The 2026 GEO-tool market launched ten dashboards in six months. Profound, Otterly, AthenaHQ, Peec, Hall, Semrush AI Toolkit and counting. They all answer the same question: am I cited? None of them answers the harder one: how do I start being cited?
GEO dashboards (Profound, Otterly, AthenaHQ, Peec AI, Hall, Semrush AI Toolkit, Ahrefs Brand Radar) monitor whether you're cited by Perplexity, ChatGPT search and Google AI Overviews. They don't get you cited. To actually appear in AI search answers you need presence inside the conversational sources those engines pull from — Reddit threads, Quora answers, niche forums. Use the dashboards as a measurement layer paired with a real acquisition operation, not as a replacement for one.
The rest of this piece walks through which dashboards do what, where they differ, and what the underlying acquisition layer looks like. For the broader context of where GEO sits between SEO and AEO, see our SEO vs AEO vs GEO pillar. For the Reddit-specific acquisition side of GEO (the production work the dashboards measure but do not produce), see Reddit GEO.
Open r/SEO_LLM right now. The most-upvoted question this week is "what's the best GEO tool?" The answers are a list of brand names: Profound, Otterly, AthenaHQ, Peec AI, Hall, plus the AI modules from Semrush, Ahrefs and Plerdy. The replies argue about which dashboard is prettier.
Look at the actual product these tools sell. All of them, without exception, do one thing: they ask Perplexity, ChatGPT search and Google AI Overviews a series of queries on your behalf and report back which sources are cited and whether your brand is mentioned.
That's monitoring. It's a useful product. But monitoring is not acquisition. And the GEO conversation in 2026 is collapsing the distinction.
Every GEO dashboard in the current cohort sells the same primitive: a polling loop against AI search engines, plus a CSV of which sources got cited and whether your brand was named.
Profound and Otterly compete on UI polish. AthenaHQ leans into agency-friendly multi-client management. Peec AI emphasises competitive benchmarks. Hall is bundling with social listening. Semrush and Ahrefs added GEO modules to defend incumbency. None of them are wrong. None of them are unique either, because the underlying product is the same: query the engine, count the citations.
This is roughly where SEO was in 2008. Rank trackers existed, they were useful, and they sold "are you ranking?" but couldn't sell "how to rank." The actual ranking work was done elsewhere, by content teams, link builders, agencies. The tools didn't move the ranking. They told you what the ranking was.
Today's GEO dashboards are doing the same thing for AI search. They tell you whether you're cited. They don't get you cited.
This is the state of the category as of mid-2026. Prices are publicly listed entry tiers; check vendor sites for current rates.
| Dashboard | Best for | Engines tracked | Sentiment of citation | Competitive bench | Entry price (mo) |
|---|---|---|---|---|---|
| Profound | Polished UI, single-brand teams | Perplexity, ChatGPT, AI Overviews, Gemini | Limited | Yes | ~$500 |
| Otterly | Budget monitoring | Perplexity, ChatGPT, AI Overviews | No | Basic | ~$300 |
| AthenaHQ | Agency multi-client | Perplexity, ChatGPT, AI Overviews, Claude | Limited | Yes | ~$700 |
| Peec AI | Competitive benchmarking | Perplexity, ChatGPT, AI Overviews | Basic | Yes (best in class) | ~$600 |
| Hall | Bundled with social listening | Perplexity, ChatGPT, AI Overviews | Limited | Yes | ~$800 |
| Semrush AI Toolkit | If you already pay for Semrush | Perplexity, ChatGPT, AI Overviews | No | Through Semrush data | Bundled |
All six do the same primitive: poll the engines, log citations, surface trends. The differences are UI quality, multi-client management and whether competitor benchmarks are included. None of them get you cited; they tell you whether you are.
The dashboards report on a downstream artefact: citation by an engine. The work that creates that artefact happens two layers up, in the corpus the engine pulls from. The engine cites Reddit threads, Quora answers, Stack Exchange posts, named-domain blogs and a few specialty forums. Those are the inputs.
If your brand isn't mentioned inside those inputs, no dashboard improves your situation. The dashboard tells you you're not cited. You buy a second dashboard. It tells you the same thing.
What changes the situation is presence inside the corpus. Specifically, three things:
None of these are observable from a polling dashboard. None of these are produced by a polling dashboard. They are produced by people writing in subreddits where they have karma history. That's a separate operation, and the GEO-tool market does not sell it.
We ran a sample of 240 commercial-intent queries in crypto, fintech, iGaming and creator-platform verticals during Q1 2026. For each, we recorded which sources Perplexity, ChatGPT search and Google AI Overviews cited.
The aggregate result was unambiguous. Roughly four out of five answers cited at least one Reddit thread. Three out of five cited two or more conversational sources. Brand-owned comparison pages appeared as top-three citations in fewer than one in twelve answers.
Inside the cited Reddit threads, brand mentions followed a power law. A small number of brands (usually one or two per category) were mentioned in over half the cited threads. The other brands in the same category were mentioned in zero or one. The brands in the long tail were not being cited because their dashboard told them they weren't cited. They were not being cited because they weren't inside the conversation.
A dashboard would have told the long-tail brand "no citations" every week of those four months. The dashboard would have been correct and useless.
There are three operations that change whether your brand gets cited. None of them involve a dashboard as the primary tool.
One: get into the canonical threads that already exist. For every category, there is a small set of Reddit threads (usually three to ten) that AI engines repeatedly cite. Identify them. Get mentioned inside them through in-sub residents with karma. This is the fastest path because the threads already have authority.
Two: write the canonical thread for queries that don't have one yet. Many long-tail commercial queries don't have a dominant Reddit thread yet. The first sub-credible long-form answer published in that gap gets cited. This is the highest-leverage play but takes 60-120 days to compound.
Three: maintain freshness. Engines re-crawl high-engagement threads. A two-year-old thread with new comments this month outranks a one-year-old thread that's gone quiet. Adding real-experience comments to existing high-rank threads is mechanical but works.
A dashboard can help you measure whether any of this is working. It can't do the work.
This is not an argument against the dashboards. Run one. Run two. Track which Reddit threads are cited for your top 20 commercial queries. Watch the brands that show up most. Watch which threads gain citation share month over month.
What the dashboards are good for:
What they cannot do:
The way to use the dashboard correctly is to pair it with an acquisition operation. The dashboard is the measurement layer. The acquisition is somebody, somewhere, posting credibly in the sub that owns the query. Without the second part, the dashboard is just a graph of zeroes.
A short read on the next 12-18 months in this category.
Consolidation under SEO incumbents. Semrush and Ahrefs added GEO modules to existing subscriptions. Most of the standalone dashboards will be acquired or commoditised by 2027. The product is too thin to support an independent SaaS at scale.
Sentiment and parsing layers. The next differentiation is whether a citation is positive, neutral or negative for your brand, and what context it's in. A few of the current vendors are building this. None do it well yet.
Source-attribution APIs from the engines themselves. Perplexity already exposes some source data through its API. ChatGPT and Google AI Overviews will follow. When they do, the polling-loop primitive that powers today's dashboards becomes a free utility, and the tools have to find new value.
Bundling with acquisition. The honest direction is for some of these vendors to bundle citation monitoring with citation acquisition, actual ghostwriters, actual sub-management, actual residents. The technical-PM brain in those companies usually resists this because it doesn't scale like SaaS. The category may end up with two halves: thin SaaS dashboards on one side, agencies-with-dashboards on the other.
Until then, the brands winning citations in 2026 are running an acquisition operation and using a dashboard to measure it. Not the other way around.
Are GEO dashboards a scam? No. They do exactly what they advertise. They monitor citations. The problem is monitoring is being marketed as the whole product, and it's not.
Which GEO tool is best? For pure monitoring on a budget: Otterly. For agency multi-client: AthenaHQ. For competitive benchmark depth: Peec AI. If you're already on Semrush, their AI Toolkit is good enough and saves a subscription. The differences between them are small enough that the "best" question matters less than people think.
Can a tool write content that gets cited? The content-writing tools (Surfer SEO's AI layer, Frase, Clearscope) optimise for traditional SEO rank, not for AI citation. The signals are similar but not identical. As of now, no tool reliably produces content that gets cited by Perplexity without human editorial pass.
Is GEO different from SEO? GEO is a subset of SEO that focuses on getting cited by AI search engines (Perplexity, ChatGPT search, Google AI Overviews) rather than ranking your own page in traditional search. It uses the same fundamentals (high-engagement sources, multi-source confirmation, freshness) but the output is a citation in someone else's answer, not a click to your page.
How do I track citations without a paid tool? Manual probing. Ask Perplexity, ChatGPT search and Google AI Overviews your top 10 commercial queries weekly. Log the cited sources. Cheap, slow, exact. This is what most working operators were doing as of mid-2026 before the dashboards launched, and it's still the most accurate baseline.
What if I don't have time for any of this? Then your competitors get cited and you don't. The market for AI-search citations is small enough right now that one or two brands per category dominate. By 2028 the dynamic will be similar to traditional SEO, late entrants buy expensive ladders to climb back into the conversation. The window is open in 2026.
Want a snapshot of which Reddit threads cite your category, and which brands are inside them? Get a sub map. Free, takes 20 minutes, shows you the citation landscape you can't see from a dashboard. See our Reddit Resident Network for how we operate on the source side of those dashboards.