33 to 90, 68 to 82: three AEO case studies and their starting Rank

Every engagement begins with a reading. The starting Rank is the first one.

Webflow's AEO program produced an overall AI traffic increase of 129% across its blog content, yet a lift reported without its starting point cannot tell another company what to do first.

According to Graphite's case study with Webflow, share of voice also rose for 70% of the questions the team targeted. I admire the work. Still, case studies in this trade are written as the old chroniclers wrote of victories, with the battle described and the map left out. A construction business reported a 723% increase in AI visibility across ChatGPT, Claude, Perplexity and Google's AI Overviews, and I have no reason to doubt it. But a percentage is a ratio, and a ratio without its base is a portrait without a face.

The base matters because the engines read what is already there. When Soft Surfaces was weighed against its rivals, ChatGPT drew on accreditation badges already on the company's website, CHAS and Constructionline among them, badges that had never been placed there for AEO. Part of that verdict was settled before anyone began.

An AEO Rank is a diagnostic measure of how ready a site is to be read, extracted and cited by AI answer engines. In what follows I set three anonymized engagements side by side, each with its starting Rank. In every case, the starting number decided the lever.

Why does a site that starts at 33 need engineering before articles?

A starting AEO Rank of 33 is rarely a verdict on the prose. It marks a locked door, which is work for an engineer like ours, with 20 years of building enterprise systems.

An analysis of 3 sources shows that practitioners place access and structure ahead of eloquence. The electro-mechanical manufacturer in the first engagement began at an AEO Rank of 33 and finished at 90 over 4 phases, and I read that starting number through what I call the four-door check, four questions asked in order before a single article is commissioned:

1. robots.txt: does the file admit AI crawlers, or does it still turn them away as it had always done?
2. llms.txt: is there a plain map of the site for language models, or nothing at all?
3. Bing index: are the important pages present in Bing's index, or are there gaps no one has looked for?
4. Structured data: does JSON-LD, including FAQ schema, tell an engine what each page is, so that an answer can be lifted without guessing?

According to a commenter in an r/DigitalMarketing thread from April 2026, surprisingly many sites cannot be reached by AI crawlers at all, and the three most common blind spots are robots.txt issues, a missing llms.txt and Bing indexing gaps. The same commenter separates the disciplines cleanly: SEO optimizes for ranking signals, while AEO optimizes for extraction, which is where FAQ schema and self-contained answer units enter. I would expect a site in the 30s to have failed the first test before it is ever asked the second.

There is something of an old empire about such a site. Its offices still stand, its titles are still printed on the doors, and yet no messenger arrives. A common misconception is that a low Rank means the writing has failed. According to a thread on r/aeo from April 2026, a lot of brands are "invisible to AI engines for reasons that have nothing to do with content," and "most brands don't know what's broken until they actually look." In that same thread a software company described moving its product documentation off legacy knowledge base tools, with its blogs to follow off WordPress, because it wanted "fine grained control for json-ld, markdown, etc." That is an engineering decision made in the service of content, and it is the kind of decision a site at 33 is still waiting for.

Monitoring alone will not find the lock. Practitioners who have paid for AI visibility trackers complain that most of them follow outputs that shift daily, with no reliable connection to what actually drives them, and a tracker will record the silence of a blocked site faithfully without once naming the cause. The phase-by-phase ledger of the manufacturer's climb is not part of this record, and I will not reconstruct it from memory. What such a ledger would show, once it is set down, is the order in which the doors were opened and what each opening was worth.

What this means is plain. On a site that crawlers cannot reach, new articles are written into silence. In practice, I would give the first phase of any low-Rank engagement to an engineer, and the writers would follow once the doors stood open. The takeaway: open the doors before you furnish the rooms.

Why does a site that starts at 68 gain fewer points, and are they worth having?

A site that starts at 68 has usually opened its doors already, so its ceiling is citation share: how often other sources name it, not how its own pages are built.

The customer-service company in the second engagement moved from 68 to 82 with a WordPress plugin alone. It is a gentle irony, after so much talk of leaving WordPress for finer control, that the old platform was enough here, and whatever a plugin does, it can only work on pages that already exist. The care-services site in the third engagement arrived at the same 82 with 5 articles. Two sites are not a law, and I would not pretend otherwise. Yet the coincidence suggests to me that the low 80s may be where work on a site's own pages slowly begins to meet its limit.

Above that line the order of things changes. An answer engine does not hand the answer to the first link, as Google once did with its blue links. It summarizes many citations, and the brand named first is usually the one mentioned most across them. Practitioners who study these answers describe the same pattern from another side: a single prompt is broken into 10, 15 or even 20 different queries, and a brand that appears across all of those sub-questions has a good chance of surfacing in the final answer. One recent construction-firm campaign was built around that insight, mapping which pages belonged on the client's own site and which needed to live on external websites.

So what remains for a site in the low 80s is, in my view, less a flaw in the house than the silence of the neighbors. Citation share is the proportion of the sources an engine reads that name your brand (the AEO Knowledge Base covers the vocabulary of AEO more broadly). No plugin can raise it, because the plugin lives on your server and the neighbors do not.

Are the smaller gains worth paying for? According to Graphite's case study with Webflow, 8% of Webflow's total signups came from AI chatbots, and the signup conversion rate for those visitors was 24%, "six times that of our non-brand SEO." A 2025 episode of The Digital Insurance Agent podcast cited studies showing that AI traffic converted five to six times better, even as traffic counts from Google fell, and noted that Google's AI draws on real-time reviews and local business data. Neither figure belongs to these three engagements. The citation outcomes that accompanied the move from 68 to 82 are not part of this record either; what such a record would show, once kept, is whether the new points arrived as mentions in other people's pages or only as tidier pages of one's own. Keeping that record over time is what Visibility Tracking is for.

In practice, the points above 80 are earned off the site. The takeaway is that a smaller gain near the top may be worth more than its size suggests. What this means for a site at 68 is a change of lever, not a change of effort: fewer pages written by you, more pages written about you.

How should a startup read its starting Rank to choose its first 90 days of work?

Low starting Rank: fix access and structure. High starting Rank: earn mentions. Either way, our promise stands: named in AI answers in 90 days, or we work free until you are.

The engagements above resolve into what I call the two-ceiling rule. Every site sits under one of two ceilings: an access ceiling, made of crawler rules, missing files and absent markup, or a citation ceiling, made of how rarely other sources mention the brand. The starting Rank tells you which ceiling is lower, and the lower one is where the first 90 days belong.

Alex and I bring a combined 40+ years of SEO and content infrastructure experience to AEO, and the two halves of that phrase are the two halves of this rule. Infrastructure answers the access ceiling. Content, and the conversation it provokes elsewhere, answers the citation ceiling. In my view, a startup rarely needs both at once in its first quarter, and it can seldom afford to buy both at once.

The contrast with the old order is worth keeping. In those days a young company waited for authority as a junior officer waits for promotion, slowly and by seniority. According to a December 2025 video from Julia McCoy, ranking in AI answer engines takes about 13 referring domains, compared with 41 for traditional page-one rankings, which suggests a young company need not wait in the old way. The same video reported that clients who began six to nine months earlier were then featured in AI Overviews for 40 to 100 plus keywords. That is a longer horizon than a single quarter, and I would set expectations accordingly: the first 90 days should prove that the right ceiling is moving, not that the whole house is finished.

Measure the outcome in something a founder can count. One of our proof points reads, simply, from a quiet site to 10 booked calls in 3 weeks, and I would rather a board heard that sentence than a Rank alone. In practice, your first 90 days are decided before anyone writes a word. The takeaway is simple: find the lower ceiling and spend the quarter there. What this means for a portfolio company is a scoped first quarter, not an open-ended retainer.

What will matter most in AEO over the next 12 to 24 months?

The starting Rank will matter most: buyers will scope work by where a site begins, paying for access fixes at the bottom and for third-party mentions at the top.

I see three signals behind that forecast. None of them is loud yet. Each is already visible to anyone who reads the practitioners closely rather than the vendors.

According to Graphite's case study with Webflow, the company's AEO work stands on two pillars built from its existing SEO: earned visibility off-site, through third-party sites, publications, reviews and forums, and owned content on-site. I read that division as the same two ceilings described above, arranged by a company that could afford to work under both at once. Most startups cannot, which is why the order will matter more than the budget.

I hold this forecast loosely. If the engines began to hand most answers to a single top-cited source, as Google once did with its first blue link, the old ranking game would return, and the line between foundation and mentions would blur again.

What most buyers miss is that a falling traffic chart can hide a rising pipeline. Traffic from Google is falling as AI Overviews answer above the links, yet Google's AI now draws on real-time reviews and local business data, which compresses the steps between a prospect's first contact and the purchase decision. Fewer visits, shorter roads. The report that still counts only sessions will describe, with great fidelity, a world that has already passed.

Why does the starting Rank matter more than the final one?

The starting Rank chooses the lever before anyone chooses a vendor, and the same budget spent under the wrong ceiling buys very little that an answer engine will ever repeat.

A Rank is a diagnosis, not a scoreboard. The distance a site travels, as the manufacturer's did from 33 to 90, is set first by where it stands on the morning the work begins. According to Graphite's Kristen Vaughn, "Just like broader SEO, there could potentially be a ton of wasted work with AEO." In my view, most of that waste is labor done under the wrong ceiling.

The engines, meanwhile, read the record you already keep. In the Soft Surfaces case, ChatGPT noticed that a rival offering a 10-year guarantee had been trading for only four years, and it questioned how that guarantee could be warranted. Once an engine settles on a source it trusts, it tends to cite that source again, and the advantage compounds quietly, as interest once did in the old savings banks.

Over the coming year I expect buyers to ask for the starting Rank before they ask for the price. The first thing I would check is not the copy. It is the robots.txt file, still turning visitors away as it may have done for years.