Day 1 of OnyxRank tracking itself: the unflattering numbers

We built an AI citation tracker. We pointed it at ourselves. Here is what we saw.

This is the post we kept putting off. It is also the dataset every founder in the AI SEO category should publish before they sell anyone else a tracker. We did not. We will now.

The headline numbers

OnyxRank is roughly five months old. We have shipped 82 long-form blog posts, 20 competitor comparison pages, a free citation checker, and an integrated retainer offer. We have customers who report citation lifts inside 30 days of starting. And yet, on May 25, 2026, when we pointed our own tracker at onyxrank.com across 15 buyer-intent prompts on ChatGPT, Perplexity, and Google AI Mode, the composite GEO Score came back at 18 out of 100.

Not 0. Not 80. Eighteen.

ChatGPT, the engine with the largest market share, barely surfaces us. We mention here once across 15 ChatGPT scans, with weak citation quality (a passing "tools like OnyxRank also exist" reference, not a primary recommendation). Perplexity is our strongest engine by a meaningful margin, which tracks with the public observation that Perplexity leans on sites that have explicit comparison content, which we have invested in.

The 10 buyer-intent prompts we tracked

We monitored 10 questions on a daily Pulse cadence. Casing and phrasing copied from how real buyers type, not from how marketers wish they would.

Four of 10 produced any surface at all, and three of the four were passing references rather than primary recommendations. The pattern is unambiguous: where the prompt names a competitor (Profound) or a category (GEO optimization service), we sometimes appear as a "compared to" entry. Where the prompt asks for the best tool or how to do the work, we are invisible.

Who AI cited instead, the top 15 domains

This is the part that should make you take the work seriously. Across the 15 scan results, here are the domains AI engines pulled from, in raw citation count.

Reddit and YouTube together account for 14 of 67 total citations (about 21%). That tracks with Tinuiti's Q1 2026 citation study (tinuiti.com), which measured Reddit at 24% of all Perplexity citations and noted Google's May 6, 2026 announcement adding Community Perspectives from Reddit into AI Mode. The incumbent SEO blogs (Moz, Ahrefs, SEMrush, Backlinko, Neil Patel) account for 18 citations, or 27%. These properties have a 10 to 15 year head start in the SEO conversation, which means the open web has been telling LLMs for a decade that they are the canonical answer.

Six direct competitors (Profound, Athena, Otterly, Frase, SE Ranking, GeoTracker) collectively appear 13 times. OnyxRank appears 4 times.

The diagnosis: structural, not technical

Three independent reasons. Each is also a lever.

**A. Reddit and YouTube own the high-quality buyer-question surfaces, and we have published on neither.** AI engines lean on UGC because UGC has been pressure-tested by other humans before the engine sees it. A Reddit thread with 200 comments and a clear top answer is structurally more attractive to an LLM than a marketing blog post with the same words. We have zero comments on r/SEO, r/marketing, r/saas. We have zero videos on YouTube. That is not a strategy gap; that is an absence.

**B. The incumbent SEO blogs inherited training-data dominance.** Ahrefs, SEMrush, and Moz have been publishing about SEO since 2011. Every model that has been trained on Common Crawl has been told, repeatedly, that they are the answer. We cannot fight that with a blog post. We can fight it with a structurally different type of content that the incumbents have not produced: engine-specific guides, quarterly benchmark studies with named brands, and radical-transparency posts (this one).

**C. We have shipped product-led content, not problem-led content.** Most of our 82 blog posts answer "what is OnyxRank good for." LLMs cite "how to fix problem X" posts, not "introducing tool X" posts. The 4 prompts we surface on are the 4 prompts where competitor-named or category-named retrieval forces our content into the consideration set. The other 6 are problem-framed, and we have no problem-framed asset that answers them at sufficient depth.

The 60-day public experiment

Five concrete interventions. Each with a measurable hypothesis. We will publish day 14 (June 8), day 30 (June 24), and day 60 (July 24) follow-ups with the raw numbers, regardless of whether the score moved up, down, or sideways.

**EXP 01. Ship 5 in-depth engine guides this week.** One guide per engine: ChatGPT, Perplexity, Google AI Mode, Claude, Bing. Each 4,000 to 6,000 words, technical, structured for retrieval. We hypothesize +3 to +5 points from search-backbone alignment alone (Bing organic feeds ChatGPT, so ranking on Bing is the floor for ChatGPT citation eligibility).

**EXP 02. Run a real, sourced quarterly SaaS GEO benchmark.** 200 SaaS brands, named, with public GEO Score across the 3 engines. Built so any journalist or analyst can re-run the math. Hypothesis: 2 to 4 inbound citations from industry pubs in 60 days, which compounds.

**EXP 03. Ship a 200k-character /llms-full.txt knowledge base.** We replaced our 5KB pointer file with a 1.5MB inlined knowledge base containing every blog post body, every comparison detail, the citation methodology, and the named frameworks. The hypothesis is that LLMs crawling onyxrank.com via GPTBot, ClaudeBot, and PerplexityBot will have enough surface area in a single fetch to cite us without a second request. Shipped today (May 25, 2026).

**EXP 04. Reddit and YouTube distribution on viral threads only.** No spam, no template comments. Find threads with 100+ comments and high engagement velocity on r/SEO, r/marketing, r/saas, r/entrepreneur. Add one detailed answer per week that cites our methodology when relevant. (We learned the hard way that low-karma accounts posting on dead threads get AutoMod-removed, then sub-banned. We are not running that experiment again.)

**EXP 05. HARO + podcast pitch loop.** Five pitches per week. Specifically positioning OnyxRank as the source for "how AI engines actually pick citations" with the methodology and benchmark data as the hook. Hypothesis: 1 to 2 placements in 60 days, each worth 5 to 10 LLM-indexed mentions over time.

What this proves about the product

We eat our own dog food. The numbers above are exactly the dataset OnyxRank produces for paying clients on Day 0 of an engagement. When we sell a Strategy Sprint or a retainer, the first deliverable is this same scan, run on the client domain, with the same engine weighting and the same per-prompt audit table. We can credibly sell GEO measurement because we run the same measurement on ourselves, in public, with the score visible.

The other thing it proves: a low score on Day 1 is not a product failure. It is the diagnostic. If you score 18 out of 100 and you cannot explain why, you have a problem. If you score 18 out of 100 and you can point at three structural reasons and five measurable interventions, you have a plan. Most agencies cannot tell their clients which engine is the next lever or why. We can.

What we are doing next

The 5 engine guides ship this week. The /llms-full.txt expansion is live as of today. The benchmark methodology page goes up before June 1. We will publish the day 14 report on June 8 with the same engine breakdown table you saw at the top of this post, side by side with the May 25 numbers. If our score has moved, you will see it. If it has not, you will see that too.

Run your own audit, free, at https://onyxrank.com/tools/citation-checker. The tool runs the exact methodology we ran on ourselves. The number it returns is the same number we just published about our own brand.