From traffic to AI shortlist: What the latest studies reveal about software searches
Carmen Martins & Rebecca Loeks3/1/2026
This is how we respond at OMR Reviews in order to be cited as a reliable source of AI
Table of contents
- Takeaway 1: External sources are crucial
- Takeaway 2: Review platforms and listicles are important AI sources
- Takeaway 3: Real data (information gain) is preferred
- Takeaway 4: Content timeliness as a relevance signal
- Conclusion: Traffic is no longer a reliable growth metric
Let's be honest: classic organic traffic via Google is declining noticeably in many areas. The software industry is also experiencing a decline. According to recent analyses by G2, B2B software buyers now use large language models (LLMs) – AI language models such as ChatGPT, Perplexity, or Google's AI Overviews (the AI summaries directly in Google search results) – to start their research. Instead of laboriously scrolling through Google search results, they let AI build a software shortlist for them in seconds.
For you as a tool provider, this changes the focus: it is no longer primarily about clicks on your own website, but about being mentioned in the AI response. Those who are recommended by the models are more likely to end up in the relevant set of decision-makers.
We took a close look at the latest studies on AI search (also known as Generative Engine Optimization or GEO). The good news: the studies show very clear patterns of success. And the even better news: we at OMR Reviews are already successfully implementing much of what is required as “best practice” there. Read on to find out what four insights we can draw from the analyses.
Key takeaways
- AI models prefer external third-party sources such as OMR reviews for validation.
- Unique user data (information gain) increases the likelihood of AI citations.
- Structured ranking articles from OMR Reviews promote top AI rankings for providers.
- The timeliness of reviews serves as a decisive relevance signal for language models.
Takeaway 1: External sources are crucial
A comprehensive study by AirOps has shown that 85 percent of brand mentions in AI responses come from external third-party sources and not from the software brand's own domain. AI models look for validated information and independent confirmation. When third-party platforms and real users confirm the strengths of a tool, LLMs evaluate this as a reliable fact.
What we do at OMR Reviews:
We offer precisely this external validation. With our genuine user reviews, we position tools in a trustworthy environment. AI models rely on our domain as an authority to support their recommendations.
Takeaway 2: Review platforms and listicles are important AI sources
Where do AI tools get their information for comparisons? An analysis by SE Ranking shows that almost one in three Google AI Overviews (31.9%) contains a link to a review platform. When users explicitly search for reviews, this proportion rises to 63.5%. In German-speaking countries, Trustpilot and OMR are among the dominant sources. In addition, the AirOps study shows that almost 90 percent of mentions in third-party sources come from listicles and comparison articles.
What we do at OMR Reviews:
We publish highly structured ranking and comparison articles that contribute precisely to this. A fitting example is our Newsletter-Tool-Ranking from the last five years, which is used as a primary source by AIs such as Perplexity. As a result, rapidmail und Brevo, the highest-rated tools, showed an increase in citations to the stored prompt set.
Screenshot of the article on the newsletter tool ranking over the last five years, which is based on primary data from OMR Reviews.
We see something similar in the Made in Germany article “Rapidmail vs. Mailchimp”. Within a few weeks of its publication in October 2025, the article had 120 citations on specific technical issues and the advantages of “Made in Germany.” Our article is the most cited independent source in the entire set. It ranks third in the entire set, directly behind the compared tools rapidmail and Mailchimp themselves – ahead of specialized players such as EmailToolTester or Markop (source: Rankscale).
This proves that our content is used by LLMs as a reliable source for in-depth comparisons and German market specifics.
Takeaway 3: Real data (information gain) is preferred
AI models reward what is known as information gain, i.e., content that provides new data and unique perspectives. Generic statements are cited less frequently by LLMs; instead, specific facts, structured data, and authentic empirical values are in demand.
What we do at OMR Reviews:
Instead of interchangeable content, we focus on primary data in addition to editorial quality. We use verified insights from our community and the OMR Score to underpin our articles with real value. We also structure our content in an AI-friendly way – with clear headings, bullet points, expert opinions, tables, and infographics.
Screenshot of a German “best of” article on ContentHub with tables and info box on the ranking methodology of the OMR score.
Lesetipp: Learn more about the difference between GEO and SEO here .
Takeaway 4: Content timeliness as a relevance signal
Another key criterion for LLMs is the timeliness of the data. According to AirOps, 70 percent of the pages cited by AI have been updated within the last year.
What we do at OMR Reviews:
Thanks to the constant influx of new user reviews on our platform, the signals for the listed tools always remain up to date. At the same time, we regularly maintain and revise our content pieces so that AI models always have access to the latest market conditions.
Conclusion: Traffic is no longer a reliable growth metric
A decline in general traffic is no cause for concern, as the quality of users from AI searches is high according to current analyses. Data shows that traffic generated via AI chatbots can have a conversion rate up to six times higher than traditional Google traffic. These users are already deeper in the decision-making process, as the AI has presented the tool to them in advance as a validated solution.
Our takeaway for tool providers: Simply being present on your own website is often not enough to be recommended in AI responses. With our authority as a software review platform and targeted content formats, we at OMR Reviews help establish brands as reliable options in the new search reality and make them visible where shortlists are created.
Quellenverzeichnis
Author
Carmen Martins
Carmen ist Teamlead Content bei OMR Reviews und sorgt mit ihrem Team dafür, dass aus dem oft unübersichtlichen Software-Markt klare Orientierung wird. Mit einem Mix aus strategischem Content Marketing und innovativen GEO-Ansätzen entwickelt sie Lösungen, die Usern echten Mehrwert bieten und Entscheidungen erleichtern.
Author
Rebecca Loeks
Rebecca ist Senior SEO-Consultant bei OMR Reviews und bringt Inhalte genau dahin, wo sie hingehören – an die Spitze der Suchergebnisse. Dank +6 Jahren Erfahrung in SEO- und Content-Strategien weiß sie, welche Hebel wirklich funktionieren. Ihre Devise: datengetriebene Entscheidungen, smarte Tools und hohe Qualitätsstandards.