What a Ghost result means
If your brand is an AI ghost, it’s critical that your team learns how to get cited in AI search results.
Let’s say you ran the test. You asked ChatGPT, Perplexity, or Gemini who the top companies in your category are, and your company did not appear.
Perhaps you even tried the problem-aware query (“we are an enterprise looking for a DevOps partner”) and still nothing. You typed your own company name and got back either a hallucination, or a thin paragraph that reads like it was assembled from two sentences on your about page.
This is the ghost result. Of the five AI visibility failure patterns, it is the most urgent to fix, but because a ghost has no foundation to build on. Every other failure pattern at least means you exist in the model’s understanding of your market. A ghost means you do not.
The cause is almost always the same: there is not enough authoritative, indexable content about your company in the places AI models draw from. The fix is systematic. It can’t be quick, but it is well within the reach of any B2B tech marketing team that is willing to prioritize it.
The ghost result is an urgent problem
Let’s say you ran the test. You asked ChatGPT, Perplexity, or Gemini who the top companies in your category are, and your company did not appear.
Perhaps you even tried the problem-aware query (“we are an enterprise looking for a DevOps partner”) and still nothing. You typed your own company name and got back either a hallucination, or a thin paragraph that reads like it was assembled from two sentences on your about page.
This is the ghost result. Of the five AI visibility failure patterns, it is the most urgent to fix, but because a ghost has no foundation to build on. Every other failure pattern at least means you exist in the model’s understanding of your market. A ghost means you do not.
The cause is almost always the same: there is not enough authoritative, indexable content about your company in the places AI models draw from. The fix is systematic. It can’t be quick, but it is well within the reach of any B2B tech marketing team that is willing to prioritize it.
Step 1: Claim your category in plain language
The first thing to check is whether your own website describes what you do in the language your buyers use. This sounds elementary, but we have found that it is the problem in a surprising number of cases.
Founders and marketers at B2B tech companies frequently resist category language for a few reasons. They may think the category is too crowded, or they have coined proprietary terminology they prefer. However understandable this may be, it can work against AI visibility.
AI models need clear, consistent category signals to place your company accurately. If your homepage describes you as “a platform that transforms how organisations think about operational intelligence” but never says “business intelligence software” or “data analytics platform,” you are invisible to any buyer who searches by category (which is most buyers in the early research phase).
The fix is to audit your homepage, your about page, and your primary product or service pages. Each one should use the two or three phrases your buyers actually type when they are looking for what you do.
Step 2: Build third-party citation (this is the real lever)
Your own website carries limited weight with AI models, particularly pure LLMs trained on a fixed corpus.
These models get a much stronger signal when other sources reference your company in a relevant context. This is the highest-leverage activity for a “ghost”, and it is the one most B2B tech companies underinvest in.
The sources that matter most, in rough order of impact:
- Press coverage that names your category and ICP explicitly
- Guest articles and bylines in industry publications
- Inclusion in roundup posts and “top X tools for Y” listicles
- Integration partner pages on well-known platforms that describe what you do
- Analyst and research mentions
- Customer-published case studies that appear on third-party domains.
Five to ten credible external references can shift a ghost result to a basic presence.
Step 3: Fill out your structured profiles properly
G2, Capterra, Crunchbase, and LinkedIn company pages appear frequently in AI-generated responses. If your profiles on these platforms are thin, incomplete, or out of date, they are actively working against you.
Each profile should describe, in plain and specific language:
- Your category your brand operates in
- The ICP you’re targeting
- A primary use case in plain, descriptive language (not marketing copy)
This is a manageable chunk of work that can produce a visible result within weeks for search-augmented models. It is one of the fastest wins available to a ghost.
Step 4: Publish content that answers the questions buyers ask AI
Long-form content that addresses specific buyer problems gets indexed and cited. The format that works best for AI visibility is substantive answers to real questions. Keyword-optimized landing pages aren’t enough here. What you want are articles that a buyer would find genuinely useful if they were researching your problem space.
The practical test: would a buyer save this article, share it with a colleague, or reference it in a vendor evaluation? If yes, it is the kind of content AI models draw from. If it is primarily written to rank for a keyword rather than to inform a reader, it will contribute less.
A focused publishing programme of one or two well-researched articles per month, consistently targeting the problems your ICP faces, will build a content base that AI models can index and synthesise within a quarter. Consistency matters more than volume.
Step 5: Pursue earned media with intent
Podcast appearances, conference speaking slots, analyst briefings, and interview-based features in trade publications all generate content that exists outside your own domain and references you in context. AI models treat these as high-quality signals precisely because they represent third-party validation rather than self-description.
The key is to approach earned media with the same specificity you would apply to your content programme. An appearance on a well-known podcast in your vertical, where you spend thirty minutes discussing a specific problem your buyers face, will produce more AI visibility signal than a generic press release about a funding round.
Be specific about the problems, the use cases, and the buyers you serve. That specificity is what AI models extract and use.
| How quickly will this work? A real example. Oktopost, a B2B social media management platform, moved early on AEO and GEO before best practices had solidified. Working with Inspired Marketing, they restructured existing content for AI extractability, built depth around their core subject matter, and tracked results directly from AI platforms rather than relying on traditional SEO metrics alone. Within 11 months: ChatGPT traffic grew by 90%Claude by 80%Gemini by 75% The traffic was high-intent: users arriving from AI engines showed strong engagement, with leads and demo requests attributable to AI-driven search. The first signs of movement came well before the 11-month mark. Search-augmented models like Perplexity can reflect new content within weeks for high-authority sources. Pure LLMs update on longer training cycles. Prioritize the search-augmented result first, and run the audit again at 30, 60, and 90 days. The first sign of progress is usually moving from invisible to generic. That is a good sign. It means the foundation is working. |
The order of operations: how to get cited in AI search results that are currently ghosting you
If you are starting from scratch, the sequence matters.
- Category language on your own site first: This is the foundation everything else builds on
- Structured profiles second: Quick wins that can produce visible results fast
- Third-party citation third: This takes longer to build but has the highest long-term impact
- Content programme and earned media run in parallel from there as the sustained investment that compounds over time
Do not wait until everything is perfect before running the test again. Check your results at 30, 60, and 90 days. The movement from ghost to commodity to a well-positioned presence is incremental, and seeing early progress will help you prioritise where to invest next.
The AI prompt ghost is fixable. All it takes is the right strategy, and the commitment to see it through
The companies that remain ghosts are almost always the ones that treat AI visibility as a one-off project rather than a sustained programme.
Oktopost’s results did not come from a single campaign. They came from a deliberate, sustained programme that built on existing content foundations and extended them into the formats and signals AI systems could reliably interpret. That is the model.
If you have run the audit and identified a Ghost result, the most useful thing you can do next is map your current content assets against the five activities above and identify the gap. Where are you already investing? Where are you absent? That gap is your roadmap.
If you would like a second opinion on where to start, that is a conversation we are happy to have.
