The Growth Newsletter #322How to overtake incumbents in AI search (Part 1 of 3) Truly disruptive distribution platforms come along maybe twice in a generation. The web. Then mobile. That's the list for the last 30 years. When they arrive, the slate gets wiped clean. Incumbent moats evaporate. Entirely new companies emerge and claim distribution that took the old guard a decade to build. AI's technology shift already happened. The distribution shift is just beginning. For the first time in 15+ years, startups have a real shot at claiming ground from companies 100x their size. Today, we're kicking off a 3-part series with Zach Boyette, Managing Partner of our new AI search agency, Saturation. Zach has been building at the frontier of AI search longer than almost anyone. He makes the case for why this is a blue ocean opportunity for startups — and shares a 5-step framework to start taking advantage of it. Brought to you by Insense Save 40+ hours on influencer and UGC campaigns Their creator marketplace handles everything from:
Join brands like Bones Coffee, Quip, and Easy A Media who trust Insense for all their UGC and influencer marketing needs. Match their results with a 2.16 ROAS, 85% influencer activation, and 100+ assets in 45 days. 👋 Want to get in front of 105,000+ founders and marketers? Let's chat. AI Ate Your FunnelInsights from Zach Boyette — Managing Partner @ Saturation Try something right now. Open ChatGPT, Perplexity, or Gemini and type in a query your ideal customer would ask before buying your product. Something like: "What's the best project management tool for a 15-person startup?" Look at the answer. Not the ads. Not the search results. The answer. If you're not in it, your potential customers aren't finding you in the fastest-growing discovery channel in the world. And unlike traditional search, there's no page 2 to scroll to. There's no page at all. AI gives them three to five options. They pick from the list. If you're not on it, you don't exist. How AI search actually works (and why it's nothing like Google)Traditional SEO trained us to think about rankings. Position 1 through 10. Blue links. Click-through rates. AI search doesn't rank. It recommends. When someone asks ChatGPT for a project management tool, it doesn't crawl the web in real time and score pages. It synthesizes everything it's absorbed about your brand, your competitors, your reviews, your content, your presence across the internet, and generates a curated shortlist. This means the game has changed in three fundamental ways: 1. It's a reputation game, not a ranking game. Google rewarded pages. AI rewards brands. The model's "opinion" of you is built from thousands of signals across your entire web presence, not a single optimized page. 2. Every model sees a different internet. ChatGPT, Perplexity, Gemini, and Claude each train on different data, weight sources differently, and update on different cycles. A study of 100,000 prompts across ChatGPT and Perplexity found only 11% overlap in the domains they cited. You might be visible in one model and invisible in another. 3. Size matters less than you think. In traditional search, domain authority gave big brands an almost unbeatable advantage. In AI search, the playing field is more open. Models care about consistency and specificity. A startup that shows up clearly and consistently across niche sources can outperform a Fortune 500 company that has a scattered, generic presence. This is the window. It won't stay this open forever. The 5-step AI visibility checkHere's a practical way to find out where you stand. This takes about 20 minutes. Step 1: Ask what your customers askOpen ChatGPT, Perplexity, and Gemini. In each one, type 5–10 queries your ideal customer would ask before buying. Not branded queries (those are easy). The unbranded ones:
Track your results in a simple grid: query on one axis, model on the other. Mark whether you appear, and in what position. Step 2: Test across all major modelsDon't stop at one. The 11% domain overlap finding means your visibility is model-specific. You might rank #1 in Perplexity and not exist in ChatGPT. Test at minimum:
You're looking for patterns. Where are you consistently present? Where are you consistently absent? Where does it vary? Step 3: Study the descriptions (this is where the real insight is)This is the step most people skip, and it's the most valuable. Don't just check whether you appear. Read how the model describes you. When AI recommends your product, it attaches a description. That description is your brand positioning as understood by the model. You didn't write it. You don't control it directly. But it determines whether the user clicks or scrolls past. Ask yourself:
Compare your descriptions to your competitors' descriptions. If theirs are more specific and compelling, the model has a better understanding of their positioning than yours. That's fixable, but you have to know it's happening first. Where descriptions come from: The model builds its understanding from your website copy, review sites, Reddit threads, press coverage, comparison articles, and documentation. If those sources tell an inconsistent story, the model's description will be vague or wrong. If they tell a clear, consistent story, the description will be sharp. Step 4: Identify why you're winning or losing each queryFor every query where a competitor appears and you don't (or where their description is stronger), diagnose the gap. It's usually one of three things: Coverage gap: The competitor has more content addressing that specific query across more sources. They have a blog post, a comparison page, Reddit comments, a G2 review, and a podcast mention all reinforcing the same message. You have a homepage and a blog post. Consistency gap: You have the content, but it tells different stories in different places. Your homepage says "enterprise-grade." Your Product Hunt launch said "perfect for solo founders." Your G2 reviews focus on price. The model can't form a clear picture because your signals conflict. Specificity gap: The competitor is positioned for a specific niche. You're positioned for everyone. AI models favor specificity because it makes the recommendation more useful. "The best CRM for B2B SaaS companies with 10-50 employees" beats "a CRM for businesses of all sizes." Once you know which gap is the problem, you know where to focus. Step 5: Prioritize by buying intentYou now have a map of where you're visible, how you're described, and where the gaps are. The question is: where do you start? Start with the queries closest to a purchase decision. Here's how to identify them: High buying intent (fix these first):
Mid intent (fix these second):
Low intent (fix these later):
For your top 2-3 high-intent queries where you're missing or poorly described, build a focused plan: what content needs to be created, updated, or distributed to close the coverage, consistency, or specificity gap you identified in Step 4. Why we built SaturationWe built Demand Curve to help startups operate at the frontier of growth. That hasn't changed. But when we look at AI, we don't see a new channel to bolt onto the existing playbooks. We see a platform shift that requires its own approach. New mental models, new skill sets, new team structures. So we took our own advice and built something purpose-built for it. That's Saturation. If you want to see how your startup shows up in AI search today, start with a free AI search audit at saturation.co → This is Part 1 of a three-part series on AI search strategy. Next up: How to systematically build your AI visibility across models. Until next week! Thanks y'all! |
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