Tuesday, October 6, 2026
9 stories · 4 topics · 8 outlets
Answer Engines
6How to plan 2027 when traffic is down and AI won't attribute
This Growth Memo column argues that setting a traffic target and working back to revenue no longer fits most brands, because more of the buying work happens where no click, cookie or referral can see it. Author Kevin Indig recommends funding fixed SEO capabilities and splitting them by scenario instead of last year's traffic, with digital PR taking 40% of capacity in his example. Marketers should plan 2027 around signals that happen before a visit or without one, rather than around traffic targets alone.
Studies: AI Overviews are making strong inroads in France
Journal du Net reports on studies of the launch of AI Overviews in France, saying informational and long queries are among the most affected, along with certain sectors. The excerpt does not name the studies or give figures. Marketers should expect informational pages to lose clicks in French search and should track AI Overview exposure by query type and sector.
Google’s Mueller Says AI Crawlers Access Sitemaps & RSS In His Logs
Google's John Mueller says AI training crawlers rarely offer a way to submit a sitemap, and that his own logs show such crawlers fetching sitemaps and RSS feeds. He suggests publishing a sitemap under a default file name or running an RSS feed so those crawlers can find a site's content. Marketers who want their pages available to AI systems should check that a default-named sitemap or an RSS feed is live and crawlable.
Identifying the Right KPIs in the Context of AI Search
iPullRank's Mike King writes that ranking and click-based KPIs no longer tell the whole story, because AI models answer questions directly and send people down paths that often bypass brand domains. He says attribution in AI search is uncertain, which makes any metric more a matter of precision than accuracy, and that the industry has no standard for AI search KPIs. Marketers should choose KPIs that reflect how AI answers shape a decision and treat single-number precision as unreliable.
What is llms.txt & should you use it?
Semrush published an explainer on llms.txt, a file meant to help large language models understand the content on a site, and on whether a site should publish one. The post weighs the arguments for and against. Marketers should treat llms.txt as an optional convention rather than a substitute for crawlable pages, and test whether it changes anything with the models that cite their category before investing time in it.