Monitoring or fixing?
When a shopper asks AI what to buy, it names a few stores. These tools split on one line: some only show you where you stand, some fix your page so you get cited.
Most tools are monitoring dashboards: they tell you where you stand, they don't change anything on your page.
We measured 40 stores: more than half (52%) were not cited by AI for their own product's buyer queries. And when AI did name a store, one in three times it wasn't the one selling the product.
The dividing question: do you get a dashboard, or the finished fixed page + schema code.
Google's AI Overviews already answers over 2 billion users a month (Google, 2025). The shopper reads the AI's answer, not a list of results. If you're not in the answer, you're not in the decision. Classic SEO isn't enough: ranking in results doesn't mean you get cited in the AI's answer.
What each one actually does
Ecommerce, SKU-level. Monitors who gets mentioned and acts to fix it. Tied to Yotpo's stack (reviews/loyalty).
Enterprise AI-visibility analytics, broad engine coverage. Monitoring.
Mid-market monitoring and benchmarking.
Entry-level brand-mention and citation tracking.
Per product page, per run, any platform. Not a dashboard: measures who AI cites and hands you the fixed product page + schema code to add yourself.
| Tool | Does | Platform | Output |
|---|---|---|---|
| Yotpo Discover | Monitor + fix | Yotpo stack | Dashboard + actions |
| Profound | Monitor | Platform-agnostic | Dashboard |
| Peec AI | Monitor | Platform-agnostic | Dashboard |
| Otterly.ai | Monitor | Platform-agnostic | Dashboard |
| Outcite | Fix | Any | Ready page + JSON-LD |
Four questions before you buy
- Monitoring
- Does it only monitor, or does it fix your page?
- Platform
- Does it work on your platform (Woo, Shopify, anything) or is it locked in?
- Output
- Do you get a concrete deliverable (page copy + schema) or just a metric?
- Pricing
- Do you pay an ongoing subscription or per need?
If you want portfolio-scale monitoring and have a team for it, a monitoring dashboard fits. If you want a specific product page to start getting recommended, you need the fix: finished page copy and schema code. Outcite does the latter per product page, on any platform, with no subscription.
You'll get a verdict. And a fix?
Run this and in two minutes you get what a monitoring tool gives you: a verdict on whether you're known. Then the prompt asks the model what you should actually change tomorrow morning — and to mark what data it is missing. That second half is what a dashboard never hands you.
Do not browse the web. Answer only from what you already know. PART 1 — do what a monitoring tool does: 1. Do you know the brand ? If not, say so plainly. 2. If someone asked you for a recommendation in the category , would you name this brand? Yes or no, and why. PART 2 — now do what a dashboard doesn't: 3. Tell me exactly what I would have to change on my product page, field by field, for you to name me. No generic SEO advice. 4. Next to each item, mark what data about my store you are missing in order to say it with confidence. 5. Finally count: how many of your items stayed guesses because the data was missing? Be direct. If you can't be specific, that is the result of this exercise.
- What you saw
- Part 1 gave a verdict — exactly what a monitoring dashboard sells you for a monthly fee. Part 2 fell apart, because the model has no data about your store to be specific from.
- What was missing
- The same thing in both halves: structured product data. Without it the model neither names you nor can tell you why not.
- What we do
- We produce that data and put it where AI reads it. The audit tells you what's missing; Outcite fixes one product page at a time.
Schema code written by an AI hardcodes whatever values happened to be on the page at the moment it ran. Price, availability and stock freeze at that second, and after the first discount your structured data tells machines a different price than the page tells a human. We put the data into the platform's template, where the values are read from the same source as the visible page — so it stays correct without anyone touching it.
The prompt tells you which fields are missing. It doesn't know their values. The model doesn't know your GTIN, your fill power, your certification or your store-level stock. Ask it to fix the page and it will invent them — and invented product data, once published, is worse than missing data: it's a consumer-law problem and it comes back as returns.
In a chat window you fix one product once. The problem is hundreds or tens of thousands of products, in every language, and again every time the catalogue, the price or the stock changes. That's a pipeline, not a prompt.
The model prints JSON-LD as text in a chat. It still has to live in your platform's template, per language, valid, and survive theme updates. That is wiring work into your platform, not copy-paste.
The model assesses itself from memory, on one AI surface, at one moment — it usually says so itself. We run ChatGPT, Perplexity and Google AI, on the same queries, repeated over time.
GEO (Generative Engine Optimization) means shaping content and data so AI answers (ChatGPT, Perplexity, Google AI) surface and cite you. AEO (Answer Engine Optimization) is nearly the same, framed around answer engines. Both aim at the same thing: getting named in the AI's answer, not just the results list.
Not on its own. Ranking in results doesn't mean you get cited in the AI's answer — they are different machinery. AI surfaces sources by how clearly and structurally a page answers the question, not by ranking alone.
A monitoring tool shows a dashboard: where you rank and who gets mentioned. It changes nothing on your page. A fix gives you a concrete deliverable — better page copy and schema code — that you add to your page so AI starts citing you.
Yes. AI answers in the language it's asked and cites that language's pages. The JSON-LD and content must be in each language page's own language to be cited in each market.
Some tools are platform-agnostic, some are locked to a stack. Structured data (schema.org) itself works on every platform; the difference is whether the tool gives you the finished code and steps for your platform, or just a metric.
What does your store look like to AI?
A free audit. No signup, works on every platform.