Content strategy under ChatGPT - how to design content so AI will recommend you

In this article you will find specific rules for designing content that is readable by AI algorithms. You'll learn why classic keywords aren't enough today and how to revamp your offer descriptions, FAQ sections and landing pages so ChatGPT treats them as a reliable resource. You'll learn the 5 foundations of content strategy under language models, and you'll get ready-made checklists that will help you systemically implement changes and increase the chance that artificial intelligence will recommend just your brand.

Content strategy under ChatGPT: how to design descriptions, FAQs and landing pages so AI will recommend your offerings

ChatGPT and other language models (GPT- 4, Gemini, Claude) have become the first place many people look for answers, tool recommendations and vendors. If your content is "invisible" to AI, more and more demand will bypass your brand.

This article shows how to design offer descriptions, FAQs and landing pages so that language models can easily understand your value proposition and are more likely to recommend your offer. We will also show how the tool Semly i approach positioning in AI  helps to systemically implement such a strategy throughout the service structure.

How ChatGPT "sees" your site and recommends offers based on that

Where does AI get information about your brand

Language models learn from huge collections of text: public websites, Wikipedia-type services, documentation, books and forums. In training, they don't build a classic index of sites like Google, but an internal "map" of linguistic concepts and relationships.

In practice, the impact of your content on AI responses has two levels:

1. Historical level (pre-training) - some of the public content may have found its way into training collections. This is an uncontrolled process from the perspective of a single brand, so it is impossible to "force" the inclusion of a particular site.
2. Current level (retrieval / browsing) - Newer systems (e.g., ChatGPT with browsing, Perplexity, Gemini) can pull current content from the web in real time and summarize it in a response. Here you have a real impact with how you design content.

If someone asks: "Which SEO tool is worth choosing for scaling content under AI?", the model can:

• refer to your "embedded knowledge"

• reach for up-to-date content from the web and use it as material for answers

The more clearly and fully you describe who your offering is for, what problems it solves and in what scenarios, the easier it is for AI to "recognize" that your brand fits the question.

How the model reads and interprets the page

When ChatGPT or another system downloads your site, in simple terms, this happens:

1. HTML is converted to text with structure: headings, lists, tables
2. The model gets a snippet of the page (a fragment of text in the limitation of length - the number of tokens)
3. On this basis, it "extracts" the most important information and transforms it into a response

Research on AI-search and so-called LLM-SEO shows that the models perform particularly well:

• clear H1 - H3 headings

• FAQ in question-answer format

• bulleted lists and tables

• brief summaries

If your site is a long, undivided block of text, it is harder for the model to quickly find and use key information. Therefore, the content strategy "under ChatGPT" is largely a strategy of clear structure.

5 principles of content strategy under ChatGPT and generative AI

Think in the intentions of AI conversations, not just in keywords

Classic SEO starts with phrases like "SEO agency Warsaw." In the AI-first world, we tend to think of full questions:

How to choose an SEO agency for SaaS B2B?

• What are some good tools for planning SEO content under AI?

• Who can help me design a content strategy under ChatGPT?

Users formulate queries like natural questions to a consultant. This means your content should:

• answer these questions directly in headlines and FAQs,
• build full decision pathways: from "is this for me?" to "what to do next?".

Get more specific about who your offer is for

Models often generate responses like, "If you're [segment], you might consider [type of solution/brand] that...". For your brand to naturally appear here, the content must clearly communicate:

• industries and customer types (e.g., "SaaS B2B, e-commerce, marketing agencies"),

• company sizes (SMB, mid-market, enterprise),

• situations in which the solution works best.

Ensure completeness of information: who / what / how much / how / when

For AI, it's the specifics that count:

• scope of services/functions

• prices or at least price ranges

• implementation time

• technical requirements

• restrictions and exclusions

The more gaps in these areas, the less likely the model will consider your site a good source for a complete answer.

Design formats that AI likes to "read": FAQs, checklists, comparisons

Meta-analyses of AI-search studies indicate that the best performers are:

• FAQ,

• step-by-step (how-to) guides,

• options comparison,

• checklists.

These are formats that closely resemble the response structure that ChatGPT generates. If your content already has this shape, the model can practically "rewrite" it, adapting it to a specific question.

Write in human terms, but informative - less "empty" marketing

Models are trained on a mix of styles, but they strive for an expert and neutral tone in their responses. Excessive generic slogans ("innovative, end-to-end solutions") are simply noise to them.

Style is better:

• simple

• specific

• grounded in real problems and numbers

This is exactly the style of content that Semly helps implement - a tool that combines SEO, topic analysis and content generation so that it is both search engine friendly and generative AI.

How to design offer and product descriptions so ChatGPT "understands" them

Key elements of the offer description under AI

A well-designed bid description should answer the 7 questions directly:

1. What it is A short, concrete definition of a product/service.
2. Who is it for? Industry, company size, role of the decision maker.
3. What problem does it solve? Maximum specificity, with the language of the customer.
4. How it works In several steps or modules.
5. What are the effects/benefits? Preferably with numbers or examples.
6. How much does it cost (approximate)? Price ranges, plans, minimum thresholds.
7. What are the limitations / when is it not worth it?

If you explain these issues in a single description, the model has all the ingredients to "assemble" a neat recommendation in response to a user question.

Example: an excerpt from the "before" and "after" description

Before (typical, not very AI-friendly passage)

Problems:

• lack of specificity (what is the service?)

• no target group

• lack of effects

• zero data, zero usage scenarios

Po (AI-friendly version)

Semly is an SEO and content marketing platform for B2B, e-commerce companies and agencies that want to systemically plan and create content that is visible in search engines and generative AI.

We help marketing teams:

• plan topics and content structures for specific user intentions (Google + ChatGPT)
• generate draft articles, offer descriptions and FAQs in a consistent standard
• analyze results and develop thematic clusters across the site

Typical results at our clients include an increase in organic traffic and more queries from "best tools for..." queries, in which users ask AI for recommendations.

In the new version, the model easily identifies:

• solution category (SEO and content marketing platform)

• target group (B2B, e-commerce, agencies)

• issues and effects (content planning, visibility in AI, increase in inquiries)

Checklist of offer description under ChatGPT

Use this short list for every important bid page:

• You unambiguously named the product/service in the first paragraph.
• You indicated what industries / types of companies the offer is for.
• You have listed 2-4 of the customer's most important problems in their own language.
• You explained in 3-5 steps how the collaboration or operation of the tool.
• You gave examples of the effects (with numbers, if possible).
• You outlined price ranges or a clear pricing model.
• You described when you are not a good choice.
• At the end you added a short FAQ with the most common questions of the decision maker.

FAQs under ChatGPT - how to build a database of questions and answers

The best questions for FAQs are those that customers are already asking:

• on sales inches and demos

• in emails and live-chat

• inquiries

• in SEO tools (long tail phrases, "people also ask" questions)

In the context of AI, the key questions are:

• costs ("how much does it cost for...?"),

• matching ("is this solution good for...?")

• integrations and limitations ("does it work with X?", "can it be used with Y?")

• security and compliance (especially with tools with data)

How to write language model-friendly responses?

A good FAQ answer should:

• begin with a short, one-sentence answer

• only then develop the context and exceptions

• repeat naturally the name of the product / service + segment, if it helps in understanding.

Such an answer is useful for both humans and AI, which can paraphrase it in style:

FAQ structures that work well under AI

1. Topic FAQs - you group questions by area (pricing, implementation, security, features)
2. Stage FAQs - separate sections for: purchase consideration, implementation, daily use, scaling
3. FAQ problem-solution - you formulate the questions as problems: "What to do if...?", "How to solve...?"

Here, Semly can act as an "engine" for collecting FAQ topics (based on SEO data and insights from content) and generating first versions of the answers, which the team only refines.

"AI-first" landing pages - what needs to be on them

What's changing from classic SEO

Landing "AI-first" goes a step further and responds to how users talk to AI. Research on consumer behavior shows that generative AI often acts as an advisor: helping to set selection criteria, compare options and make decisions.

That's why it's a good idea to include sections on the landing page:

• "Who is this solution for?" - with specific company profiles.
• "When does this tool/service work best and when does it not?"
• "What does the step-by-step process look like?"
• "What results can you realistically achieve?" (with examples and figures).
• "The most common questions before making a decision" - mini-FAQ on the site.

Example of a landing page framework under ChatGPT

You can use this framework when designing a new LP (for example, under Semly or a specific service):

• Lead / TL;DR

A short summary that defines what problem you are solving, for whom and how - perfect to keep the user on the page in the first seconds.

• Section: Who it's for

Define 2-4 personae (e.g., Marketing Manager at a SaaS, e-commerce owner, Head of Content at an agency) and assign them typical challenges they face on a daily basis.

• Section: How Semly helps solve these problems

Prepare 3-5 blocks always in the format: problem → solution → effect.

• Section: How it works step by step

Describe the process in 3-6 steps: from deployment and configuration, to first campaigns, to scaling visibility.

• Section: effects and examples of use

Present mini-cases (industry, results) and customer quotes that build social proof.

• Section: FAQ

Prepare 6-10 questions that arise just before the decision (about the contract, test period, support or data security).

• Section: What's Next (CTA)

Define one main call to action to be taken by the user after reading - for example, "Request a demo," "Test for 14 days," or "Talk about content strategy under AI." An effective CTA should be clear and directly linked to the value that Semly delivers.

You can design and optimize content for each of these blocks in Semly, using SEO data and knowledge of the topics that are already driving traffic and inquiries.

How to measure the effects of content strategy under AI?

New types of customer inquiries

Pay attention to the phrases:

• "I came across you guys because ChatGPT recommended..."

• "AI suggested to consider..."

• "Does this tool work well with ChatGPT / generative AI?"

You can add one field to the form like "How do you know about us?" with the option "AI recommendation / ChatGPT / other AI tool".

Changes in SEO query profiles and organic traffic

Although forecasts indicate a possible decline of up to 50% in organic traffic by 2028 in favor of AI-search, it is still worth analyzing in the short to medium term:

• an increase in queries like "best tools for...", "alternatives to..."

• long tail question queries ("how to choose...", "what to choose...")

• traffic to guide, FAQ and comparison sites

Semly, as a content-focused SEO tool, can help:

• identify growing themes and questions
• create concepts for new content responding to these intentions
• monitor effects at the level of thematic clusters rather than individual keywords

Content comparison tests

You can run type tests:

• "Old" landing vs. "AI-first" landing (differences in conversion)

• offer description with full checklist vs. abbreviated description (time on page, inquiry rate)

It is also good practice to regularly "prompt" ChatGPT or other systems (as part of their usage policies) with questions like:

• "What are the tools for ... for [your segment]?"

• "How do you design a content strategy under AI for [your segment]?"

Mini-FAQ: the most common questions about content under ChatGPT

Is it possible to "rank" in ChatGPT as in Google?

There is no equivalent to items 1-10. Models generate responses that combine multiple sources. However, you can increase the chance that your brand will show up in recommendations by providing content that is complete, specific and well-matched to users' intentions, according to the principles of [AI positioning].

Isn't AI "stealing" content from my site?

Models summarize and paraphrase information from multiple sources. In practice, if you provide valuable content, you become more visible as an expert. On the other hand, it's worthwhile to make sure you have correct legal labels, privacy policies and, if necessary, robots.txt files.

Does it pay to invest in long articles when AI summarizes them anyway?

Yes, provided the article is well organized. AI needs a full, substantive source to build a good response. Thin" content is often overlooked. Your goal is to be the source from which models draw.

Can I write everything with ChatGPT and hope it will be enough?

Generative AI is great for drafting content, but you still need strategy, data and expert verification. Semly allows you to combine writing automation with quality control and alignment with SEO and user intent.

How often to update content for AI?

At least once every 6-12 months, it's worth reviewing key landing pages, offer descriptions and FAQs for changes in products, pricing and user behavior. Up-to-date dates, fresh data and new case studies are quality signals for both Google and AI systems.

Semly's role in content strategy under ChatGPT

Semly was created in response to the growing needs of marketing teams who want:

• plan content not only for classic SEO, but also for user behavior in generative AI
• produce more quality content without losing consistency
• build topic clusters and content structures that AI easily understands and uses

In practice, Semly can help you:

• map topics, questions and user intentions (Google + AI conversations)
• create templates for offer descriptions, FAQs and landing pages in line with "AI-first" principles
• generate the first versions of the content and iterate over the data
• maintain consistency of language and structure throughout the site, which is crucial for language models

Instead of treating each site as a separate project, you can approach your content strategy systemically - and Semly helps maintain that systemicity.

Summary

The era when SEO ended with optimization for Google's algorithm is irrevocably passing. ChatGPT, Claude and Gemini are becoming the "new home page" of the Internet - the place where your potential customers not only look for definitions, but ask for specific recommendations of suppliers and tools.

If your content is not readable to them, your brand will simply cease to exist in their responses. Remember, in the world of AI, you are not fighting for the 1-10 position, but to be part of a substantive response.

The key to success is to abandon empty marketing slogans in favor of specifics: clearly defined target groups, precise answers in FAQs and structures that AI can easily "digest."

By implementing GEO and AEO principles, you are not only preparing for the future of search, you are already building a huge advantage over competitors who are still optimizing content for standards from a decade ago.

An AI-first strategy is an investment in getting your business recommended by the most influential advisors of today - language models. Semly helps you translate this vision into action. From topic mapping, to generating drafts for specific intent, to maintaining the consistency that AI models require to build brand trust. The future of search is happening now - make sure your content is ready for it.

Sources

• Elastic - What is a large language model
• NNGroup - How AI Is Changing Search Behaviors
• E. Mogaji - How generative AI is (will) change consumer behavior
• S. Kim - Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation
• W. Chang - A comparative study on the effect of ChatGPT recommendation and AI recommender on consumer choice
• ResearchGate - Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation
• OpenAI - How People Use ChatGPT (economic research paper)
• MIT - Large language models use a surprisingly simple mechanism to retrieve stored knowledge
• TTMS - LLM-powered search vs traditional search 2025-2030 forecast
• StackOverflow Blog - From training to inference: The new role of web data in LLMs
• ImpactPlus - How to Get Your Business Found and Recommended on ChatGPT
• In AI We Trust - How to Optimize Your Content for ChatGPT & LLM Answer Engines
• Ryan Tronier - Content Formats That Work for AI and LLMs [2025 Playbook]
• Virayo - 10 Generative Engine Optimization Strategies (With Case Studies)
• LinkGraph - LLM Optimization: Make Your Content Visible in AI Answers
• Wildcat Digital - Creating LLM-Friendly Content Formats
• OrganicLabs - Optimizing for AI Search Engines: A Meta-Analysis of 19 Research Studies
• Brandon Leuangpaseuth - LLM Ranking Factors: AI Optimization Guide (2026 Update)
• OpenAI - Usage policies: https://openai.com/policies/usage-policies/

• OpenAI - Usage policies (revisions archive)

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