Wednesday, January 21

🌟 Today’s Highlights:

• Google Shopping’s API migration deadlines are approaching

• Your finance-related queries might not pick up AI Overviews

• Start 2026 right with a free audit of your martech tools stack

• 📊 Stat of the Day: Organic search traffic is down just 2.5% year over year. (Source: Graphite)

• 💡 Today’s Insight: Why LLM-only pages aren’t the answer to AI search

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⚡️ Today’s Headlines ⚡️

🌅 Google Shopping’s API migration deadlines are approaching. Google is sunsetting older API versions and pushing all merchants toward the Merchant API as the single source of truth for Shopping ads by February 28.

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🫥 New data shows AI Overviews disappear on certain finance queries. According to new research from BrightEdge, finance queries with an educational component (such as “what is” queries) trigger a high level of AI Overviews.

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🇪🇺 One of the first alternative app stores in the EU is shutting down. The store, Setapp Mobile from Ukranian-based developer MacPaw, first launched in September 2024. Now, all applications will be removed by the end of the sunset date, February 16.

💡 Today’s Insight 💡

Why LLM-only pages aren’t the answer to AI search

🗞 TL;DR - A new content strategy has been gaining steam within the search world: LLM-specific pages, aka pages no human will ever see, intended just for AI engines. Search Engine Land explored the thinking behind this strategy and why you maybe shouldn’t jump into it just yet.

💡 Insight - So, what’s the thinking behind this rise of ‘LLM-only’ web pages? Well, it comes in different forms – either llms.txt markdown files, markdown page copies, JSON metadata files, or in some cases, entirely separate versions of their content under /ai/ or /llm/.

In theory, it’s a good idea, but do these LLM-optimized pages actually get cited? In both individual and large scale analyses, no, not really. The files often didn’t help citations, it just added noise.

Across nearly 18,000 citations, llms.txt represented 0.03% of citations, markdown pages represented 0% of citations, /ai pages were 0.15-16% of citations (the higher-performing site put significantly more info on their /ai pages than anywhere else on the site), and JSON metadata represented 5% of citations.

In the large scale analysis of 300k domains, removing llms.txt from the model actually improved its accuracy.

The conclusion: LLM-optimized pages get cited when they contain unique, useful information that doesn’t exist anywhere else on your site. The format doesn’t matter. To add to it, no major AI company has confirmed using llms.txt files in their crawling or citation process.

Instead of wasting time and resources on these niche pages, focus on what actually works. Build clean HTML that both humans and AI can parse easily, because the best page for AI citation is the same page that works for users: well-structured, clearly written, and technically sound.

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