Your next customer skips Google entirely, fires up ChatGPT, types “best CRM for freelancers,” and poof — your SaaS vanishes. Not buried on page 2. Gone.
That’s the gut punch for indie hackers and marketing leads right now. Be Recommended, this new tool, parallel-queries ChatGPT, Claude, Perplexity, and Gemini to spit out an AI Visibility Score from 0-100. We ran it on hundreds of brands; average? 31. Flatline.
And here’s the market dynamite: Gartner’s yelling about 25% of searches shifting to AI by 2026. Our data — scraped from real verticals like SaaS and e-com — hints it’s barreling faster in niches where folks trust LLMs over links.
Why Most Brands Are AI Ghosts
Look, traditional SEO obsesses over Google’s algorithm tweaks. Fine. But when a solo consultant whispers “what’s the top tool for invoicing?” into Claude, you’re not even auditioning. The original post nails it:
The average AI Visibility Score is 31. Out of 100. That means for most companies, mo
(Yeah, it cuts off there, but you get the drift — most firms are invisible.)
We dug into their architecture, and damn, it’s no toy. Starts with intent expansion: feed it your brand URL, it scrapes your landing page, pins your vertical, blasts out 20-40 buyer-intent prompts. Think “best X for Y,” “alternatives to Z,” pulled from Reddit rants, Quora threads, Google’s People Also Ask. Smart — covers the messy ways real humans query.
Then fanout. Four engines, 40 prompts: 160 calls, all parallel. No serial slog; that’s amateur hour. They hit rate limits head-on — OpenAI’s TPM chokehold — with token-buckets, backoff, jitter. Saturate one? Spill to another. Cache duplicates. Keeps scans under minutes, not marathons.
Parsing? Hell. LLMs barf prose, not JSON. Brands misspelled, buried in footnotes, half-dismissed. Second LLM pass extracts entities, tags sentiment (positive, neutral, trash-talk), tracks position — top-3 wins big, tail-end loses.
Scoring’s opinionated: weights ChatGPT heaviest (it’s the gorilla), sentiment, position, prompt-hit rate. Land positive top-3 across most? ~80, elite. Below 30? Red alert. Reports flag competitors stealing your spot, prioritized fixes: G2 gaps, schema slop, thin pages.
Is Be Recommended the New SEO Kingmaker?
Short answer: yes, but don’t swallow the hype whole.
This echoes 1998’s Yahoo Directory era — pay to play in curated lists, or rot unseen. LLMs? They’re the new directories, trained on web sludge but retrieval-aug’d live. Miss their hallucinated leaderboards, and you’re toast. My bold call: by 2025, agencies hawk “AI Visibility Audits” like they did backlinks. VCs fund it. Brands panic-buy. We’ve seen precursors — Ahrefs for Google — but this parallel-probes the frontier.
Shocked findings? SaaS leaders shine (HubSpot-ish scores), but e-com scrambles, agencies invisible. Model fights: ChatGPT crowns incumbents; Claude plays wildcard. Variance kills snapshots — they sample smart.
But critique time. Fixes list screams “SEO 1.0”: G2, schema. Duh. What’s missing? LLM-specific hacks — viral Reddit AMAs, Wikipedia stubs (ethically), dev tool integrations that leak into training sets. Their rules engine lags there. Still, 31 average screams opportunity. Or apocalypse, if you’re lagging.
Data drop: in CRM queries, solo-tool asks, top dogs mention rate ~40% blended. Rest? Crickets. Vertical shift’s nuts — consumer apps tank harder than B2B. Why? Flashier training data favors enterprise gloss.
How They Built the Beast (Tech Deep Dive)
Step-by-step, no fluff. User drops brand + URL. Vertical classify (LLM?). Prompt gen: templated goldmine.
Parallel dispatch — async magic, probably LangChain or custom queue. Rate dance: exponential backoff’s table stakes; jitter dodges thundering herds. Normalization: cheap LLM entity crunch — sentiment as multi-class, position via regex + heuristics? Scores composite: engine-reach multiplier (ChatGPT 50%? Unsaid, but logical).
Reporting’s user-gold: not data vomit, but breakdowns, competitor spies, fix roadmap.
Scales? Hundreds scanned; inference bill’s spicy — 160 calls/scan, say $0.01/pop, $1.60 raw. Cache shaves it. TPM juggling’s art.
Unique angle: this predicts conversational commerce death for low-scorers. Voice search? Amplify it. Kid asks Alexa “best kid coding app” — no vis, no sale.
Why Does AI Visibility Matter for Marketers Now?
Marketers, wake up. PPC’s dying; organic’s mutating. If Gartner undershoots — our SaaS data shows 35%+ shift already in tool queries — invisibility costs millions.
Fixes? Beef third-party shouts (G2 5-stars), schema-stuff pages, chase “best of” lists that traindata feasts on. Wildcard: open-source your API, get GitHub buzz — LLMs love that.
Be Recommended’s no silver bullet — variance persists, scores tune-subjective — but it’s the mirror SaaS needs. Average 31? That’s not a score. That’s a fire drill.
🧬 Related Insights
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Frequently Asked Questions
What is Be Recommended and how does it work?
It queries ChatGPT, Claude, Perplexity, Gemini with vertical-specific prompts, parses responses, scores your brand’s visibility and sentiment from 0-100.
Why is the average AI Visibility Score so low at 31?
Most brands lack the third-party mentions, strong landing pages, and buzz that LLMs pull from training data and retrieval — you’re invisible in direct answers.
Will AI Visibility replace traditional SEO?
Not fully, but it’s the next layer — Gartner predicts 25% search shift by 2026; this measures the LLM leaderboard you’re missing.
