New research by ICODA agency tested whether crypto projects are uniquely exposed to Reddit in AI-generated answers. They aren’t, and that’s the worse news.
The test ran clean reputation prompts, questions like “has anyone had problems with X” and “is X a scam,” through Perplexity across 12 crypto brands, then repeated on a control group of unrelated brands (Notion, Salesforce). Reddit was never named in the prompts:
- Crypto: Reddit cited in 88.4% of responses, 24.6% of all citations
- Control: Reddit cited in 90.0% of responses, 29.3% of citations
Statistically, no difference, and the control ran slightly higher. Crypto isn’t a special case. It’s already how AI retrieval treats every industry that gets asked a trust question.
Why “You’re Not Special” Is the Worse News
A null result sounds like nothing to build on, but this one proves the exposure is structural, not a crypto-specific fix. A crypto-only problem could be patched with category-level PR; a mechanism that treats every reputation question the same way has to be managed project by project. Any blockchain advertising agency or crypto marketing agency still pitching this as a crypto problem is selling the wrong diagnosis.
Reddit Is the Substrate of Trust Queries, Not Just Crypto Ones
Reddit dominates reputation answers across the board, not only crypto:
- This test’s own data: reddit.com was the single most-cited domain, 6.4× ahead of the runner-up, Trustpilot (3.8%)
- Ahrefs: Reddit ranks #2 in Google AI Overviews, an 18.5% mention share, behind only YouTube
- Profound: Reddit ranks #1 on Perplexity, #2 on ChatGPT and AI Overviews, but #31 on Microsoft Copilot, proof “AI search” isn’t one surface
- Evertune (a broader sample, all question types): no domain, Reddit included, exceeds roughly 5% of citations
That’s not a contradiction, just a different question mix: reputation queries pull harder toward Reddit than the average prompt does.
The Question Shape Decides the Source, Not the Industry
What predicts a Reddit citation is the shape of the question, not the vertical asking it, and the pattern replicates across industries:
Experience questions run roughly 3× more Reddit-dependent than recommendation ones, in both crypto and the control, a pattern, not a coincidence.
The Thread Deciding Your Reputation Is Probably Three Years Old
Reputation used to decay. In AI retrieval, it doesn’t. Cited Reddit threads in this test average 1,186 days old (3.2 years), median 1,013, and 71% are over two years old. Semrush’s cross-vertical baseline puts the average cited post around 900 days old; this sample runs about 30% older.
The thread an AI engine quotes about your project right now was probably posted before your current marketing hire started; nothing in retrieval rewards recency the way a news cycle does.
Two Things You’d Assume Protect You. Neither Does.
- Sentiment. Profound found positive-sentiment Reddit content cited at 5%, negative at 6.1%, nearly identical. A brand with a strong positive aggregate score can still have its most-quoted thread be the angry one.
- Engagement. Semrush found 80% of cited Reddit posts have fewer than 20 upvotes, median 5 to 8. This analysis couldn’t replicate that itself (Reddit blocked every metadata path), but the baseline holds: you can’t outvote or bury a thread retrieval never sorted by engagement to begin with.
The Seam: Where ORM and AI Visibility Both Miss It
Reputation exposure in AI answers falls into a gap between two services most crypto projects already pay for:
That content scores near zero on every metric ORM sorts by, and sits in a query class GEO doesn’t target: invisible twice, to two vendors, and each one can honestly say “that’s not what we do.”
Most blockchain advertising agencies aren’t tracking this. The standard Web3 online reputation management stack sells mention and sentiment tracking with no AI-search layer, and GEO, where it appears, is a separate, unmerged service line. Nobody’s selling the join.
Why This Can’t Wait for Next Quarter
Reddit’s weight in AI answers is a paid, unstable commercial arrangement:
- Google pays roughly $60 million a year for Reddit’s data, feeding Search and Gemini; a separate OpenAI deal feeds ChatGPT, and Reddit has blocked general crawlers to protect both deals
- As of late July 2026, Reddit was weighing cutting off Google’s access; its stock fell 9%, and Wells Fargo estimates $500 million of licensing revenue at stake
None of this changes the mechanism, but it changes how much weight today’s numbers deserve, the real argument for treating AI marketing for crypto and blockchain projects as an ongoing measurement job, not a one-time check.
You Can’t Press-Release Your Way Out, and You’re Watching the Wrong Rooms
The model is reading the thread, not your announcements: of 36 subject-specific answers scored, 31 grounded their caution in user reports, not official action. That rules out the reflex fix (announce good news, hope it outranks the bad) and gaming the thread (a Reddit terms-of-service and FTC risk). What’s left, and what a client can’t do alone, is engaging the actual complaint in the actual thread. A Princeton study found clearer claims, citations, and formatting lifted AI citation rates 22 to 41%, on owned pages, not Reddit threads.
Most of that citation volume sits in subreddits built around individual brands: r/ledgerwallet, r/Coinbase, r/CelsiusNetwork, r/Metamask, r/LidoFinance, r/UniSwap, r/KrakenSupport, not the general forums agencies monitor. Watching “crypto Reddit” as one feed means watching the wrong rooms.
What to Actually Measure
Closing the seam means tracking a metric set neither ORM nor GEO tooling owns on its own:
- Citation-source inventory: which URLs ground AI answers about your project, per trust query
- Age profile of the cited set: how much of your AI reputation predates your current team
- Query-class coverage: experience questions tracked, not only “best X”
- Recurring-thread register: threads cited repeatedly across engines (about one in eight did)
- Per-engine split: Perplexity, ChatGPT, and Copilot retrieve differently
None of that shows up on a standard mention-tracking dashboard, and it’s cheap to test: about a dollar per project.
Closing This Gap Takes One Team, Not Two
Splitting reputation work across a separate ORM vendor and a separate AI-visibility vendor guarantees the exact blind spot this piece describes, since each one is built to watch half the problem. Closing it means one practice that reads Reddit the way ORM does, but scores what it finds by what AI engines actually cite, not by upvotes or reach.
This research came out of ICODA, a crypto marketing agency that runs both sides of that practice under one roof rather than splitting them across separate vendors. As a full-service agency, ICODA builds each engagement, ORM, AI visibility, or anything else, around the specific project’s goals instead of a fixed package: a citation inventory, an age profile, a question-shape breakdown, tailored to the brand being audited, not a generic sentiment score. Plenty of teams can point at this gap; fewer can hand a project the actual thread list, ages, and subreddits carrying the risk.
Getting started costs nothing: ICODA’s specialists run a free ORM and AI Visibility audit that covers both sides of the seam in one pass.
