Before we break down the Loop framework, let's get on the same page about why a new playbook is even necessary.

The core problem is that the traditional inbound marketing funnel (largely built on attracting organic traffic from search) isn't quite flowing like it used to. The evidence is mounting…

• The Rise of Zero-Click Search: Nearly 60% of Google searches now end without a click. Instead of browsing links, people are getting answers directly from generative AI.
• Scattered Customer Attention: Your audience’s attention is now fragmented across a dozen different channels like YouTube, TikTok, Reddit, and podcasts.
• The Declining Power of the Blog: Even HubSpot is now seeing 90% of their leads coming from non-blog sources, with YouTube leads up 100% and newsletter leads up 90%.

This is where the distinction between SEO and AEO becomes critical. Traditional SEO is largely determined by how well your site indexes on a single platform (mostly Google), driven by content quality, technical on-site SEO, and backlinks. AEO is different. LLMs don't merely pull from your website; they synthesize answers from data across multiple surfaces where your brand is mentioned and described.

Here's an example to make this concrete. In the pre-LLM era, getting your product mentioned in a Reddit comment or a YouTube video was great for awareness, but it wouldn't help your "SEO juice" without a direct backlink. In the LLM era, that's no longer true. Since AI models are trained on full video transcripts and entire comment threads, simple brand mentions now impact how you show up in AI answers. As HubSpot puts it, brand mentions are the new backlinks, and things like Reddit posts, YouTube videos, and reviews matter more than ever.

So like it or not, it appears we’re no longer just optimizing for Google's crawlers. We're also optimizing for a swarm of AI models that learn from the entire internet.

The top sources LLMs cite:

Decoding the Loop: A Founder's Translation

Seeing that list of sources can be overwhelming. The idea of managing your brand's presence across Reddit, YouTube, and a dozen other platforms feels like a tall order for most lean startup teams.

This is where HubSpot's Loop Marketing comes into play. It's a framework designed to bring order to this chaos by helping you tell a consistent, compelling story across all the surfaces AI models learn from.

HubSpot's framework is a cycle with four stages. Here's the official definition, and our translation of what it means for your AEO strategy.

1. Express

• HubSpot’s Definition: Define your brand’s unique taste, tone, and point of view before you bring in AI.
• Translation: Nail Down A Unified Message. Before you even think about creating content, it’s smart to decide on the single, consistent message you want AI crawlers to find everywhere. This is because LLMs appear to get more confident when the same story is repeated across multiple trusted surfaces. If your message is fragmented, so is their understanding of your value.

For example, let's say your company is a new AI note-taking app (like Fathom or Fireflies). If your website claims your key differentiator is "seamless integration with project management tools," a YouTube review you sponsored highlights its "superior transcription accuracy," and a Reddit thread praises its "unbeatable price," an LLM sees three different, conflicting signals. AEO experts are urging marketers to pick one core message and stick to it.

2. Tailor

• HubSpot’s Definition: Use AI to make your interactions with customers personal, contextual, and relevant at scale.
• Translation: Plan Your Content for Specific Audiences. This is the strategy phase. Once you have your core message (from the Express stage), “Tailor” is about using AI to identify your key customer segments and plan content that speaks directly to their pain points. The power of AI here is making this level of personalization feasible for a small team, where it might have previously been cost-prohibitive.

Continuing the AI note-taker example...Let's say you've decided your most strategic differentiator is "seamless integration." You analyze your user base and find three main archetypes: startup founders, enterprise sales execs, and growth marketers. The Tailor phase is where you can use AI to help brainstorm, outline, and create laser-focused landing pages, blog posts, Reddit threads, etc. for each of those segments, all reinforcing your chosen core differentiator.

3. Amplify

• HubSpot’s Definition: Diversify your content and distribute it across the channels and surfaces where both humans and bots will find it.
• Translation: Execute Your Plan on the Right Surfaces. If “Tailor” was the strategy, “Amplify” is the execution. This is where you take the content plans you created and deploy them on the high-value surfaces that LLMs are crawling. You’re strategically placing your tailored content where it will have the most impact for AEO.

4. Evolve

• HubSpot’s Definition: Use AI to iterate on your strategy quickly and effectively in real time.
• Translation: Measure and Adapt. This is the crucial feedback loop. Once you’ve amplified your content, you need to track what’s working. For example, if you launched a Reddit AEO strategy, the Evolve stage is where you check back in. Are you seeing an increase in brand mentions? Is your AEO score improving in tools like HubSpot’s AEO grader? This is where you analyze the data and decide whether to double down, pivot to a new surface, or refine your messaging.

This framework is general enough to be executed with any toolset. However, it's clear that HubSpot has intentionally built its product suite to power each stage of this loop, making it worth a look if you're searching for an integrated solution to manage the whole process.

So, What Now? Four AEO Topics We're Thinking About at Demand Curve

Look, we could attempt to give you a 7-step playbook on how to execute an AEO strategy. But frankly, we're learning AEO for the first time too, and it's top of mind considering the recent launch of Growth Program 2.0. So after digging into HubSpot's Loop framework and the broader conversation around AEO, here are the four big takeaways our team is discussing at Demand Curve.

1. Establish A Baseline

Before diving into a new strategy, it’s always smart to know your starting point. You can't improve what you don't measure, and AEO is no different. Since this is new territory for most of us, getting a clear baseline can feel a bit abstract.

To establish a baseline, we started with HubSpot’s free AEO Grader. The tool generates an AEO score out of 100 by scanning a URL, and provides an actionable checklist of recommendations. The score is based on factors that AI models prioritize, like content readability, author authority, and trustworthiness. It provides a quick snapshot of where a site stands before you make any changes.

2. Good AEO Starts with Good SEO

The idea of optimizing for a dozen new platforms is daunting, so our next question was, "Do we have to throw out our entire SEO playbook?"

The answer, thankfully, is no. As SEO expert Matt Kenyon explains, ranking in AI search largely boils down to "doing good SEO with a few important nuances." The established fundamentals are more important than ever.

AI models still need to find and understand your content. This means:

• Crawlability is key: AI crawlers like OpenAI’s GPTBot and Google’s crawlers need to be able to access your site. Your robots.txt file must allow them in. If you’re non-technical, it might be worth hiring someone to make sure your site can be crawled.
• Structure matters: A clear hierarchy of headings, bullet points, and tables makes your content easy for both humans and AI to parse. Groundbreaking, right?
• Schema is your friend: Using schema markup to explicitly label your content (e.g., as an article, organization, or product) is critical for helping AI understand exactly what it’s looking at.

The takeaway for us is that strong SEO practices are the foundation for any AEO strategy. So, if you're already doing that, you're in a great starting position.

3. We're Auditing Our Brand's Digital Footprint

HubSpot's framework points out that LLMs synthesize answers from data across multiple surfaces. While a backlink from an aggregator site like G2 or Crunchbase might not carry the same weight as an editorial link in traditional SEO, its role in AEO seems to be different.

LLMs build confidence by seeing the same story repeated across multiple, trusted platforms. This has us thinking about the importance of brand consistency everywhere. We're planning a sprint to audit and align our messaging on platforms like:

• ​Wikidata (the structured database behind Wikipedia)
• Business directories like G2, Crunchbase, and Google My Business​
• Niche industry databases

If an AI model sees Demand Curve described consistently across our website, LinkedIn, G2, and YouTube transcripts, it's more likely to trust that narrative and repeat it in an answer. This makes auditing our "digital footprint" for consistency a new priority.

4. We're Systematizing Outreach for Brand Mentions

The idea that "brand mentions are the new backlinks" is probably the single biggest shift for us. While Demand Curve already has a decent SEO presence from nearly a decade of consistent content creation, our social presence outside of LinkedIn is, well…lacking. An unlinked mention in a Reddit comment or a mention in a creator's YouTube video now appears to be a powerful AEO signal.

With that in mind, our next step is to get more high-quality mentions on the surfaces that AI is trained on. This effort looks a lot like a traditional link-building or digital PR campaign, but the goal is different. We're planning to target creators on YouTube, Reddit, and high-signal newsletters to generate authentic conversation and mentions, whether linked or not.

A key part of this effort is making it easy for creators to talk about us (and make content about us). To that end, we're taking a page from our favorite creator marketing expert and building out media drop kits that give creators everything they need in one place: our core message, stats, unreleased brand assets & videos, curiosity-inducing storylines, etc.

The Bottom Line

Ultimately, HubSpot's Loop framework provides a solid mental model for organizing these efforts. Define your story (Express), tailor it (Tailor), seed it where it matters (Amplify), and measure the impact (Evolve). The inbound traffic playbook is no longer about winning a single algorithm on a single platform (we're looking at you Google). It's about shaping the entire conversation around your brand across the open internet.

The beauty of this approach is that you can execute it with any toolset, making it accessible to most teams. And while you can certainly run this play using your own stack, it’s worth noting HubSpot has built its entire marketing suite around the concept of Loop Marketing. So whether you patch together your own process or give Hubspot’s AI Marketing Suite a shot, it’s probably time to start thinking about your AEO strategy. Because the brands that move quickly will become the default answer in their niche.

​Kevin DePopas​
​Demand Curve Chief Growth Officer

​Gil Templeton​
Demand Curve Staff Writer