- Whether a text comes from AI cannot be reliably determined. But the impression “sounds like ChatGPT” says something about its effect: familiar, interchangeable and not very well thought out.
- Eight patterns make marketing copy interchangeable, from unfounded claims to missing details from first-hand experience.
- AI makes linguistically good mediocrity accessible to almost everyone. If you want to stand out for SEO and GEO, you have to work deeper: talk to customers, interview experts, analyze your own data.
You read a text and think after a few sentences: this sounds like ChatGPT.
Whether it actually comes from AI cannot be reliably determined from that. But the impression says something about its effect: the text sounds familiar, interchangeable and not very well thought out.
The grammar is correct. So is the structure. Still, you hardly know more afterward than before.
In marketing copy, I notice these eight patterns in particular:
1. Claims are amplified instead of justified
A service saves time. In addition, it increases productivity, improves customer satisfaction and enables sustainable growth.
That sounds like many benefits. In fact, several claims have been strung together.
Take invoice processing software. The text could explain:
“The software transfers invoice data into accounting. Employees no longer have to retype amounts and invoice numbers.”
Now the benefit can be understood. How relevant the time savings are depends on the invoice volume and the previous process.
2. Contrasting pairs are supposed to create meaning
“Not just efficient, but future-proof.”
“More than consulting: your key to success.”
“Not a service provider, but a strategic partner.”
Sentences like these sound like positioning. They say little about what a company actually does.
A consultancy could explain instead:
“We discuss the results with your management, prioritize the next steps and support the responsible teams during implementation.”
This creates a picture of the collaboration. You can judge whether this approach fits your needs.
3. Problems are dramatized until the solution seems to be the only option
An outdated website suddenly endangers the entire competitiveness. Manual processes inevitably lead to loss of control. Without the solution on offer, you risk falling behind the market.
Yet the interesting question would be: when does a problem actually arise?
A small website can serve its purpose if it answers the most important questions and enables inquiries. It becomes critical, for example, when prospects don't understand the services, can hardly read information on their smartphone or a form doesn't work.
These are concrete starting points. They help more than a blanket warning of digital decline.
4. The language is abstract, the content remains thin
“We create sustainable added value along the entire value chain.”
What work is behind that?
Is it about reconciling inventory? Speeding up approvals? Planning delivery dates more reliably?
A concrete sentence could be:
“Purchasing and production work with the same inventory data. As a result, both teams see which materials are missing and which orders are already in progress.”
After this sentence, you can picture something. After the added value along the value chain, not so much.
5. Strategic terms feign precision
Scaling. Transformation. Standardization. Strategic importance.
These terms have a technical meaning. In texts, however, they are often used without explaining it.
When a company talks about scaling, you want to know: what is supposed to grow? The number of customers, orders or locations? Which processes have to change for that? Where are the current limits?
With standardization, you're interested in: what is being unified and which exceptions remain necessary?
Without such answers, the statements sound more precise than they actually are.
6. Argument and sentence structure always run the same way
First comes the challenge. Then the solution on offer. Finally, a general benefit.
Paragraph after paragraph.
Trade-offs, exceptions and limits are missing. Yet that is exactly where expertise shows.
For a heat pump, heat demand and the required flow temperature are part of the advice. For a marketing campaign, it must be clarified whether the offer is convincing and whether inquiries can be handled. For new software, data quality and responsibilities play a role.
A helpful text explains such prerequisites. It shows that someone knows more than the sales arguments.
7. Generic benefit descriptions replace verifiable changes
“More efficiency.”
“Better collaboration.”
“Higher customer satisfaction.”
What does that mean in concrete terms?
For a property management company, less effort could mean that repair reports go directly to the responsible team. In an online shop, better advice could mean that customers can see before ordering which accessories are compatible.
This doesn't always require a big metric. First, it requires an understandable description of what changes.
8. The details that can only come from first-hand experience are missing
A case study reports faster implementation, satisfied employees and improved service.
All expected benefits. But what was special about this project?
A hypothetical example: during a software rollout, it turns out that the biggest obstacle is an approval that gets stuck with the same person every week. Only a substitution rule makes the new process workable.
An observation like this tells you something about the project. It shows that someone looked closely and understood why a change works.
Of course, such details must not be made up. They have to come from conversations, documentation and actual experience.
And that is exactly why, in my view, good content work for SEO and GEO is becoming more demanding
In the past, competitors often had thin, poorly structured or incomplete content. Anyone who researched carefully, wrote clearly and answered the important questions could already stand out significantly.
Today, AI delivers neatly worded, detailed and clearly structured texts at the push of a button. It makes linguistically very good mediocrity accessible to almost everyone.
This raises the baseline quality we compete with. A long guide with suitable subheadings and the usual answers is less and less often a convincing difference.
If you want to offer more than that, you have to work deeper:
Talk to customers. Interview experts. Analyze your own data. Compare products and processes. Document specific cases. Resolve contradictions and explain limits.
A general buying guide is quickly created. Finding out which questions customers should actually ask before making a wrong decision takes experience and research.
AI shortens the time to the first draft. The effort to create a clear information advantage can still increase.
For SEO and GEO, this means: we must be able to justify more precisely why our page in particular deserves a visit or a source citation. That is no guarantee of visibility. But an interchangeable text gives little reason for it.
The decisive part of the work therefore often begins where the AI draft ends
What information is missing? Which statement holds up to scrutiny? What do our experts know that isn't yet in the general guide?
You don't have to recognize who wrote a text to notice that your questions remain unanswered.
That is exactly what we should measure our content against.
