Ahrefs vs SparkToro

714 Suppression Campaigns: Negative Results Trends Analyzed

Erase.com analyzed 714 online reputation suppression campaigns (Aug 2024 - May 2026) to identify what impacts success in pushing down negative search results. Key findings reveal that the starting position of the worst negative result is the strongest predictor of clearing Page 1; campaigns starting at position 4 or lower were 3.5x more likely to succeed. The number of negatives also mattered. Publishing volume was not a differentiator; instead, the placement of new assets within the top 10 was key. Most successful campaigns cleared Page 1 within 3-4 months. Court records were easiest to suppress, while Reddit threads and review sites were hardest. The rise of AI Overviews, which often cite URLs beyond Page 1, suggests that pushing negatives only to Page 2 may be insufficient.

• Erase.com analyzed 714 suppression campaigns from August 2024 to May 2026.
• Campaigns with the worst negative starting at position 4 or lower cleared Page 1 3.5x more often than those starting at position 1.
• The typical suppression campaign published 29 positive assets, but successful campaigns had a median of 6 new assets in the top 10 vs. 4 for unsuccessful ones.

Publishers Shift from Clicks to Valuable Sessions

Digital publishers face a decline in search referral traffic due to AI-generated answers in search engines. A Chartbeat analysis of over 2,500 publisher sites shows a global drop in Google search traffic of about one-third by November 2025, with a 38% decline in the US. An Ahrefs study of 300,000 keywords found that the top result's click-through rate is 34.5% lower for queries with AI Overviews. This shift makes volume-based monetization models unsustainable. Publishers are advised to focus on Revenue Per Session (RPS) rather than pageviews or individual clicks. This involves integrating editorial recommendations, native ads, and display formats into dynamic content feeds that are optimized for relevance and user experience, thereby increasing the value of each session despite fluctuating traffic.

• Chartbeat analysis of over 2,500 publisher sites shows global Google search traffic declined by one-third year-over-year through November 2025.
• Ahrefs analysis of 300,000 keywords shows a 34.5% lower click-through rate for top results on queries with AI Overviews.
• The article advocates for a shift from pageview-based metrics to 'Revenue Per Session' (RPS) as the key performance indicator.

Google's AI Spam Detector Judges Networks, Not Pages

Google has published a research paper describing the Scalable Cluster Termination System (S-CTS), a new spam detection approach that analyzes site networks and generation clusters rather than individual pages. The system uses Sentence-BERT embeddings and infrastructure signals to identify templated, AI-generated content produced at scale. This coincides with Google's June 2026 spam update, which has already led to organic traffic declines for websites flagged by Ahrefs as having 'Very high' AI content levels. Google's official policy still rewards quality content regardless of production method, targeting only scaled content abuse intended to manipulate rankings. The paper also details adaptive techniques like Low-Rank Adaptation (LoRA) and Automatic Prompt Optimization (APO) to quickly retune classifiers against new generative models. Marketers and publishers relying heavily on AI content may face tougher penalties as Google's enforcement becomes more sophisticated.

• Google published a research paper on the Scalable Cluster Termination System (S-CTS) for detecting AI-generated spam clusters.
• S-CTS uses Sentence-BERT text embeddings and infrastructure signals to group related accounts or domains into generation clusters.
• Google's June 2026 spam update has finished rolling out, and sites with high AI content levels are experiencing organic traffic declines.

Rapid AI changes mean GEO is a weekly job now

This article argues that the rise of AI-generated search responses has made Generative Engine Optimization (GEO) a weekly responsibility for PR, SEO, and content teams. Citing SparkToro data showing 68% of Google searches end without clicks and Pew Research finding only 8% of users click traditional results when AI summaries appear, the author advocates for a unified, weekly workflow. The described agency uses internal tools to surface buyer prompts, coordinates PR, SEO, and content efforts, and monitors live AI search results weekly to adjust strategy. The piece emphasizes that maintaining brand visibility in AI answers requires continuous, cross-functional effort rather than quarterly campaigns.

• SparkToro analysis of Similarweb panel data (first four months of 2026) found 68% of U.S. Google searches end without a click.
• Pew Research found users click a traditional search result in only 8% of visits when an AI summary appears, versus 15% without.
• The article advocates for a weekly PR-SEO-content workflow for GEO.

AI’s Best Content Role Is Strategy, Not Volume

An industry perspective by Dan Baptiste, EVP at Skyword, argues that Generative AI's most valuable role in content marketing is strategy and analysis rather than mass-producing generic content. While traditional SEO favored high-volume content, AI-powered discovery and search engines now reward authoritative, proprietary data and expert viewpoints, deprioritizing recycled web content. The article outlines three key ways to utilize AI for strategic value: detecting market trends from customer platforms, auditing existing content to bridge narrative and authority gaps, and atomizing human-written cornerstone assets into multi-channel formats to maintain brand authority.

• According to Sparktoro data, 68% of search queries now end without a click, signifying a major shift in audience traffic patterns.
• AI-powered search and discovery engines are increasingly deprioritizing content that merely recycles existing web information.
• The author advises using AI for market trend analysis, content gap audits, and asset atomization instead of automatic writing.

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