AEO

Large language model (LLM) visibility tools track brand mentions, citations, and share of voice across answer engines. According to Digitaloft, 80% of users rely on zero-click results at least 40% of the time, meaning they often get what they need directly from a search engine results page (SERP) or an AI-generated answer. That behavior can leave marketers with fewer on-site signals such as clicks, scroll depth, and engagement rate.

Marketers choosing between Ahrefs Brand Radar and Profound are really asking whether AI visibility belongs in your SEO suite or in a dedicated AEO platform. Brand Radar is the first option, Profound is the second, and HubSpot AEO is a third worth testing if you want visibility data connected to content and marketing workflows.

If you’re comparing Profound vs. Scrunch, the buying decision usually comes down to where your AEO workflow stalls, not which tool tracks more answer engines. Both Profound and Scrunch measure how AI answers cite your brand, but they’re built for different jobs: Profound leans toward market analysis and content creation, while Scrunch leans toward technical optimization and task handoff.

Companies without the internal resources or budget to build a dedicated search department still need to know what options exist for running AEO without a large team. Answer Engine Optimization is no longer optional for companies that rely on search to generate leads and revenue. AI Overviews now appear at the top of search results before a single organic listing — and sometimes above paid ads.

Digital PR has always been about earning coverage that influences the audience you can’t reach through paid channels. While the value proposition of digital PR hasn’t changed, the definition of “showing up” has.

Clients are asking about AEO. Some have seen competitors show up in AI results and want to know what it means. Others have read that AI is changing how buyers find vendors and want to know what their agency is doing about it.

Enterprise brand teams face a complex version of AEO that most tools weren’t built for. A single brand might span a dozen product lines, operate in multiple languages, and compete in markets where local answer engines have their own citation patterns.

Buyer behavior has changed since the advent of artificial intelligence. Now, before ever filling out a form or clicking an ad, prospects are likely asking AI for recommendations, comparing vendors, and gathering answers. Those interactions shape which companies make the shortlist, but they often happen outside the systems marketing operations teams use to measure performance.

Demand generation has been built around the assumption that buyers will come to a brand when they are ready to learn about its category, whether through search, ads, content, or other channels. The funnel starts when a prospect arrives somewhere the business can see, measure, and influence it. But AI is changing what happens before that point.

Product marketing’s core job is positioning: Deciding how a product should be described, what category it competes in, and which differentiators matter most to buyers. The results are deployed through sales, content, and campaigns. But now there’s a channel that interprets and rebroadcasts your positioning at scale without asking permission: answer engines.