Your AI Visibility Score (0–100) measures one thing: how likely AI assistants are to recommend your product when someone asks about your category.

We believe scoring should be transparent, not a black box. Here's exactly how it works.

Two Layers Working Together

Most AI visibility tools only do one thing — they search the web and count mentions. We do that and something no one else does:

Layer 1 — Real-time Web Scan: We search the live web for your product and analyze what signals AI systems can find about you.

Layer 2 — AI Probe (Direct Query): We literally ask ChatGPT and Perplexity: "Do you know [your product]? Would you recommend it?" — and show you the raw response. This is what real users see.

Layer 1: The 5 Dimensions (0–100 points)

Your score comes from 5 weighted dimensions. Each measures a different signal that AI systems use when deciding what to recommend:

DIMENSIONPOINTSWHAT IT MEASURESHOW TO IMPROVE
Web Presence 25 How many third-party sites mention your product by name? More independent domains = stronger signal. Get listed on directories, blogs, review sites. Each new domain counts.
Source Authority 20 Are you mentioned on sites that AI trusts most? (TechCrunch, Product Hunt, G2, Forbes, etc.) Get featured on high-authority publications. Even a single mention matters.
Recommendation Signals 20 Do "best of" lists, roundups, or reviews explicitly recommend you? Get included in "Top 10 [category]" articles. Pitch bloggers and reviewers.
Community Validation 20 Do real people talk about you on Reddit, Product Hunt, Indie Hackers, or forums? Build genuine community presence. Real discussions beat manufactured mentions.
Competitive Context 15 Do you appear in "vs" comparisons, "alternatives to" articles, or competitive lists? Create comparison content. Get listed on AlternativeTo. Write "vs" blog posts.

Why these weights?

Web Presence gets the most points (25) because it's the foundation — AI can't recommend what it can't find. Competitive Context gets the least (15) because it's a secondary signal; being compared to others helps, but being known at all matters more.

These weights are based on our analysis of what correlates with actual AI recommendations across hundreds of product checks. We adjust them as we learn more.

Layer 2: AI Probe — We Ask AI Directly

This is what makes us different from every other GEO tool.

After calculating your web-based score, we send real queries to AI systems and ask them about your product directly:

Perplexity Probe
We ask Perplexity AI: "What is [your product]? Would you recommend it?" Perplexity searches the web in real-time and cites sources — this shows whether AI can find and understand your product right now.
GPT Probe
We ask ChatGPT the same question. GPT relies more on its training data — this shows whether your product has enough web presence to have been "learned" by the model.

The AI Probe doesn't add to your numeric score — it gives you a separate KNOWN / UNKNOWN status for each AI system. Combined with your 5-dimension score, you get the full picture.

Data Sources

SCORING PIPELINE [Input] Product name + URL ↓ [Step 1] Tavily Web Search API — real-time search, 7+ results ↓ [Step 2] Pattern matching + source classification → Tier 1 sources (TechCrunch, Forbes, G2...) → Tier 2 sources (blogs, review sites) → Community signals (Reddit, PH, forums) → Competitive signals ("vs", "alternative to") ↓ [Step 3] Deterministic scoring (temp=0, same input → same score) ↓ [Step 4] AI Probe — Perplexity API + OpenAI API ↓ [Output] Score (0-100) + 5 dimension breakdown + AI Probe status

Key technical details:

What We Don't Do

Known Limitations (We're Honest About These)

Sample size: Our web scan analyzes the top 7+ search results. This is a representative sample, not an exhaustive crawl of the entire internet. Products with very niche naming may get fewer relevant results.

AI visibility is a lag indicator. When you publish a blog post or get mentioned on Reddit today, it takes 2–6 weeks for that signal to fully propagate through AI systems. Your score today reflects actions taken weeks ago.

We're early. pickedby.ai launched April 5, 2026. Our methodology improves with every product we scan. We update our scoring algorithm based on what actually correlates with real AI recommendations.

Our Own Score: 12 out of 100

We don't hide behind our own tool. We ran pickedby.ai through our own scoring engine:

We're documenting the journey from 12 to (hopefully) much higher. Read the Day 0 story →

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Questions?

If you have questions about our methodology, data sources, or scoring — reach out at hello@pickedby.ai or @pickedbyAI on X.

We believe in transparency. If you think our scoring should work differently, we want to hear about it.