AI Overviews Can Recommend Competitors From Your Own Listicles, Study Finds

A recent analysis highlights a significant shift in how Google’s AI Overviews process “best [category] software” listicles, often leading to a brand’s content being cited while a competitor receives the actual recommendation. This trend, identified by marketing expert Lily Ray, suggests that traditional self-ranked listicle strategies may backfire in the age of AI search. For businesses in India, particularly those in the rapidly growing SaaS and tech sectors, understanding this dynamic is crucial for refining their digital marketing and SEO efforts.

The study, which examined 100 B2B “best [category] software” queries in Google’s AI Overviews between April and June 2026, found that self-ranked listicles were frequently cited as sources. However, in a striking 69% of these cases, Google’s AI recommended a rival product listed within the same article, rather than the brand that published the listicle. This indicates a clear distinction between a citation (naming a page as a source) and a recommendation (telling the user which product to choose), with only the latter driving direct sales.

Understanding the Citation-Recommendation Gap

The core issue lies in the “citation-recommendation gap.” While a citation acknowledges a brand’s content, the recommendation is what truly influences buyer decisions. Ray’s research suggests that Google’s AI treats self-ranked pages differently. Brands that secure recommendations are generally established names with extensive third-party coverage, including independent sites, reviews, and mentions across the wider web. This implies that on-page SEO adjustments alone are insufficient to bridge this gap.

The data shows that recommended brands had significantly more referring domains and mentions across various AI platforms, including ChatGPT. This suggests that Google’s AI prioritizes external validation and broad web coverage when making recommendations, rather than solely relying on a brand’s self-promoted content.

Key facts:

Metric	Finding
Queries analyzed	100 B2B “best [category] software”
AI Overviews generated	80
Self-ranked listicles cited	323 times
Competitor recommended from cited listicle	224 times (69%)

Implications for Content Strategy in India

For Indian businesses, particularly startups and SaaS companies aiming for visibility in a competitive market, this research underscores the need to re-evaluate content strategies. Simply publishing listicles that rank your own product highly may no longer be an effective path to AI-driven recommendations. Instead, the focus should shift towards building a robust ecosystem of independent third-party endorsements.

The study points to the importance of increasing the number of web pages about a product on domains not controlled by the brand. This includes fostering more third-party reviews, comparisons, and walkthroughs. Platforms like Reddit, Forbes, and YouTube were among the most-cited domains for recommendations, highlighting the value of diverse, independent content.

Building an Affiliate Ecosystem for Recommendations

One effective strategy identified is to establish or enhance affiliate programs. Instead of one-off commissions for individual pieces, an always-on affiliate program can incentivize creators to consistently produce reviews, update comparisons, and publish walkthroughs. These affiliates, ranging from niche site owners to YouTube reviewers and media publishers, generate the kind of independent content that Google’s AI Overviews are more likely to recommend.

The success of such programs hinges on recruiting partners who are genuine content creators with established audiences, rather than those focused solely on discount codes or driving raw referral volume. By funding continuous, high-quality third-party coverage, businesses can organically increase their referring domain counts and web mentions, thereby improving their chances of securing AI recommendations. This approach aligns with the long-term goal of building brand authority and trust, which AI search engines increasingly value.

Source: Search Engine Journal, https://www.searchenginejournal.com/ai-search-recommending-competitors-firstpromoter-spa/581579/