The search engine optimization landscape is undergoing its most volatile evolution in a decade. With the introduction and expansion of Google’s AI Overviews, traditional search strategies are being challenged by generative algorithms. Among the most affected sectors is B2B and SaaS marketing, where companies have historically relied on comparative content to capture high-intent traffic. However, a groundbreaking analysis reveals that one of the most popular tactics in this space—publishing self-serving “best of” listicles—is actively backfiring on the brands that use them.
According to a detailed study conducted by SEO expert Lily Ray, Google’s AI Overviews frequently cite these self-promotional listicles as sources of information, yet recommend the brand’s direct competitors in the generated response 69% of the time. This phenomenon represents a major paradigm shift: your own content, optimized at great expense, could be serving as the data source that drives potential customers directly into the arms of your rivals.
The Mechanics of the Study: Examining the Data
To understand the scope of this trend, Lily Ray tracked 100 B2B search queries framed around “best [category] software” (for example, “best CRM software” or “best project management tools”). The data was pulled across three specific dates to observe changes over time: April 15, May 15, and June 8.
Using Ahrefs Brand Radar, the research analyzed both the text generated by Google’s AI Overviews and the sources cited in the link cards. Out of the 100 queries tracked, 80 prompts successfully triggered an AI Overview. Within these generative responses, the following patterns emerged:
- High Citation Rates: Self-promotional listicles—pages written by a brand that ranks itself as the top solution—were cited a total of 323 times.
- The Recommendation Gap: In 224 of those instances, Google’s AI Overview used the brand’s listicle as a reference citation but completely excluded that brand from the actual recommendations generated in the text.
- The 69% Disconnect: This means that in nearly 70% of cases, writing a self-serving listicle resulted in Google utilizing your page’s data to recommend other software providers while ignoring your own product.
Why Google AI Overviews Separate Citations from Recommendations
To understand why this is happening, it is necessary to examine how large language models (LLMs) and retrieval-augmented generation (RAG) systems operate. When a user inputs a query like “best LMS for selling courses,” Google’s retrieval system searches the index for high-quality, relevant documents to feed into its generator.
A comprehensive comparative listicle written by an industry player often contains structured data, clear comparisons, and detailed feature breakdowns of various market options. To an algorithm, this page looks like a highly informative resource. Google’s AI scraper extracts the information, summarizing the pros, cons, and features of the various software platforms listed on the page.
However, when the generative model synthesizes the final response, it applies a layer of entity verification and brand trust. The algorithm cross-references the claims made in the listicle with the broader web ecosystem. If the host website is a lesser-known platform claiming to be superior to industry giants, the AI system notices the discrepancy. It credits the source page with a citation link (for transparency and sourcing), but its actual natural language recommendation is reserved for the entities that possess stronger independent validation across the web.
The Oasis LMS Case Study
The study highlighted several stark examples of this dynamic in action. For the query “best LMS for selling courses,” Google’s AI Overview cited a comparative article published by Oasis LMS. However, Oasis LMS was not among the platforms recommended in the generated text. Instead, the AI Overview recommended:
- Kajabi
- Thinkific
- LearnWorlds
- Teachable
All four of these recommended platforms were mentioned and analyzed within the Oasis LMS article. In essence, Oasis LMS did the heavy lifting of researching, formatting, and publishing a comparative guide, only for Google to strip that data, present it to the searcher, and direct those users to Kajabi and Thinkific.
This pattern was not isolated to the learning management space. Similar occurrences were documented across various highly competitive B2B software verticals, including:
- Help desk and customer support software
- Task and project management platforms
- Survey and feedback tools
- Customer Relationship Management (CRM) systems
- Search Engine Optimization (SEO) software
The Invisible Hand of Brand Authority
If self-promotional content is being bypassed, who is winning the recommendations? The data indicates that Google’s AI Overviews rely heavily on established brand authority and third-party validation.
Brands that already led their respective categories, possessed strong backlink profiles, and were widely mentioned across independent media outlets and forums were far more likely to be recommended by the AI. This suggests that LLMs rely on a consensus-based model. If dozens of independent publications, forums, and directories agree that a specific CRM is the best for small businesses, Google’s AI will recommend that CRM, even if it extracts the supporting details from a competitor’s blog post.
This creates a compounding disadvantage for smaller or mid-tier SaaS brands. Relying on clever content optimization alone is no longer enough to win the primary visibility spot in search results. If the broader web does not validate your self-proclaimed status, the AI will use your data but give the conversion opportunity to your competitor.
The Fall of Organic Visibility and the May 2026 Core Update
The shift in how AI Overviews handle self-promotional content is part of a broader, systemic decline in organic search visibility for sites relying on these tactics. According to historical tracking, a downward trend for many of these B2B and SaaS sites began around January 20.
Many of these affected companies had scaled up content production strategies designed to dominate both traditional Search Engine Optimization (SEO) and Generative Engine Optimization (GEO). These strategies included:
- Mass-producing AI-generated comparison and alternative pages.
- Creating programmatic directories and “best of” hubs that systematically ranked their own brand as the top option.
- Targeting hundreds of long-tail transactional keywords with thin, highly biased reviews.
While these tactics initially drove traffic, they faced severe corrections during subsequent search ranking adjustments. This decline accelerated dramatically during Google’s May 2026 core update. Many brands that relied heavily on self-ranked listicles saw their overall search visibility drop by 30% to 50%.
Where Is Google Sourcing Its Recommendations?
As Google demotes brand-owned, self-serving listicles, it has shifted its reliance to alternative source types to answer “best” queries. The study notes a significant increase in citations from third-party authority sites and platforms containing user-generated content (UGC).
Among the most-cited domains in AI Overviews containing the word “best” are:
- Forbes: Known for highly authoritative, broad-topic buying guides and directory lists.
- Reddit: Valued by search engines for offering real, unvarnished human opinions and discussions on software performance.
- YouTube: Frequently cited for video demonstrations, tutorials, and third-party software reviews.
The rise of Reddit citations in search results highlights Google’s effort to prioritize authentic user experiences over highly optimized corporate marketing copy. For marketers, this means that off-page SEO, digital PR, and community engagement are becoming more critical than on-site comparative content.
The Rising Legal Risks of Self-Ranked Listicles
Beyond the loss of organic search visibility and referral traffic, the practice of publishing self-ranked “best of” lists carries growing regulatory risks. In the United States, the Federal Trade Commission (FTC) has steadily tightened its guidelines regarding consumer reviews and testimonials.
Under the FTC’s Consumer Review Rule, presenting company-controlled marketing content as independent, unbiased reviews can be classified as a deceptive practice. The rule targets several specific actions common in B2B SaaS marketing:
- Writing reviews or rankings of your own product without clearly and conspicuously disclosing your material connection to the brand.
- Falsely implying that a “best of” list is based on independent testing or objective, third-party user feedback when it is actually an internal marketing asset.
- Suppressing negative reviews or artificially inflating ratings on company-controlled comparison portals.
As search engines and regulators both crack down on deceptive review practices, the legal and financial risks of using self-serving listicles may soon outweigh any remaining SEO benefits.
How B2B Marketers Must Adapt Their Strategy
The realization that a citation in an AI Overview does not equal a recommendation requires a fundamental reassessment of B2B content marketing. To maintain visibility and capture high-intent leads in an AI-driven search environment, brands should consider the following strategic pivots:
1. Focus on Entity-Building and Off-Page Trust
Because AI Overviews recommend brands with strong web consensus, priority must be given to building real authority. This involves earning genuine mentions and reviews on independent third-party platforms, participating in industry-specific discussions on forums like Reddit, and securing coverage in reputable publications. The goal is to ensure that when Google’s LLM cross-references your brand name, the consensus across the web is overwhelmingly positive.
2. Pivot to Transparent, Unbiased Comparison Content
If you publish comparison pages, aim for transparency. Instead of automatically ranking your software as number one in every category, provide realistic, objective comparisons. Detail the specific use cases where your competitors might be a better fit, and clearly define your product’s unique strengths. Highly objective content is more likely to be trusted by both users and modern search algorithms.
3. Optimize for User-Generated Platforms
With Reddit and YouTube gaining substantial visibility in AI Overviews, B2B brands should establish a presence on these platforms. Encourage your actual users to share their experiences, post video tutorials, and discuss your software online. Actively participating in these spaces helps build a footprint of genuine user sentiment that search engines can easily crawl and understand.
4. Align Marketing with Product Reality
In an ecosystem where AI can analyze thousands of customer reviews in seconds, marketing claims must align closely with product performance. Invest in customer success, product quality, and customer support to naturally generate positive reviews on platforms like G2, Capterra, and Trustpilot. These directories serve as primary data sources for search engines synthesizing B2B recommendations.
A New Era of Search Visibility
The era of manipulating search rankings through highly optimized, self-serving listicles is drawing to a close. Google’s AI Overviews have introduced a new dynamic where your own content can be used to fuel your competitors’ growth. Succeeding in this new landscape requires a shift away from hyper-optimized, biased content toward genuine brand authority, transparent reporting, and robust third-party validation.