2026-06-05
Looking for an Otterly alternative? Here's how aiListing compares.
If you've been researching AI visibility tools, you've probably encountered Otterly. It's a solid product for tracking whether AI assistants mention your brand. So why would an e-commerce store choose aiListing instead?
The short version: Otterly measures the outcome (mentions). aiListing measures the outcome *and* diagnoses why you're not getting them — which is the part most stores actually need first.
What both tools do
Both aiListing and Otterly monitor whether AI assistants (ChatGPT, Perplexity, Gemini) mention your brand or products when users ask relevant questions. Both give you a mention rate, trend lines, and some form of competitor comparison.
For a large enterprise brand doing general AI visibility tracking, that overlap covers most of your use case.
Where they diverge
aiListing was built specifically for e-commerce stores selling physical products. That focus changes what the tool actually checks.
When a customer asks an AI assistant "where should I buy running shoes under €100 in Berlin?", the answer isn't just about whether your brand name appears — it's about whether the AI can *read your catalog* at the machine level. That requires:
- AI crawlers having explicit access to your site
- Product pages exporting complete structured data (price, brand, GTIN, availability)
- Collection pages rendering without JavaScript
- A sitemap and llms.txt that give the AI a navigational map
None of this shows up in a mention-rate dashboard. But all of it determines whether you *can* be mentioned for shopping queries.
This is the gap aiListing fills: a technical audit of the infrastructure beneath your mention rate, with specific findings and downloadable fixes — before you set up monitoring.
The Otterly vs. aiListing comparison
| Feature | aiListing | Otterly |
|---|---|---|
| Share-of-answer monitoring | Yes | Yes |
| ChatGPT, Claude, Gemini, Perplexity | All four | Three (no Claude) |
| Technical AI visibility audit | Yes — A–F grade | No |
| Crawler access check (robots.txt) | Yes | No |
| Product schema completeness check | Yes | No |
| Client-side rendering check | Yes | No |
| Downloadable fix files (robots.txt, llms.txt) | Yes | No |
| Competitor benchmarking | Yes | Yes |
| Starting price | €29/month | $29/month |
| Free tier | Full A–F audit, no account | Limited |
| Managed implementation | Yes — 90-day program | No |
Which to choose
Choose aiListing if: you run an e-commerce store and want to understand *why* AI systems aren't recommending you — and fix it. Start with the free audit to get a diagnosis before you pay anything.
Choose Otterly if: you're primarily interested in brand mention tracking across a broad topic set (not e-commerce buying queries specifically), and you don't need to understand the technical stack beneath the mentions.
They're genuinely different tools built for different primary use cases. There's an argument for running both, though at €29 + $29/month, most stores pick one and see what they learn.
The case for starting with a technical audit
Most stores that go straight to monitoring discover that their mention rate is low — but they don't know why. Is it because competitors have better structured data? Because AI crawlers can't access their collection pages? Because their product descriptions are being ignored?
An audit answers those questions before you spend months watching a flat monitoring trend and wondering what to do differently.
Run the free audit on your store → It takes 60 seconds, shows you a real A–F grade, and identifies the specific technical blockers between your store and AI recommendations. If you pass everything, then monitoring-first makes sense. If not, you have a prioritized fix list before you commit to a monthly tool.
On price
Both tools are priced similarly at the entry level (€/$/29 per month). The meaningful difference is what you get: aiListing's Basic plan includes 8 monitored queries, 2 AI assistants, 1 competitor, weekly re-audits, and the technical audit + fix downloads. Otterly's equivalent tier focuses on monitoring without the technical layer.
For a store that's never audited its AI visibility, the audit is where the immediate value is. Monitoring becomes high-value once you understand what's driving (or blocking) your mention rate.
Try both
Both tools have enough of a self-serve free tier that you can get meaningful data without a commitment. Run the free aiListing audit on your store, see what it finds, then decide if the monitoring layer is worth adding.
The audit is 60 seconds. If your store passes everything, the finding itself is useful — you know your AI infrastructure is solid and the limiting factor is something else.