Perplexity Loves Reddit: Exploring LLMs’ Top Sources

Deciding on a GEO strategy is a complicated endeavor, made more complicated by the fact that models rely on different domains to different degrees when using search to improve responses, a process known as Retrieval-Augmented Generation, or RAG. 

Using our GEO and AI marketing platform, we tracked the sources LLMs’ cited in responses to more than 200 million prompts made over the last five months. Because LLM responses are so dependent on the topic and wording of each prompt, we focused our analysis on four domains that are widely used and can be cited on an enormous range of topics. Those four are Reddit, Wikipedia, YouTube and LinkedIn. 

We found clear differences between models and changes for each model over time, but perhaps the clearest takeaway was how much Perplexity trusts Reddit.

Reddit Accounted for As Many As 1 in 5 Perplexity Citations

None of the five models we examined (ChatGPT, Gemini, Google AI Overview, Google AI Mode and Perplexity) gave as much weight to any one domain as Perplexity gave to Reddit. It cited Reddit in 20% or more of its responses at times in January and February, based on a rolling 7-day average. 

ChatGPT, by contrast, cited Wikipedia the most out of the four domains we analyzed, but Wikipedia’s share of citations topped out at around 5%.

Perplexity’s affection for Reddit does not appear to be mutual. Reddit is suing Perplexity for allegedly circumventing the social media site’s data protections to scrape data, a claim Perplexity denies.

Models’ Citing Behaviors Change Over Time

Reddit was Perplexity’s most-cited domain of the four we examined for the entirety of the last five months, but its share of citations climbed noticeably beginning in December. It is possible to see behavioral changes like this as model makers release new versions with different algorithmic behaviors and training methods. 

YouTube, for example, appears to be gaining citation share on both Perplexity and Google AI Overview. You can compare how each domain’s share is trending on each platform by selecting a domain in the menu below.

Although we focused our analysis on Reddit, Wikipedia, YouTube and LinkedIn, it is clear that these are not the only four domains you should consider when working to improve AI visibility. On all of the models except Perplexity, the combined share of the four domains rarely exceeded 5% of citations. The other 95% of citations are spread across thousands of other domains. No one domain is dominant, and each domain’s share of citations changes over time.

The chart below shows the distribution of the combined domains’ citation share per model, with each dot representing one day’s 7-day rolling average. Gemini consistently gave the four domains very little weight, although there is a clear increase in February. ChatGPT, too, gave the domains more weight in recent months than in October and November. Then there’s Perplexity, which had a very wide range of weights for the domains stretching from about 6% to more than 30% and high variability within each month.

It is also important to note that models do not always incorporate search in their responses. In some cases, LLMs use only the foundational knowledge they have from their training, one of the key differences that separate GEO from SEO. At Evertune, we prompt models’ foundational knowledge directly and track this separately from search-assisted model responses.

Evertune is the Generative Engine Optimization (GEO) and AI marketing platform that helps leading enterprise brands improve visibility in AI search by analyzing responses at scale and delivering actionable insights. With data-driven content creation and distribution strategies to increase AI discoverability, Evertune’s platform is purpose-built for AI search as a marketing channel. Founded by early team members of The Trade Desk and headquartered in New York City, Evertune has raised $20M in funding from leading adtech and martech investors.