Most advertising and marketing groups I speak to are doing genuinely good search engine optimization, and but after they open ChatGPT or Perplexity and kind within the prompts their consumers are literally utilizing, their model is nowhere to be discovered. That is the precise drawback the FSA Framework was constructed to unravel.
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For the final decade, standard knowledge has been, “Do good search engine optimization, and the remaining takes care of itself.” That assumption was secure, and lots of manufacturers benefited from a well-executed search engine optimization technique (hey, income!). Nevertheless it doesn’t work anymore.
The mismatch isn’t as a result of search engine optimization is damaged. search engine optimization is doing precisely what it was designed to do. The issue is that engines like google prioritize rating the most effective useful resource, and reply engines prioritize offering the most effective reply..
These are two very totally different machines, and so they reward two very various things.
Desk of Contents
What’s the FSA Framework?
The FSA Framework stands for Freshness, Construction, and Authority — the three alerts that reply engines truly consider when deciding which sources to quote inside a generated reply. It’s the diagnostic lens I take advantage of to determine why a model is or isn’t displaying up in ChatGPT, Perplexity, Gemini, and Google’s AI Overviews, and what to repair first after they’re not.
Every pillar does a unique job:
- Freshness determines whether or not your content material will get reconsidered when new prompts are available in.
- Construction determines whether or not a mannequin can truly raise a clear reply out of your content material.
- Authority determines whether or not the mannequin comes again to your model the subsequent time a associated immediate exhibits up.
Miss one, and the others can’t absolutely compensate. When all three are working collectively, your content material stops being a candidate and begins being the apparent selection inside an AI-generated reply.
The place the FSA Framework Got here From
In 2025, I began utilizing my very own web site as a testing floor for reply engine optimization. I had a hunch about AEO, and nobody was operating the experiments I needed to learn. So, I ran them myself throughout ChatGPT, Perplexity, Gemini, and Google’s AI Overviews, monitoring what surfaced for every immediate and — extra importantly — what didn’t.
In one experiment, I up to date a single web page utilizing the ideas I’d been creating, and tracked AI Share of Voice throughout the complete window. The web page was on a subject the place Search Engine Journal — a legacy writer with the sort of area authority most entrepreneurs would kill for — had been the dominant cited supply for months.
Inside 96 hours, AI Share of Voice for Cassie Clark Advertising on that subject moved from round 27% to 72.7%. Search Engine Journal dropped to 0% visibility in the identical window. There have been no new backlinks and no promotional push. I simply had a better-structured, more energizing, extra extractable model of the identical thought.
Beneath conventional search engine optimization logic, this could not have been attainable. A solo strategist’s website shouldn’t displace a legacy writer in 4 days. That doesn’t occur — particularly that rapidly — in conventional rankings.
However beneath AEO logic, it made excellent sense. The legacy web page had stopped being maintained, and its construction was constructed for crawlers, not for extraction.
Once I went again by means of each check I’d run that 12 months, I observed engines have been frequently skipping high-authority domains. As a substitute, they cited content material that was just lately up to date, cleanly structured, referenced persistently throughout a number of sources, and straightforward to raise into a solution.
Freshness, construction, authority. The identical three alerts, each time, throughout each mannequin.
Why We Want a New Framework within the First Place
Conventional search engine optimization was constructed round a easy premise: A person sorts a question, the search engine identifies probably the most related pages, and people pages compete for place on a outcomes web page. Pages are the vacation spot, and the entire job of search engine optimization is getting your vacation spot increased up the record than the subsequent particular person’s.
That mannequin assumed two issues that reply engines now not assume:
- The person desires an inventory of choices.
- The person will consider these choices themselves.
AI fashions don’t work that manner. They retrieve data from a number of sources, synthesize it, and hand the person a single, assured reply. The person will get a abstract, not an inventory. And inside that abstract, sources are talked about, not as a reward for rating properly however as proof that the reply could be trusted.
So the query the engine is asking has modified utterly. It’s now not “which web page ought to we present?” It’s “which sources assist us clarify this clearly and precisely?”
That feels like a small distinction whenever you learn it on a web page, however in apply, it modifications the whole lot about what your content material has to do so as to be helpful to the system. Your content material is now not a vacation spot, however an enter.
And, when you internalize that shift, the FSA Framework stops feeling like a brand new set of ways. It turns into the one logical response to how reply engines truly work.
Featured Useful resource: How AEO is altering the search panorama.
The FSA Framework Breakdown
Freshness
In AEO, freshness is a weight — one which influences how confidently a mannequin reuses your content material, how typically it will get reconsidered when new prompts are available in, and whether or not it stays eligible to seem in assembled solutions in any respect. Stale content material will get dropped from the candidate pool solely.
The best way I give it some thought is that this: Freshness is recency, relevance, and reinforcement.
- Recency is the time-based piece. When was this final touched?
- Relevance is contextual. Does this nonetheless match how the subject is definitely mentioned right now with the language individuals are truly utilizing?
- Reinforcement is behavioral. Has this supply continued to indicate up, get cited, and maintain its place over time?
All three feed the identical sign, and a web page can fail on any considered one of them and lose floor.
What Freshness Actually Means
Reply engines don’t want a “final up to date” badge to find out whether or not content material is present. As a substitute, they discover when the language doesn’t match how a subject is being mentioned now, whenever you reference a instrument that doesn’t exist anymore, or when the encompassing subject house has advanced previous what your web page is describing.
In fast-moving verticals — SaaS, AI, fintech — content material has roughly a 90-day shelf life earlier than it begins dropping relevance alerts. For extra evergreen matters, you might have nearer to 6 months. After that, you threat falling out of the reply pool solely.
The sensible takeaway is easy:
- Don’t simply replace the date.
- Add a present instance.
- Pull in a latest stat.
- Reference one thing that’s truly modified within the house.
The amount of updates issues manner lower than their consistency and their substance. One actual replace each quarter beats 5 beauty modifications a month.
Freshness will get your content material reconsidered, however getting reconsidered isn’t sufficient by itself. The mannequin nonetheless has to have the ability to use what it finds.
Construction
Construction for AI is totally different from construction for crawlers, and the 2 don’t all the time align.
AI fashions don’t learn your web page the best way people do. They parse it and scan for clear hierarchies, self-contained explanations, and clearly labeled sections they’ll raise into a solution with no need the remainder of the web page to make sense.
Content material that performs properly in AI solutions shares quite a lot of the identical structural traits:
- Clear H2s and H3s.
- Brief paragraphs that resolve one thought at a time.
- Express definitions close to the highest of a piece, earlier than the reason unfolds.
- Labeled steps.
- FAQ sections.
- Callouts.
In case your finest thought is buried three paragraphs into a piece that requires the earlier part to observe, the mannequin goes to skip it. Not as a result of it’s a nasty thought, however as a result of it may’t be extracted cleanly.
Why Structuring for Reply Engines is Completely different From Conventional search engine optimization
In case your content material forces the mannequin to do interpretive work, the mannequin will discover one thing structured in a manner that’s simpler to interrupt aside.
The error I see most frequently is groups optimizing construction for crawlers — meta tags, clear header hierarchy, inner hyperlinks — and assuming that’s the identical job. It’s not. Crawler construction focuses on navigability, whereas AI construction prioritizes extractability.
The fitting query to ask of any web page is: Can ChatGPT raise a clear, correct reply out of this with no need the remainder of the web page?
If the reply isn’t any, you might have a construction drawback, irrespective of how properly your headings are nested.
Authority
In search engine optimization, authority meant area authority. It took years to construct and was nearly unattainable to displace as soon as a model had it. Whole company enterprise fashions have been constructed round hyperlink acquisition.
In AEO, authority is now entity authority. The query isn’t “how sturdy is that this area?” It’s “is that this model the one which persistently explains this particular subject, throughout each channel I can discover them on?”
Entity authority will get constructed one point out at a time, in a manner that has nearly nothing to do with backlinks. Each time your model seems someplace a mannequin can study from — a podcast, a Reddit thread, a visitor publish, a quote in a third-party article, a LinkedIn publish, your personal web site — it provides to what the mannequin is aware of about you.
One point out is an information level. However repeated mentions in comparable contexts throughout a number of channels assist construct a sample and create mannequin confidence. Confidence is what will get you cited.
Why Smaller Manufacturers Have Sturdy Entity Authority
Inside AI solutions, smaller manufacturers are out of the blue successful fights they don’t have any enterprise successful on paper. Digging deeper, the explanation why is apparent.
Smaller manufacturers typically create content material just for their core viewers and depend on social media or influencer advertising and marketing to construct model authority throughout surfaces, not simply their very own web site. When a mannequin encounters these manufacturers repeatedly, it positive aspects confidence in reusing the reason.
The large writer, in contrast, has 100 contributors writing about the whole lot. None of them is constructing a recognizable entity round a particular, user-focused subject. Distribution is commonly nonexistent as a result of conventional search engine optimization knowledge says that area authority is sufficient. When this occurs, the mannequin has nothing to anchor to.
Authority work is now nearer to fame administration throughout channels than hyperlink constructing. None of this appears like an search engine optimization marketing campaign, but it surely’s precisely the way you turn out to be the model the mannequin acknowledges.
Methods to Apply the FSA Framework
So if that is how reply engines truly work beneath the hood, the subsequent query is: What ought to groups be doing otherwise to place the FSA Framework to work?
Right here’s the best way I body it for shoppers. search engine optimization will get you into the room. AEO will get you chosen when you’re there. Right here’s the best way to apply the FSA framework in apply.
1. Begin with an audit — and discover your cash prompts
Earlier than you contact a single web page, you’ll want to audit your visibility to know the place you truly stand inside AI solutions. Which means operating actual prompts in ChatGPT, Perplexity, and Gemini for the matters tied to your pipeline — not the matters tied to your key phrase record.
These are your cash prompts. Take into consideration the questions your consumers are literally typing after they’re evaluating an answer, evaluating choices, or making an attempt to determine if you happen to’re the best match. They often sound like:
- “Finest AEO instrument for [specific use case]”
- “[Your brand] vs. [competitor] for [buyer context]”
- “How do I [solve the problem your product solves] as a [your ICP]”
- “What ought to I search for in a AEO instrument if [specific constraint]”
Run your cash prompts throughout a number of engines and pay shut consideration as to whether your model exhibits up in any respect, who’s displaying up as an alternative, and what the AI-generated reply truly says about your house. That single train will let you know extra about your actual AI visibility than any key phrase report.
Professional Tip: You may measure mentions with HubSpot AEO — observe prompts throughout ChatGPT, Perplexity, and Gemini, and see precisely the place your model stands.
When you’ve executed the preliminary scan, audit your prime 5 pages by means of the FSA lens with an trustworthy eye towards the place every pillar is or isn’t holding up:
- Is the content material present and reflecting how the subject is being mentioned right now, or is it quietly getting older out of relevance?
- Is it structured in a manner {that a} language mannequin may raise a clear reply out of the primary few hundred phrases?
- Is your model persistently represented throughout the channels the place consumers in your house are literally paying consideration? Or are you primarily invisible all over the place besides your personal area?
Analysis earlier than ways, each single time.
2. Change quantity targets with refresh targets
Sustaining and updating current content material on a constant cadence does extra for AI visibility than publishing net-new content material each week. In case your editorial calendar is constructed round what number of posts you ship, rebuild it round what number of of your top-performing pages get meaningfully refreshed every month.
3. Construction for extraction, not simply indexing
Audit your prime pages with one query in thoughts: Can a mannequin raise a clear, full reply out of the primary few hundred phrases?
If not, restructure with:
- Definitions up prime.
- Labeled sections.
- FAQ blocks.
- Comparability language for prompts the place consumers consider you towards options.
4. Construct entity authority throughout channels
Your web site alone isn’t doing all of the work anymore. Reply engines study from content material diversification, that means:
- Podcast appearances.
- LinkedIn firm and worker content material.
- Reddit feedback and threads.
- Visitor articles.
- Professional quotes.
- Group participation.
The manufacturers that construct a constant presence throughout a number of surfaces are those fashions begin to belief.
5. Measure AI Share of Voice, not simply rankings
AI Share of Voice tracks how typically your model seems inside AI-generated solutions in comparison with competing sources. It’s a zero-sum metric — when one model positive aspects share, one other model loses it.
HubSpot’s AEO options now allow you to see how your model is displaying up throughout reply engines and the place opponents are being cited as an alternative — which is genuinely helpful as a place to begin, since most groups don’t know the place their gaps are till they’ll see the info.
6. Choose one pillar to repair first
As soon as you already know the place you stand, choose one pillar to repair first moderately than making an attempt to handle all three without delay:
- In case your content material is stale, begin with freshness. That’s the quickest sign to maneuver.
- In case your content material is complete however dense, restructure for extractability.
- In case your model is invisible regardless of having genuinely good content material, the issue is sort of definitely entity authority, and the repair lives outdoors your web site.
Most AI visibility issues fall cleanly into a kind of three buckets. Loads of what appears like a visibility drawback is definitely an authority drawback in disguise.
Professional tip: Pair the FSA Framework with these AEO finest practices for a extra complete method.
What This Means for Your Content material Technique
The FSA Framework is a diagnostic lens for determining why visibility is or isn’t occurring to your model inside AI solutions. You may cease guessing and begin engaged on the best factor in the best order.
The precise alerts reply engines weigh will change because the fashions evolve. The ways constructed on prime of the framework will have to be adjusted because the surfaces shift. However the underlying logic — favor freshness, reward readability, belief consistency — has held regular throughout each mannequin I’ve examined, and I anticipate it to proceed to carry because the engines evolve.
The manufacturers that win inside AI solutions over the subsequent few years aren’t going to be those chasing each new tactic. They’re going to be those who perceive how AEO truly works, diagnose their visibility gaps actually, and repair the best pillar first.
Construct on these ideas, and the FSA Framework adapts because the floor modifications.
