Scooutly analyses your pricing, packaging and features alongside your competitors'. It tracks your visibility in AI answers and on Google, plus reviews and ads, on a regular schedule.
Open this on a desktop to see the full picture.
Your pages are crawled; positioning, packaging, trial terms and conversion hygiene are combined into a single score, shown next to the category average. You don't have to guess whether it's good or bad.
Every finding is labelled critical / important / minor, and the reason is tied to a competitor comparison. Anything you fix drops off the list on the next crawl.
Competitors' pricing pages are captured at whatever interval you chose, and the difference between two snapshots is extracted. A/B tests and timestamp noise are filtered out; only meaningful changes become alerts.
The same feature under different names is merged into a single row. What they have and you don't: and what only you have, is marked, and you can see which feature is locked behind which tier.
Scooutly asks five models the real questions people ask in your category; it extracts who gets recommended, which sources feed the answer and where you stand.
ChatGPT, Gemini, Perplexity, Claude and Grok all run the same question set. Reading a category from a single model is misleading.
Answers are volatile. Every question is asked three times; the result is treated as a frequency rather than a yes/no, and we look at the trend.
We never ask the model “what's my score?”. Position, weight and tone go into an explicit rubric; the same input produces the same score.
We extract which pages the model built its answer from. If you're not on them, changing your own copy doesn't help.
Direct access is tested with real bot identities. A bot reaching your page does not mean it picked you as a source.
Google's AI answer and the sources behind it are extracted separately; classic ranking and the citation side are never conflated.
The real buyer questions asked in your category are put to five models: ChatGPT, Gemini, Perplexity, Claude and Grok. Who got recommended, in what position, based on which source, all extracted and re-measured on every crawl.
We extract which pages the models built their answers from. Rewriting your own copy is weak leverage; the real work is appearing on the pages the model feeds on. Every row comes with a recommended action.
The same question model runs in classic search too. Your Google rankings and the keywords you won and lost sit side by side. The intent asked of the AI and the keyword typed into search come from the same model.
Google's AI answer and the pages it draws on are extracted separately. If your classic ranking is good but you're absent from the AI answer, the problem isn't the content: it's sources and access.
Classic search isn't a separate world: same intent, different surface. Your Google ranking, AI Overview sources and the gap to your competitors are measured on every crawl.
Every intent asked of the AI is translated into a search keyword and crawled on Google. Your rankings and the gap to your competitors sit on one axis; the two systems are measured in the same model, not separately.
Every crawl lists which query you rose on, which you fell on and where a competitor moved ahead. Position + click share are combined into one weighted score.
Whether you're cited in Google's AI answer is measured independently of classic ranking. Ranking well and never appearing in the AI answer is very common. The two are never mixed.
Your reviews and your competitors' are collected from three platforms; score averages, volume and recency sit side by side. An empty profile is a weak signal for AI too.
Reviews are split into themes and placed next to your competitor's themes. A single complaint is noise; the same sentence repeated is a market signal.
Competitors' active ads are pulled from the Meta, Google, TikTok and LinkedIn ad libraries on a schedule; creative, format and message are archived. No ad account to connect: only the public libraries are read.
The density timeline shows when a competitor stepped on the gas. A sudden rise usually means a launch, a campaign or a price move: and you find out before the market does.
The public ad libraries of Meta, Google, TikTok and LinkedIn are crawled on a schedule. Each network is tracked separately; the lifespan, format and message of every creative is archived. Who stepped on the gas and when, which message stuck and which was pulled, all become visible.
Retailo shifted its ad language from “cheap” to “reliable”
Peakly started advertising on TikTok, 9 video creatives in its first week
Vantix doubled its LinkedIn creative count in a week
Data comes from each network's public ad library. TikTok's library only covers ads shown in Europe.
Scooutly decodes the content that works for your competitors, rebuilds it in your brand and publishes it when you approve.
The same message is rebuilt in each platform's language: size, length, hook and caption all change. Pick a platform to see how your content will look there.
Your rival changed its price. Did you notice?
♫ cartly · Original audio
“Your rival changed its price. Did you notice?”
Instagram recommends up to 5 hashtags per post. The hook text sits on the first frame, so viewers with sound off read it too.
Tell your bots what you want and the content lands in your calendar. One click shows a live post's analysis or a waiting post's preview.

Hi! Videos that open with a question worked best for your competitors this week. What should we add to the calendar?
Scooutly exposes an MCP server. Connect the AI client you already use once, and your measurements land in that conversation. We also have our own assistant and it runs on credits; MCP is included in every plan.
Product names and marks are used only to indicate compatibility; they do not imply partnership or endorsement.
Four worlds sit in this table: Semrush and Ahrefs are the incumbents of classic search; Peec AI, Otterly.AI and Profound the new generation of AI visibility; Crayon competitive intelligence and Sprout Social social media management. Scooutly merges them into one analysis, adds content creation and an MCP connection on top, and shows you how every number was found.
| Scooutly | Semrush | Ahrefs | Peec AI | Otterly.AI | Profound | Crayon | Sprout Social | |
|---|---|---|---|---|---|---|---|---|
| AI visibility | ||||||||
Visibility measured in AI answers ChatGPT, Gemini, Claude, Perplexity, Grok | partial | partial | ||||||
Multiple samples per question each question asked 3 times, treated as a frequency | partial | partial | ||||||
AI Overview source tracking are you cited in Google's AI answer | partial | partial | partial | partial | ||||
Which sources the answer draws on cited pages and domains | partial | |||||||
Bot access measured apart from citation robots.txt open but still absent means something different | ||||||||
Source ownership split out your own page or a third party | partial | |||||||
| Search visibility | ||||||||
Google organic rank tracking | partial | |||||||
Keywords won and lost a diff on every round | ||||||||
Questions and keywords in one model the intent asked of the AI becomes a search keyword | partial | |||||||
Brand demand trend search interest, compared with competitors | partial | partial | partial | |||||
Keyword gap keywords a competitor ranks for and you don't | partial | |||||||
| Competitive intelligence | ||||||||
Automatic competitor discovery from four independent signals | partial | partial | partial | |||||
Competitor price tracking plan by plan, with currency | partial | |||||||
Pricing page snapshot and diff what changed, and when | ||||||||
Canonical feature comparison matrix different names mapped to one | partial | |||||||
Packaging and feature change alerts when a feature moves up a tier | partial | |||||||
Source gap sites linking to a competitor but not to you | partial | partial | ||||||
Entry-path classification self-serve signup or an editor you must email | partial | |||||||
| Reputation and ads | ||||||||
Review analysis G2 · Capterra · Trustpilot themes | partial | partial | ||||||
Recurring complaint themes extracted looks at the pattern, not individual stars | partial | |||||||
Meta, Google, TikTok and LinkedIn ad intelligence | partial | |||||||
Creative archive and messaging shifts which message a competitor has run, and for how long | partial | partial | ||||||
| Method and transparency | ||||||||
Score computed from an open formula never asked of the model, it comes from a rubric | partial | |||||||
Evidence shown for every finding raw answer and citation kept | partial | |||||||
The reason is given too not just a score, but what to do | ||||||||
| Content and social | ||||||||
Competitor social post analysis Instagram, TikTok, YouTube, X, LinkedIn, Reddit | partial | partial | partial | partial | partial | partial | ||
Hook, format and message extraction what works in a competitor's video | partial | partial | partial | |||||
On-brand content creation motion video, carousel, caption | partial | partial | partial | partial | partial | |||
Connect accounts, approve and publish cover and caption come ready | partial | partial | partial | |||||
Learns from your own post performance views and watch time steer the next piece | partial | partial | partial | |||||
| AI connection | ||||||||
MCP server read from ChatGPT, Claude and Cursor | partial | |||||||
Built-in AI assistant questions over your own data | partial | partial | ||||||
This comparison was compiled from the products' public feature pages and documentation in September 2026. Separately sold add-ons and beta features count as "partial". It changes as those products evolve.
The ones that come up first. If your question isn't answered here, write to us from Contact in the top bar.