Here is how to turn that list into a plan, and what to do when the whole category is dominated by a source you cannot join.

Why are citations more useful than mentions?

A mention tells you whether you appear. A citation tells you why. When an AI recommends three tools and names your competitor, the sources it pulled from explain the gap. If five of its citations are a comparison article you are missing from, that is a specific, fixable problem rather than a vague visibility issue.

Work backwards from sources. Mentions are the symptom; sources are the cause.

A source-driven action loop

1. Export the citation sources for your top ten prompts.
2. Group them: review sites, comparison blogs, forums, official docs, news.
3. Mark which ones already include you, and which mention competitors only.
4. For the gaps, find a legitimate route in — a corrected listing, a guest contribution, or a genuinely better page of your own.
5. Publish or reach out, then re-check the same prompts in 4-6 weeks.
6. Keep the sources that worked and drop the ones that never cite anyone in your space.

Give it a full month. AI answers update on a lag, and pinging the dashboard daily just teaches you about noise.

What actually changes an AI answer?

Three things, in order of impact. Structured, factual pages that answer a specific question clearly. Presence on the third-party sites the model already cites. And consistency — the same facts about your product across sources, so the model is not resolving conflicting claims. Vague marketing copy rarely gets quoted; a clear page with prices, limits, and comparisons does.

How do you handle a locked category?

If the same two big review sites dominate every citation and you cannot get listed, stop fighting there. Shift to adjacent prompts where the sources are blogs and forums you can join, or create the comparison content yourself and aim to become the cited source rather than a subject of it. Owning the source is more durable than trying to be listed on someone else’s.

What should you measure over time?

Track mention rate for a fixed set of prompts monthly, and share of voice against the same three competitors. Add a simple proxy for business impact — does your brand-name search volume rise as AI mentions rise. If mentions climb but brand search stays flat, you are being named without being remembered, which usually means the framing is weak.

Who should run this loop?

Teams with enough content output to act on the findings: a marketing team that can publish two pages a month and reach out to a handful of sites. If you cannot act on the data within a quarter, tracking it now is just entertainment.

Key Takeaways

• Citations explain mentions; work backwards from sources to find fixable gaps.
• Group sources by type and target the gaps where you are absent.
• Re-check the same prompts after 4-6 weeks, not daily.
• Clear, factual pages get quoted; vague copy rarely does.
• In a locked category, become the cited source rather than chasing a listing.

If you have ever wondered why a competitor keeps appearing when someone asks an AI for recommendations, this is the tool built to answer that.

What is Peec AI?

It is an analytics dashboard for generative engine visibility. You enter your brand and the topics or prompts you care about, and Peec runs those prompts across multiple AI models on a schedule, recording mentions, sentiment, and citation sources.

It reports on the models it supports — the major assistants — and shows you the sources the AI leaned on, which is often more actionable than the mention count itself.

How do you set it up step by step?

1. Create an account and add your brand, including common misspellings and product names.
2. Add your competitors, so the dashboard has a baseline to compare against.
3. Define the prompts you care about — the real questions buyers ask, not keyword fragments.
4. Choose the AI models to monitor and how often to check.
5. Set alerts for new mentions or sudden drops.
6. Review the source list weekly and act on it.

The prompt list is the part people rush. Ten realistic buyer questions beat a hundred synthetic keywords, because the tool is only as useful as the questions you feed it.

What do the metrics actually tell you?

Three things worth tracking: mention rate (how often you appear at all), share of voice versus competitors, and citation sources. The third is the one that drives action. If the AI keeps citing a review site you are absent from, you know where to spend effort next.

Sentiment matters too, but treat it as a rough signal. AI descriptions of brands are short and often neutral, so sentiment swings on thin evidence.

What are the limits?

AI answers are non-deterministic. The same prompt can produce different results across runs, so a single snapshot is noisy — you need trends over weeks, not a day. Coverage depends on which models the tool queries; a model it does not track is invisible to your dashboard. And a mention does not mean a click, so pair this with your normal referral analytics.

Who is it for?

Marketing teams at brands that already get recommended offline and want to know if AI search says the same thing. Agencies pitching generative engine optimisation to clients. It is a poor fit for very small businesses with no search footprint yet — fix your fundamentals before tracking visibility in a category you are not in.

Key Takeaways

• Peec AI tracks brand mentions across major AI assistants on a schedule.
• It reports mention rate, share of voice versus competitors, and citation sources.
• Citation sources are the most actionable metric — they tell you where to invest.
• AI answers vary run to run, so read trends, not snapshots.
• Best for established brands and agencies; small players should fix fundamentals first.