Buyers don't start with ten blue links anymore. They ask an AI assistant, and the assistant searches the web, reads what it finds, and hands back a short list of recommendations with sources attached. Whatever makes it into those sources decides which brands exist in the answer. Everything else is invisible.
At Prompt Journey we simulate this process at scale: psychologically distinct buyer personas run multi-turn research conversations with web-search-enabled language models, moving through awareness, consideration, and decision the way a real buying committee would. Every source the model retrieves gets logged. That gives us something rare: a citation-level view of AI buyer research, including every Reddit thread the models chose to read.
This report covers 1,828 of those conversations across 73 research runs and 114 personas, which together produced 35,946 source citations. 1,139 of them came from Reddit, spanning 767 unique URLs across 219 subreddits. We enriched every cited post with live archive data (publication date, upvotes, comment counts) and every subreddit with its member count. Seven findings stood out.
The headline numbers:
- Reddit ranks #3 among all cited sources, behind only PubMed and LinkedIn.
- 23.5% of buyer-research conversations retrieved at least one Reddit thread.
- 53% of cited posts are question threads, the single dominant format.
- The correlation between a post's upvotes and how often AI cites it is r = 0.02.
This report is a an aggregation of what Prompt Journey measured for a multiple brands. It is in early access, join the waitlist to see the same breakdown for your own category.
Finding 1: Reddit is the third most-cited source in AI buyer research
Where do the models actually read? Mostly on companies' own turf: product pages, vendor blogs, and brand websites absorb 71% of all citations. But among independent, third-party sources the hierarchy is striking. Academic and medical databases come first (inflated by health-sector runs in our sample), LinkedIn second, Reddit third. As a single domain family, reddit.com ranks #3 overall, outranking every review platform, social network, and news outlet the models touched.
For scale: company and product websites, the pages of the brands and vendors being researched, absorb 25,505 citations, or 71% of the total. The chart below covers the remaining third-party sources.
Fig. 1: Third-party citations grouped by source category, out of 35,946 total. LinkedIn and Reddit are shown individually; every other domain is clustered by type.
Nearly one conversation in four (23.5%) touched Reddit at some point. For a single user-generated-content platform, that is a remarkable footprint: the models treat Reddit as a first-class research source, on par with professional networks and academic databases.
For marketers: Your own website still matters most. But if your AI-visibility strategy covers your site, review platforms, and press while skipping Reddit, you are ignoring the third-largest independent input into AI answers about your category.
Finding 2: Community size is irrelevant, relevance is everything
Here is the counterintuitive one. We correlated each subreddit's citation count against its member count across 195 communities. The result: essentially zero relationship (Pearson r = -0.04; log-log r = 0.01). The rank correlation is actually negative (Spearman rho = -0.29), meaning smaller communities get cited proportionally more.
A 567-member subreddit earned 72 citations. A 22.5-million-member subreddit earned one.
The most-cited communities in our data are small, hyper-specific professional forums: r/agency (14.6K members, 98 citations), r/coldemail (567 members, 72 citations), r/b2bmarketing (6K members, 63 citations). Meanwhile the giants, r/IAmA, r/javascript, and r/Makeup, each with over a million members, appear once or twice at most.
Fig. 2: Average citations per subreddit, grouped by community size. The under-1K bucket outperforms the over-500K bucket by 2.5x.
For marketers: Stop chasing big subreddits. Search retrieval matches topics, not audiences. A niche community that exactly matches a buyer's query beats a giant one every time. Map the 5 to 10 small professional subreddits where your category is actually discussed.
Finding 3: Freshness beats popularity, and upvotes barely matter
We pulled archive stats for all 746 unique cited posts. Two patterns emerged. First, recency: 82% of cited posts were published within the last two and a half years, and more than a third within the last twelve months (median post age: about 16 months). AI search skews hard toward recent threads.
Second, and this is the one that should change how you think about Reddit, engagement is close to meaningless. 44% of cited posts have five or fewer upvotes. The median cited post has 7. The correlation between a post's upvotes and how often it gets cited is r = 0.02: statistically, nothing.
Fig. 3a: Publication year of the 746 cited posts. Recency is strongly favored.
Fig. 3b: Upvote distribution of the cited posts. Popularity is not favored.
For marketers: A three-upvote post published last quarter in the right niche subreddit can outperform a 2,000-upvote legacy thread. You do not need virality. You need recent, on-topic threads to exist. Refresh the conversation regularly.
Finding 4: Questions are the citation magnet
We classified all 1,139 cited post titles by format. Questions dominate: 53% of everything the models cited is a question thread, the 'Has anyone tried', 'How do you guys use', and 'What is the best' variety. Reviews, comparisons, and how-to guides each account for a small fraction by comparison.
The logic is straightforward: an AI researching a purchase is itself answering a question, and a Reddit thread whose title is that question, with a comment section full of practitioner answers, is the perfect retrieval target. The most-cited single post in our entire dataset is a question with 35 upvotes: 'Anyone Having Success with an AI Automation Business?' (r/automation), cited 29 times.
For marketers: Find the open questions in your category's subreddits and make sure they have substantive answers, ideally from genuinely helpful practitioners (astroturfing gets deleted and burns trust). Every unanswered buyer question on Reddit is an AI citation waiting to be filled by you or your competitor.
Finding 5: Pricing talk owns the decision stage
Each conversation in our pipeline belongs to a buyer-journey stage: awareness, consideration, or decision. Classifying the search queries that led to each Reddit citation reveals a clean funnel pattern. Pricing and cost queries are the single largest classified theme (248 citations), and 57% of them occur at the decision stage. Buyers go to Reddit to find out what things really cost right before they choose.
Review-and-experience queries peak in the middle of the journey, at consideration, when shortlists are being pressure-tested against peer experiences. Comparison and 'alternatives' queries follow the same mid-funnel curve.
Fig. 5: Search query themes behind Reddit citations, split by buyer-journey stage.
For marketers: Buyers use Reddit to bypass your pricing page and find the unfiltered number. If real costs, honest ROI experiences, and 'is it worth it' discussions about your product do not exist on Reddit, the AI fills the decision-stage gap with whatever it finds, often a competitor's thread.
Finding 6: Searches for B2B buyers lean on Reddit 3.3x more than consumers
Splitting the 114 personas by buyer type: B2B personas retrieved Reddit in 27% of their conversations, B2C personas in just 8%. The pattern held across nearly every run in the sample.
Fig. 6: Share of conversations retrieving at least one Reddit source, by persona buyer type (90 B2B personas / 1,466 conversations vs 24 B2C personas / 362 conversations).
Why? Professional purchases are precisely where peer validation matters most and where marketing claims are trusted least. A practitioner thread in r/sales or r/LawFirm functions as due diligence. Consumer questions, by contrast, route more often to review sites, publishers, and health databases in our data.
For marketers: If you sell to businesses, Reddit is not a nice-to-have channel. It is a primary input into how AI describes your category to buyers. B2C brands can deprioritize accordingly.
Finding 7: Reddit enters early, and works the whole funnel
Reddit is not a fallback source the models reach for when official pages run dry. In 44% of Reddit-citing conversations it appears on the very first search turn; by the second turn, 79%. The models reach for community opinion immediately.
And it stays. Of the 68 subreddits with three or more citations, 62% are full-funnel, cited at awareness, consideration, and decision alike. But the exceptions are instructive: a cluster of tool-specific communities (r/hubspot, r/googleads, r/CRMSoftware) has zero awareness-stage citations. Buyers only land there after they already know the product exists, an awareness gap a marketer could deliberately fill with earlier-funnel content.
Fig. 7: The conversation turn where Reddit first appears (429 conversations).
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For marketers: Treat subreddits like keywords: some are full-funnel, some are stage-locked. Seeding educational, problem-framing discussions in decision-only communities is uncontested territory to reach buyers a stage earlier than your competitors do.
See this for your own brand. Prompt Journey simulates your buyers' AI research and shows which sources, and which competitors, get cited along the way. It is in early access, join the waitlist to get in.
Methodology and limitations
This analysis is based on Prompt Journey's persona-simulation pipeline: AI-generated buyer personas conduct multi-turn research conversations using web-search-enabled language models, staged across awareness, consideration, and decision. Every source retrieved by the model during search is logged with its URL, title, snippet, and originating query. Prompt Journey is currently in early access; join the waitlist to run this pipeline on your own category.
- Sample: 1,828 conversations, 73 research runs, 114 personas, 35,946 total source citations, of which 1,139 were Reddit URLs (767 unique posts, 219 subreddits). Data collected through June 2026.
- Enrichment: subreddit member counts via subredditstats.com (195 of 219 matched); post publication dates, upvotes, and comment counts via the Arctic Shift archive (746 of 746 unique posts matched).
- Classification: query themes and post formats were classified with keyword rules; counts are directional rather than exact.
- Limitations: these are simulated buyer conversations, not logs of real ChatGPT or Perplexity users. The sample skews B2B (90 of 114 personas) and reflects the categories our customers ran: professional services, marketing technology, healthcare, and consumer aesthetics. Retrieval behavior may differ across model families and search providers. Client brands and persona identities are anonymized throughout.
Correlations reported: Pearson r on raw values, log-log Pearson on log-transformed values, Spearman rho on ranks. A citation means one retrieved-source entry in one conversation, deduplicated per conversation.
