Peec vs Surfacely: an honest comparison for ecommerce stores
Two tools. One goal: figure out whether AI engines like ChatGPT, Perplexity, and Google AI Overviews are surfacing your store — and fix it when they're not. Peec and Surfacely both sit in the Generative Engine Optimization (GEO) space, and if you're evaluating both right now, the surface-level pitch looks similar. This post goes deeper.
We'll cover what each tool does well, where each falls short, how pricing compares, and a plain-language guide for which tool fits which situation. If you want the condensed matrix view, head to /vs/peec. If you want the full picture, read on.
What Peec does well
Honest comparison starts with credit where it's due.
Peec has a clean, brand-monitoring–oriented approach. Its core strength is tracking how often your brand name appears in AI-generated answers and whether that sentiment is positive or neutral. For brand managers whose primary question is "is AI mentioning us at all," Peec answers it clearly. The interface is polished, the onboarding is low-friction, and the prompt-tracking workflow is straightforward enough to hand to a non-technical marketing manager without much explanation.
Peec also covers multiple AI engines in its mention-tracking layer, which matters for brand-level reporting. If your KPI is brand citation share-of-voice across AI surfaces, Peec was built with that framing in mind.
Where Surfacely wins
1. Variant-level schema depth
Peec tracks whether AI mentions your brand. Surfacely audits what AI engines can actually extract from your product catalog — down to the variant level.
Most ecommerce stores with 500+ SKUs have the same structural problem: top-level product pages pass a surface JSON-LD check, but the size-12 black colorway has no structured data of its own. When a buyer asks ChatGPT "best wide-fit running shoes under $120," the AI has to infer from prose — and it gets it wrong, or skips the product entirely. Surfacely checks every PDP for JSON-LD completeness, variant-level structured data depth, heading hierarchy, and AI extraction confidence. Peec does not audit at that resolution.
2. A prescriptive playbook, not just a score
Scores are only useful if they tell you what to do next. Surfacely delivers a ranked fix list — ordered by expected score lift — with copy-paste-ready JSON-LD snippets and specific field-level instructions. If 12 of your PDPs are missing offers.priceCurrency, Surfacely surfaces that as a single fix, shows you the corrected schema block, and tells you the expected lift.
Peec surfaces brand mentions and sentiment. It does not produce a ranked fix list for schema, headings, or structured data completeness.
3. Shopify-native one-click apply
Surfacely connects directly to your Shopify store. Once you review a fix in the audit report, you apply it to live PDPs in one click — no developer required, no copy-pasting into a theme editor, no Shopify metafield wrangling. For a store owner managing 47 PDPs, the difference between "here is the fix" and "here is the fix applied" is measured in hours per month.
Peec has no Shopify integration in its current feature set.
4. Live LLM probing across 4 engines
Surfacely runs live queries against ChatGPT, Claude, Perplexity, and Gemini using category-level prompts relevant to your store. It records verbatim responses, citation presence, and sentiment — then diffs that data on a weekly cadence so you can see when an AI engine's answer changes. That's not a static audit; it's a live signal of how the machines are reading your catalog right now.
5. Weekly monitoring with drift alerts
AI engines change their answers week to week. A store that had strong AI visibility in March can lose it in April because an engine updated its retrieval logic or a competitor improved their schema. Surfacely monitors your tracked prompts weekly and sends a diff alert when your citation presence, sentiment, or score changes. The Pro tier includes monthly monitoring; the Agency tier runs weekly.
Pricing comparison
Here's how the two tools compare on price, as of this writing.
Surfacely
- Free — $0/mo. 3 audits per month on a free account, no monitoring, no Shopify connect.
- Pro — $49/mo (or $39/mo billed annually). Unlimited audits, monthly monitoring, Shopify one-click apply, 30-day audit history.
- Agency — $199/mo (or $159/mo billed annually). Multi-domain, weekly monitoring, white-label PDF export, priority support.
Peec Peec has no permanent free tier — it offers a time-limited trial, after which paid plans start at roughly €85/mo (Starter), with mid and higher tiers around €205/mo and €425/mo, plus a custom Enterprise tier. Pricing is built around prompt sets and brands tracked, and Peec has revised its pricing more than once over the past year, so confirm current figures on their pricing page before quoting them.
For a solo Shopify operator whose core question is "what does AI extract from my PDPs and how do I fix it," Surfacely Pro at $49/mo covers the full audit-to-apply workflow. Peec's pricing makes more sense for a brand team running multi-brand mention monitoring at scale.
What the audit covers — side by side
| Capability | Surfacely | Peec | |---|---|---| | Schema / JSON-LD audit | Full — coverage + validity + variant depth | Not in scope | | Heading hierarchy audit | Yes | No | | llms.txt presence check | Yes | No | | Live AI-answer probing | Yes — ChatGPT, Claude, Perplexity, Gemini | Yes — ChatGPT, Perplexity, Gemini by default; Claude is a paid add-on | | Verbatim AI response logging | Yes | Yes | | Sentiment scoring | Yes | Yes | | Citation presence tracking | Yes | Yes | | Prescriptive ranked fix list | Yes — copy-paste JSON-LD + field instructions | No | | Shopify one-click apply | Yes | No | | Continuous monitoring | Yes — monthly (Pro) / weekly (Agency) | Yes — continuous | | White-label PDF export | Yes (Agency tier) | Not documented | | Free tier | Yes — 1 audit, no signup required | No — time-limited trial only |
When to pick Peec
Peec fits best when your primary question is brand-level: "How often does AI mention us, in what context, and how does that compare to our competitors?" If you're a brand manager at a mid-market consumer goods company tracking AI share-of-voice across 3 competitors, Peec's monitoring and mention-tracking workflow is purpose-built for that.
Peec also makes sense if you're not on Shopify (or not on a platform where direct apply is a priority), and your optimization work happens through an agency or developer who translates insights into code changes manually.
When to pick Surfacely
Surfacely fits best when your primary question is structural: "Can AI engines actually extract the right product data from my store — and if not, what exactly do I fix?" If you're a Shopify store owner who wants to close the gap between "AI sees your store" and "AI recommends your store," the audit-to-apply pipeline is what you need.
Surfacely also makes more sense if:
- You have 20+ PDPs with inconsistent schema coverage.
- You want to apply fixes without developer involvement.
- You want a weekly signal of AI visibility drift, not just a one-time score.
- You're an agency managing 5+ stores and need multi-domain coverage with white-label exports.
And if you need to start for free — no signup, no credit card, result in in minutes — Surfacely's free tier covers a full domain audit right now.
The honest summary
Peec and Surfacely are not direct substitutes. They share the GEO label but answer different questions.
Peec answers: "Does AI mention my brand, and how?"
Surfacely answers: "Can AI read my product catalog, what's broken, and how do I fix it — right now, without a developer?"
If you're a Shopify merchant whose schema is incomplete on 23% of your PDPs and you want a ranked fix list you can apply in one afternoon, that's Surfacely. If you're a brand marketing team tracking AI citation share-of-voice across a category, Peec is a reasonable fit.
For the condensed feature matrix, see /vs/peec.
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