TL;DR
Stobo executes. Otterly monitors. Your choice depends on where you are in your AEO journey.
Technical foundation comes before content optimization. If AI crawlers can't access your site, no amount of content work will earn citations. Research shows AI crawler traffic grew 305% from 2024 to 2025, and pages with FAQ schema achieve 41% citation rates versus 15% without. Fix the barriers first.
Where they differ:
- Robots.txt: Otterly gives pass/fail. Stobo identifies which of 21 specific crawlers are blocked.
- llms.txt: Otterly confirms it exists. Stobo analyzes 7 quality factors and generates the file for you.
- FAQ-schema pairing: Stobo checks this (unique in the market). Otterly doesn't.
- Content quality: Otterly scores quotes, statistics, and conversational tone. Stobo doesn't.
The sequence: Stobo first ($199 once) to fix technical barriers. Otterly second ($29-489/month) to optimize content and track visibility. Different phases of the same optimization process.
We ran trystobo.com through Otterly's GEO Audit to see exactly what they measure. Then we compared it to what Stobo checks. This article breaks down the results, shows where each tool goes deeper, and helps you decide which you need based on where you are in your AEO journey.
One thing upfront: we're not going to pretend they're bad. Otterly has 15,000 users and a Gartner Cool Vendor recognition. They built something real. The question isn't which tool is better. It's which problems each tool solves.
What Otterly actually measures
Their marketing claims "25+ factors." We counted closer to 22 checks. That's more honest than some competitors claiming "100+ factors" when half are variations of the same thing.
Here's what they actually analyze:
Domain-level checks (6 factors)
| Check | What it does | Depth |
|---|---|---|
| Robots.txt | Confirms LLM crawlers aren't blocked | Binary pass/fail |
| LLMs.txt | Confirms file exists and parses correctly | Binary pass/fail |
| AI Readiness | Aggregate score from quotes, statistics, and tone | Scored 0-100 |
| Static content | Measures how much content is readable by crawlers | Percentage |
| Page speed | Lighthouse metrics for performance, SEO, accessibility | Scored |
| Structured data | HTML structure and schema presence | Binary check |
Per-page content analysis (16 factors)
The interesting part is their AI Readiness scoring. They count three specific signals:
- Quote density: How many citations from external sources appear on the page
- Statistics density: How many data points and numbers you include
- Natural language score: Whether your tone is conversational or overly formal
Research supports this approach. The Princeton GEO study found that adding statistics to content improves AI visibility by up to 40%. Citing authoritative sources increased fifth-ranked websites' visibility by 115%. Otterly built their scoring around these findings.
The remaining per-page checks cover standard technical SEO: heading hierarchy, semantic HTML, title tags, meta descriptions, Open Graph tags, mobile indicators. Important, but not unique to their tool.
What we tested
We ran trystobo.com through Otterly's GEO Audit. Instead of just showing you their interface, we'll break down what the scores actually mean.
Homepage results
| Metric | Score | What it means |
|---|---|---|
| AI Readiness | 69/100 | 4 quotes, 5 statistics, conversational tone score of 69 |
| Static Content | 98% | Almost all content is crawler-readable |
| Page Speed | 95% | Fast enough that speed isn't hurting us |
| Structured Data | 74% | Schema exists but could be more comprehensive |
The AI Readiness score is the interesting one. Otterly found we cite 4 external sources and include 5 statistics on our homepage. Research from the Princeton GEO study suggests this matters: adding statistics to content improves AI visibility by up to 40%. We're doing it, but there's room for more.
Methodology page results
| Metric | Score | What it means |
|---|---|---|
| AI Readiness | 76/100 | 10 quotes, 10 statistics, natural language score of 76 |
| Static Content | 99% | Nearly perfect crawler access |
| Page Speed | 87% | Slightly slower due to content density |
| Structured Data | 74% | Same schema coverage as homepage |
Our methodology page scores higher on AI Readiness because it's packed with research citations. That tracks with what we know about AI systems: they favour content that references authoritative sources. The Princeton study found that citing sources increased fifth-ranked websites' visibility by 115%.
Their recommendation for us
Otterly's AI generated this feedback for our homepage:
"To improve natural language score, adopt a more conversational and benefit-driven tone. Use clearer, more direct answers to anticipated user questions, provide specific examples, and integrate user-centered phrasing. Expand on why and how AEO directly benefits startups in everyday scenarios."
Fair feedback. We write technically because our audience is technical. But AI systems seem to prefer conversational content, and the research backs that up. Something for us to consider.
Where the approaches differ
The tools measure overlapping territory but dig to different depths. Here's where the differences matter most.
| Check | Otterly | Stobo | Why it matters |
|---|---|---|---|
| Robots.txt | Binary (blocked or not) | 21 crawlers checked individually | Different crawlers serve different purposes. GPTBot trains models while ChatGPT-User fetches in real-time. Blocking the wrong one has different consequences. |
| LLMs.txt | Binary (exists and parsable) | 7 sub-components scored | A file can exist but still be poorly structured. Title quality, link format, and categorization all affect how AI systems parse it. |
| Schema markup | Binary (exists or doesn't) | Type diversity + page distribution | Having schema on your homepage isn't enough. Research shows 61% of AI-cited pages use three or more schema types distributed across the site. |
| FAQ optimization | Not checked | Content-schema pairing per page | FAQ-formatted content achieves 41% AI citation rates versus 15% for unstructured content. But only if paired with FAQPage schema. |
| Direct answers | Not checked | First paragraph analysis | AI systems heavily weight opening paragraphs. The optimal range is 40-60 words with clear value proposition. |
| Content freshness | Not checked | Last-modified signals | Pages not updated quarterly are 3x more likely to lose AI citations. Freshness is a ranking signal. |
| AI Readiness | Quote count, statistics, tone | Not this approach | Otterly measures content characteristics that correlate with AI preference. We focus on technical structure instead. |
The philosophical split
Otterly asks: "Does your content read well to AI systems?"
Stobo asks: "Can AI systems find and parse your content correctly?"
Both questions matter. The Princeton GEO study found that adding statistics improves visibility by up to 40%, which supports Otterly's content-focused approach. But the same research found that proper structure and citations increased fifth-ranked websites' visibility by 115%, which supports our technical focus.
Neither tool covers everything. That's actually useful information when deciding which to use first.
Real differences in recommendations
When Otterly analyzed our methodology page, their AI suggested we simplify:
"While the content explains concepts clearly and addresses the user with actionable insights, it is still very formal and heavy with technical jargon. To further improve: use more conversational language, add real-world examples in plain English, and address the reader directly with 'you'/'your' statements where possible."
Fair feedback for most pages. But that page explains our scoring methodology. It's supposed to be technical. Their recommendation might hurt credibility there.
When Stobo analyzes a site, we flag different things. We might tell you: "Your robots.txt blocks 3 out of 7 critical AI crawlers including ChatGPT-User and PerplexityBot. This prevents real-time citations when users browse with ChatGPT." Then we provide the exact code to fix it.
Microsoft's Fabrice Canel confirmed at SMX Munich 2025: "Schema markup helps Microsoft's LLMs understand your content." That's the technical foundation we focus on. Otterly focuses on what happens after AI systems can already access you.
Different problems require different tools.
When to use each tool
Choose Otterly if your technical foundation is already solid and you want to improve how your content reads to AI systems. Otterly's AI Readiness scoring analyzes quotes, statistics, and conversational tone on every page. Their monitoring feature tracks brand mentions across ChatGPT, Perplexity, and Google AI over time. Pricing runs $29-489/month depending on how many prompts you track.
Choose Stobo if you're not sure whether AI crawlers can even access your site. We check the technical barriers that block visibility before content quality matters. If your robots.txt blocks GPTBot, your llms.txt file is missing, or your FAQ content lacks schema markup, those issues need fixing first. Our audit is free. The Premium report with implementation code costs $199 once.
Use both if you want comprehensive coverage. The Princeton GEO study found that both technical structure and content optimization independently improve AI visibility. Run Stobo first to fix foundation issues, then use Otterly to optimize content and monitor results over time. Total investment: $199 once plus $29-189/month ongoing.
Most sites we audit have technical gaps they don't know about. Start there.
Pricing comparison
| Feature | Otterly | Stobo |
|---|---|---|
| Free tier | No | Yes (full 7-check audit, unlimited runs) |
| Entry price | $29/month (Lite) | $0 |
| Mid tier | $189/month (Standard) | $199 one-time (Premium) |
| Top tier | $489/month (Premium) | $199 one-time (same) |
| Model | Monthly subscription | One-time purchase |
| 2-year cost | $696 - $11,736 | $0 - $199 |
Otterly's tiers scale by volume: Lite gets you 1,000 URL audits and 15 search prompts, Standard bumps that to 5,000 audits and 100 prompts, Premium goes to 10,000 audits and 400 prompts. Google AI Mode and Gemini tracking cost extra ($9-149/month each).
Stobo has two options. The free audit runs all seven checks with no limits. The Premium report adds an action plan, generated llms.txt file, and copy-paste implementation code.
Different models for different needs. Otterly charges monthly because monitoring is ongoing work. We charge once because technical foundation is fix-it-once work.
You probably don't need to check your robots.txt every month after you've fixed it.
What they do better than us
Credit where it's due. Otterly has strengths we don't.
Content quality signals. Their quote count, statistics count, and natural language scoring identifies content gaps we don't measure. The Princeton GEO study found that adding statistics to content improves AI visibility by up to 40%. Otterly actually counts your statistics. We don't.
Per-page granularity. They score every page individually with AI-generated recommendations. You can see exactly which pages need content work. Our audit analyzes multiple pages but focuses on technical patterns across the site rather than page-by-page content scoring.
Established user base. Over 15,000 users. Recognized by Gartner as Cool Vendor. They've proven the market wants this. We're newer and smaller.
Clean interface. Their audit results are visually clear and easy to understand. Well-designed tool. We care about design too, but they've had more time to polish.
Monitoring features. They track your brand mentions across ChatGPT, Perplexity, Google AI, and other platforms over time. You can watch your visibility change week to week. We don't offer ongoing monitoring, for now. Our model is fix-it-once, not track-it-forever.
What we do better than them
Our turn to be honest about where we're stronger.
Technical depth on robots.txt. Our check identifies which specific AI crawlers are blocked. Theirs says "blocked or not." That distinction matters more than it sounds. When ChatGPT-User is blocked but GPTBot is allowed, you get included in training data but not in real-time browsing results. Users ask ChatGPT a question, ChatGPT tries to fetch your page, gets blocked, moves on to a competitor. Cloudflare data shows AI crawler traffic grew 305% between May 2024 and May 2025. Knowing exactly which crawlers can reach you is no longer optional.
LLMs.txt quality analysis. Their check: file exists and parses. Our check: 7 sub-components including title quality, description completeness, contact info, resource organization, link format preferences, categorization structure, and context optimization. Plus we generate the file for you in Premium. Over 844,000 websites have implemented llms.txt, including Anthropic, Cloudflare, and Stripe. If you're going to have one, it should be good.
FAQ-schema pairing. We're the only tool that analyzes whether your FAQ content has matching FAQPage schema on the same page. This matters because FAQ format achieves 41% AI citation rates versus 15% for unstructured content. But only when paired with schema. Unpaired FAQs are invisible to AI systems. We catch that gap.
Direct answer optimization. We check if your first paragraph is 40-60 words, which research shows is optimal for AI extraction. AirOps found that 87% of cited pages use a single H1 as the primary anchor, with opening paragraphs providing extractable context. We measure whether yours does.
One-time pricing. Fix technical foundation once. No recurring monthly fees. Pay $199, get implementation code, deploy fixes, done.
The honest assessment
Otterly is good at what they do. They're not our enemy. The GEO market is projected to grow from $848 million to $33.68 billion by 2034, 50.5% CAGR. There's room for multiple winners.
What we learned from testing their tool: content quality matters, and their approach to measuring it (quotes, statistics, tone) is research-backed. The Princeton study confirms these signals affect citations. Their AI-generated recommendations provide real value.
But they don't check the things that block citations in the first place. If your robots.txt blocks ChatGPT-User, no amount of content optimization will get you cited during real-time browsing. If your FAQ content lacks schema markup, AI systems might miss it entirely. If your llms.txt file has structural issues, the context AI systems extract could be incomplete.
Technical foundation comes first. Content quality comes second. Both matter.
What actual users should do
Starting from scratch: Run Stobo's free audit first. Fix technical barriers before worrying about content quality. Consider Premium ($199) for implementation code.
Technical foundation already solid: Use Otterly to assess content quality and monitor ongoing visibility.
Budget for both: Stobo for the one-time technical fix, Otterly for ongoing monitoring. They're complementary, not competitive.
Questions we get about this comparison
"Why are you being so nice to a competitor?" Honest comparisons build trust. Otterly is a legitimate tool. Pretending otherwise would be dishonest and obvious. The AEO market is early enough that multiple tools can win.
"Should I use both?" If you can afford it, yes. If budget is limited, start with technical foundation (Stobo) because blocked crawlers make content optimization irrelevant.
"Which tool is better?" Wrong question. Stobo: technical foundation depth. Otterly: content quality monitoring. Pick based on what you need to fix first.
Last updated: December 30, 2025 Tested with actual Otterly GEO Audit reports for trystobo.com