If your customers are asking ChatGPT, Perplexity, or Gemini for recommendations instead of typing into Google, you need a way to see whether your brand shows up in those answers. That’s what answer engine optimization (AEO) tools do. Profound, AthenaHQ, Scrunch, AirOps, and Evertune each track how often and how favorably AI models mention a brand, then help marketers act on what they find. None of them replace a content strategy. They monitor a channel that traditional rank trackers can’t see, and at Peak Marketing we’ve spent the past year testing what each one is actually good at.
Why This Category Exists Now
Search behavior split into two paths over the last two years. People still type queries into Google, but a growing share now ask a chatbot directly and accept whatever answer comes back without clicking through to a website. When an AI model answers “what’s the best trailer dealer in Idaho” or “which law firm handles employment disputes in New Jersey,” it’s pulling from a mix of its training data and live retrieval, and it’s citing sources you have no visibility into unless you’re checking manually.
AEO tools solve a specific, narrow problem: they run a set of representative prompts against multiple AI models on a schedule and report which brands got mentioned, how they were described, and which sources the model cited to justify the answer. That’s the whole category, stripped of marketing language. Everything else is a feature built on top of that core loop.
Profound
Profound built its reputation on breadth. It tracks mentions across ChatGPT, Perplexity, Gemini, and Copilot, and its reporting leans toward answering a question executives actually ask: are we winning or losing share of voice against named competitors over time. The dashboard reads more like a competitive intelligence tool than a technical SEO one, which makes it a reasonable fit for marketing teams that need to report results upward without translating jargon first. The tradeoff is that Profound’s prompt customization is less granular than some of its rivals, so niche or highly local queries sometimes get flattened into broader categories.
AthenaHQ
AthenaHQ positions itself closer to the content team’s daily workflow. Instead of stopping at “here’s your visibility score,” it tries to connect a citation gap to a specific content fix: add a comparison page, expand a FAQ section, get a specific fact onto a page the model can actually find. Agencies managing content production for multiple clients tend to like this because it turns AEO data into a brief rather than a static report. The catch is that AthenaHQ’s recommendations are only as good as the prompt set behind them, so the setup phase matters more here than with some competitors.
Scrunch
Scrunch focuses heavily on structured data and technical readability, on the theory that AI models cite pages they can parse cleanly, not just pages with the right words on them. Its audits flag schema markup gaps, ambiguous heading structure, and content that buries a direct answer under too much preamble. This makes Scrunch a natural pairing with technical SEO audits rather than a standalone reporting tool. Teams that already have a strong content operation but a messy technical foundation tend to get the most out of it.
AirOps
AirOps sits at the production end of the pipeline rather than the monitoring end. It’s built to generate and manage content at scale using AI-assisted workflows, with AEO-style visibility tracking layered in as one module among several. Marketing teams running high-volume content programs, the kind Peak Marketing runs for multiple client verticals at once, sometimes use AirOps less for its monitoring dashboard and more for the workflow automation that connects a keyword or prompt list to a drafted brief. It’s a production tool that happens to also report on AI visibility, which is a different value proposition than a pure monitoring platform.
Evertune
Evertune differentiates on measurement rigor. It runs larger, more statistically structured prompt sets and reports confidence intervals rather than a single visibility number, which matters if you’re making budget decisions based on the data. It also tracks sentiment, not just presence, meaning it distinguishes between a model mentioning your brand neutrally and one that actively recommends you over a named competitor. That precision comes with a steeper learning curve and a pricing structure aimed more at brands with dedicated analytics resources than a solo marketer checking in monthly.
What These Tools Have in Common
Every platform in this category depends on the same underlying reality: AI models cite sources that are specific, well-structured, and easy to extract a direct answer from. A page stuffed with adjectives and vague claims doesn’t get quoted. A page that states a fact, a number, or a clear recommendation in the first few sentences does. This is why AEO tooling and traditional content quality aren’t separate disciplines anymore. The tools measure whether your content is citable; they don’t make it citable on their own.
How to Choose Between Them
The right pick depends on which gap is actually costing you visibility right now.
- If leadership wants a competitive scoreboard, Profound’s reporting format fits that ask directly.
- If your content team needs a bridge from data to action, AthenaHQ’s brief-oriented output saves a translation step.
- If your technical foundation is the weak link, Scrunch’s structured-data focus addresses that directly.
- If you’re already producing content at volume and want monitoring folded into that pipeline, AirOps consolidates the workflow.
- If you need defensible, statistically sound numbers for a budget conversation, Evertune’s rigor is built for that room.
Most brands don’t need all five. Most need one monitoring layer paired with a content team that acts on what it finds.
Where This Fits Into a Broader Strategy
None of these platforms fix a content gap by themselves. They tell you where you’re invisible to an AI model and, in some cases, why. The fix still has to happen on the page: a clearer answer near the top, a fact with a source attached, a structure the model can extract instead of ignore. That’s the work that determines whether the next round of monitoring shows improvement or the same flat line.
Answer engine visibility is going to keep mattering more, not less, as AI-driven search takes a larger share of how people find businesses. Brands that treat it as a reporting exercise will fall behind the ones that treat it as a content discipline. If you’re trying to figure out which of these tools fits your situation, or you’d rather have someone build the citable content these platforms are measuring for, Peak Marketing works through exactly that kind of AEO strategy with clients across multiple industries. Reach out to talk through what your visibility gap actually looks like before you commit to a platform.
