meaningful chunk of manual work and gave me a reporting narrative that clients found genuinely compelling.
“The next six months will determine whether AI SEO Radar matures into a serious platform or stays a useful niche tool. Right now, it is the latter — and for my workflow, that is enough.”
About Me
I,m Razim Arje is an independent SEO consultant based in Austin, Texas, with six years of experience working with e-commerce and B2B SaaS brands. This case study reflects a paid trial conducted between February and April 2026. No compensation was received from AI SEO Radar for this review.
