Listicles Dead, Reddit Dead? My Take on the DMEXCO Masterclass

In short: At DMEXCO 2026, Malte Landwehr of Peec AI gave a masterclass on visibility in AI search. According to his company's data, ChatGPT has cited far fewer listicles, comparison pages and Reddit threads since the switch to GPT-5.6. Pricing pages, documentation, PDFs and official sources are cited more often. My take: this is not a fad but the logical result of too much self-promotion in ranking lists. If you want to appear in AI answers today, you need verifiable facts on your own pages, consistent information across all of them and short, self-contained paragraphs. I advise against some of the tricks from the talk.

The full talk is available as a recording on YouTube. It is worth watching, partly because it is honest: a year ago Landwehr himself still recommended listicles as the most important measure, and now he says openly that they are no longer enough. The figures come from one vendor's measurement data. They are a snapshot, not laws of nature.

What changed, according to the talk

The core observations as presented on stage:

• More sources per answer: A ChatGPT chat now uses 24 sources on average instead of 12.
• Targeted searches on single websites: ChatGPT searches only one specific domain much more often, roughly in every fifth chat.
• Listicles are losing: Their share of sources fell from 20 to 8 percent. Search queries containing "best" were cut in half.
• Reddit is losing: Its share fell from about 1.5 to below 0.3 percent.
• Official content is winning: Search queries containing "official" rose sharply. Pricing pages, product pages, documentation, PDFs and .gov and .edu domains are cited more often.
• Self-praise gets ignored: If you put yourself in first place on your own best-of list, this observation suggests you mostly help the competitors ranked below you.

My take: AI systems look for evidence, not claims

The direction does not surprise me. Listicles were a shortcut. Thousands of vendors published rankings with themselves at the top. A system that wants to back up its answers can do little with pages like that. A pricing page or technical documentation, on the other hand, is a statement a company stands behind.

In practice this means the question is no longer which article covers the most keywords. The question is whether the important facts about your company are on your own pages in a way a language model can find, understand and verify.

What I recommend

1. A summary at the top of every important page

According to the talk, 44 percent of the content used comes from the first third of a page. Language models split pages into chunks of roughly 150 words. So write a summary of at most 150 words at the top, in clear declarative sentences, naming entities instead of writing "we" and "our product". This article starts exactly that way.

2. Keep facts consistent across all pages

When ChatGPT searches a single website, it often reads several pages. If your homepage, pricing page and an old blog post contradict each other, you lose control of the story. According to the data from the talk, pricing information comes from pages other than the pricing page in 23 percent of cases, for example from old blog posts or help pages of the same company. Check specifically where your website still shows old prices, old feature sets or old company names.

3. Take pricing and service pages seriously

According to the talk, pricing pages are one of the fastest-growing source types. That does not mean every page has to show prices. It means the page describing what you offer and for whom should be well structured, answer questions directly and back up its claims. Statements like "awarded by …" belong there together with their source.

4. Read the AI's own search terms

Language models send their own searches in the background, so-called fan-out queries. They often contain category terms that were not part of the original question at all. If you know these terms, you know which words your homepage should use to describe your offer. This only works if you ask many questions several times and analyze the patterns, not with a single sample.

5. Maintain your Open Graph tags

According to the talk, ChatGPT also stores the title and description from the Open Graph tags for each URL. These are the fields otherwise mainly used for link previews on social networks. Filling them in costs little, and outdated or empty tags are an avoidable gap.

6. LinkedIn posts, not only long articles

A side note with consequences for B2B companies: on LinkedIn, regular posts are now the most cited format according to the talk, no longer mainly the long Pulse articles. If you are active on LinkedIn, publish expert statements as short, fact-dense posts as well.

Where I disagree

Part of the talk describes levers that may work but do not belong in a serious strategy:

• Planting claims on Reddit: Landwehr shows that a single Reddit post changed the answers of AI systems within two days. That is an important finding because it shows how easily answers can be influenced. As a method to claim features that are not yet documented, it is risky. If the AI says something wrong about you, it falls back on you.
• Pricing pages about competitors: Pages that explain a competitor's prices are legally delicate. In Germany and the EU, comparative advertising is only allowed within narrow limits. What does make sense is watching whether others publish such pages about you.
• Promotional lines in email footers: The talk reports that positive mentions in a Gmail inbox can influence recommendations in Google's AI Mode. Putting promotional sentences into your customers' inboxes so an AI reads them strikes me as a short-lived trick that costs trust.
• Advertorials and affiliate instructions: According to the talk, both are still being cited. I would not rely on them. What happened to listicles will happen to paid mentions too.

My rule: if you would not show something to a human without an explanation, do not build it for an AI either.

Measure instead of believing

All figures from the talk are averages across many brands. Whether they apply to your industry can only be shown by your own measurement: the questions your customers ask, asked regularly in ChatGPT, Gemini, Perplexity and Google AI Overview, with the complete answers and the cited sources. That is exactly what GEO Tool does. How ChatGPT picks and shows its sources is covered in our article on ChatGPT search citations, and we discuss these topics in our German-language podcast GEO Talk.

Frequently asked questions

Do listicles still work in AI search?

They work less well. According to the data shown in the talk, their share of ChatGPT's sources fell from 20 to 8 percent. Rankings in which the author puts themselves in first place are skipped particularly often.

Which sources does ChatGPT cite more often in 2026?

According to the talk, mainly official company pages: pricing pages, product pages, documentation and PDFs, plus .gov and .edu domains. Reddit and comparison pages are losing weight.

How long should a paragraph be for AI search?

A statement should stand on its own within about 150 words at most. Language models split pages into chunks of that size and most often cite clear, verifiable statements.