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A bite-sized, charm-filled podcast that demystifies Answer Engine Optimization (AEO) for everyday content creators. Each 5-10 minute episode breaks down one key AEO concept in an accessible, entertaining way. Listeners will learn how to optimize their content for AI-powered search tools like ChatGPT, Siri, and Google Assistant - without the technical jargon that makes their eyes glaze over.
Hello my lovely listeners, welcome back to AEO Decoded. I'm your host, Gary Crossey. Now before we dive in, let me give a proper wee shout — because I see you. The ones listening on the commute. The ones pretending it’s “research” while you’re actually avoiding your inbox. And the ones who’ve sent me messages like, “Gary, this is wrecking my brain… but in a good way.” That’s my kind of person. And listen — thank you. Truly. This show started as my personal outlet because last year few folks were talking about AEO, and now it’s turned into this strange, lovely little global thing. Right then, we have that malarkey sorted. I sound like I’m reading the shipping forecast, I know, but it had to be done. Let’s dive into Episode 2.9 — Measurement beyond clicks: AI presence, passage‑level lift, and accuracy QA. Because here’s the truth: in 2026, the win isn’t always the click. The win is when your work shows up in the answer, gets cited, gets remembered, and quietly creates demand before the conversion ever happens. So stick with me — I’m going to give you a simple way to measure what matters, without pretending attribution is perfect.
Now for the Breakdown. Right then, let’s get stuck into measurement beyond clicks — because if you’ve ever watched a brilliant bit of work get dismissed by a traffic chart, you’ll know exactly why this matters. Remember back in the “ten blue links” days? The entire story was tidy. You ranked, they clicked, they landed, and your analytics lit up like a Christmas tree. Grand. But now we’ve got answer engines. And they don’t always send you the click — they send the user the answer. So what’s “measurement beyond clicks” when it’s at home? Think of it like this: if clicks are foot traffic into your shop, then AI presence is people talking about your shop in the middle of town, recommending it, and sending others your way — even if you never see them walk through the door that day. Here’s why this is the absolute business when you think about it: if you only measure site visits and clicks, you’ll swear you’re losing while you’re actually shaping the market. And the worst thing you can do is stop right when it compounds. Let me give you a real‑world example. You’ll see this all the time with service businesses and B2B. A team cleans up its pages, tightens its claims, gets cited in AI answers… and traffic stays flat. But suddenly the leads come in with better questions. Sales calls move faster. People say things like, “I keep seeing you mentioned,” or “I feel like I already trust this.” That's a business impact showing up downstream — and if you’re not measuring for it, you miss the win. So let me break down the three core components of measurement beyond clicks in practice.
Component 1: Presence (Are we showing up?) This is where most teams fall down because they keep measuring the wrong thing. They look at sessions and think that’s the complete story. But the better question is: when people ask the questions that matter in your niche, do you appear in the answer? The fix is dead simple: pick a set of proper questions — not vanity ones — the ones that signal buying intent or trust intent. Then check the same questions every week, in the same 2–3 answer engines, and log what you see. If you’re local, it’s “who do I hire” questions. If you’re SaaS, it’s “what tool should I use” questions. If you’re in healthcare, it’s “What does this mean and what do I do next” questions. That’s a presence. You’re basically checking: are we in the room when the decision is being made? Component 2: Quality (Are we being represented correctly?) Here's where it gets spicy. Because being mentioned isn't automatically a win. If the model gets your product wrong, makes up a feature, or turns a careful, qualified point into a confident half‑truth — that's not visibility. That's you being misquoted at scale. And the worst part? You won't even know it's happening unless you're actively checking. Let me give you an authentic example. Say you're a SaaS company that offers a free trial with a credit card requirement. But the AI answer says "no credit card needed." Now you've got leads showing up annoyed, support tickets piling up, and your team managing expectations that were set by a hallucination. That's not a win — that's a mess. Or maybe you're a consultant who specialises in B2B FinTech compliance, but the model drops the "FinTech" bit and just says you do "compliance consulting." Now you're being recommended to people who needs something entirely different? You're visible, sure — but to the wrong audience, for the wrong reason. So you score quality like a normal person would. Is it accurate? Is it safe? And if it cites you, is it citing the right page for the right claim? I use a simple three‑point scale: Good (accurate and helpful), Okay (mostly right but missing context), and Bad (wrong, misleading, or unsafe). You don't need a PhD to score this — you just need to read it like a customer would and ask: "Would I be happy if these people heard about us?" When quality is strong, trust builds. People feel like they already know you. When quality is messy, you're doing brand damage without even knowing it — and no amount of traffic will fix that. Component 3: Business impact (Is it changing outcomes?) Business impact proves your AEO work is worth continuing — especially when leadership questions the investment. Here's the thing: clicks still matter, but they're not the only receipt anymore. In fact, some of the most valuable work you'll do in 2026 won't show up in your traffic chart at all — and if you're not ready for that, you'll panic and stop the work right before it delivers results. So what do you watch for? The downstream signals that show up after presence and quality improve. Branded search creeping up — people looking for you by name. More direct visits and repeat visits — they already know where you live. Better leads with shorter cycles — and more "we already know you" conversations in the sales process That's the business impact in action. And it's real. You just have to know where to look.
Q&A Lightning Round. Right then — let's dive into the Q&A Lightning Round. This is where I get to tackle questions from listeners. Let’s get stuck in with our first one. For the first question today from Jane in LA — if traffic is flat, how do I prove this is working? Brilliant question, Jane — and it’s the exact one that gets thrown at you in meetings. You don’t prove it with “more sessions.” You prove it with presence and quality trends first. Are you showing up more often for the questions that actually matter, and are you being represented accurately? Then you tie it to the business impact. Better leads. Better calls. More “we already know you” conversations. That’s the win, even when the click doesn’t happen. Regarding today's second question from Marcus in Singapore: What is the simplest way to track AI presence without purchasing specialized tools? Great question, Marcus — and I hear this one constantly. Keep it dead simple. Pick ten questions tied to real intent. Run them in two or three answer engines once a week. Take a screenshot, paste the answer into a sheet, and log three things: did you show up, did it cite you, and was it accurate. The trick is consistency. Same questions every week. Otherwise, you're not measuring change — you're just collecting vibes. Now for the third question today: How do I stop AI from making my brand sound wrong or risky? Think of it like reputation management, not SEO. Start by finding the questions where you're being mentioned but misrepresented. Then go straight to the passages the model is actually pulling from. Tighten your definitions. Add clear constraints. Include dates where they matter. And craft one "best paragraph" — the kind you'd be happy to hear read back to a customer. When you make the truth easy to quote, the model has far less room to invent. For the last question today: What do I report to leadership when attribution is messy? Don't pretend it's perfect — build a defensible story instead. Report three things: Presence (your share of answers across your 10 core questions), Quality (score each as good, okay, or bad with quick notes), and Business impact (branded search trends, direct and repeat visits, lead quality improvements, and shorter sales cycles). Present it like a proper programme with clear metrics, not a "magic AI dashboard" that promises perfect attribution. That's how you show the work is landing, even when the click doesn't always happen. And that wraps up our Q&A for today. And listen — if you've got a question you’d like me to cover in a future episode, send it my way. Seriously. Email me, message me, whatever works. I love hearing from you, and your questions make this show better.
Your One Actionable Item Here’s what I want you to do this week, and it’ll take you about an hour. Build a 10‑question “Share of Answer” baseline, and score each answer for Presence, Quality, and Business impact. Pick ten questions that represent actual intent in your world. The ones a buyer asks right before they choose. The ones your sales team hears on calls. The ones that actually move money. For each question, run it in 2–3 answer engines you care about and capture the output (screenshot or paste into a doc). Then log three things. Presence: Did your brand show up, yes or no? If yes, were you cited, and which page did it pull? Quality: Score it Good / Okay / Bad. If it’s not good, write one line about what’s wrong (missing context, wrong feature, unsafe claim, sloppy attribution). Business impact: One sentence. If a prospect read that answer, would it make them more likely to trust you, or less? Would you be happy hearing it repeated on a sales call? Don’t overcomplicate it. You’re not trying to build a perfect attribution model. You’re building a baseline you can improve. Once you’ve done the ten questions, pick one “Okay” or “Bad” result and do one fix. Rewrite the one passage on your site that should get quoted so it’s clearer, safer, and easier to cite. Do the same ten questions again next week and watch what moves. Thanks for spending this time with me. And you know what? I can hardly believe it — next week is the last episode of Season 2. Honestly, the time has absolutely flown by. But don't worry — I've got something exciting lined up for you. Tune in next week to hear the announcement for Season 3, and trust me, you're going to want to be there for it. Until then — I'm Gary Crossey, helping you make your content speak AI fluently, so it earns answers, not just clicks.