Preserving forecasting history and accuracy
RAND Forecasting Initiative Archive (infer-pub.com) scores 44 out of 100 on Brand Analyzer, placing it in the Early Stage tier among Non-profit brands, Education brands, Other brands, in the 0th percentile of 9322 Non-profit brands.
The RAND Forecasting Initiative Archive is a permanent online repository preserving the final accuracy leaderboards and question records from the now-discontinued RAND Forecasting Initiative, a crowd-sourced forecasting platform. It documents forecaster rankings and the full set of prediction questions posed during the initiative's operation. The archive serves as a historical reference for researchers, forecasters, and analysts interested in forecasting accuracy and crowd-sourced prediction history, maintaining the record after the original platform ceased operations.
| Brand Name | RAND Forecasting Initiative Archive |
|---|---|
| Domain | infer-pub.com |
| Industry | Non-profit, Education |
| Main Competitors | Metaculus (79/100), Good Judgment Open (72/100), Manifold Markets (79/100), Polymarket (93/100), Hypermind |
Moz Domain Authority 23/100 vs category average 51 / leader 95 - limited third-party links, so AI systems rarely encounter mentions of the brand.
No Wikipedia presence was found - a major gap, since Wikipedia is among the most heavily weighted sources in AI training data.
The homepage meta description reads "A permanent archive of the RAND Forecasting Initiative: final accuracy leaderboards and the questions its forecasters answered." (Meta description: 17 words (ideal length). OG description present and descriptive) - this is the summary AI engines are most likely to quote.
Structured data on the homepage: og:title, og:description, og:type. Adding Organization and FAQ schema would further help AI crawlers parse the brand's identity.
AI-crawler access: robots.txt present, no AI bot restrictions - robots.txt controls whether engines like GPTBot and ClaudeBot can read the site at all.
Social footprint: verified profiles on Instagram; no detected presence on X (Twitter), LinkedIn, Facebook, YouTube, GitHub - consistent profiles reinforce the brand's identity across the web.
0 Reddit mentions - community discussion signals real-world reputation to AI models.
Live results from asking a general-purpose AI assistant about the brand, checked September 2026.
When asked "What is RAND Forecasting Initiative Archive?", Claude could not identify the brand as of September 2026. I don't genuinely recognize this specific entity or the website infer-pub.com, though it may be connected to RAND Corporation's forecasting research given the name; it's likely too niche or has too thin a public web presence for me to have reliable training data on it.
When asked "Best brands similar to RAND Forecasting Initiative Archive?", Claude would not surface RAND Forecasting Initiative Archive as of September 2026. I can't confidently recommend something I don't have verified, specific knowledge about.
Common questions people ask in Google, ChatGPT, Claude, Gemini, Perplexity, and other AI search engines.
RAND Forecasting Initiative Archive's main competitors in Non-profit: Metaculus (79/100), Good Judgment Open (72/100), Manifold Markets (79/100), Polymarket (93/100).
Sources: Brand Analyzer scan
The archive offers access to final accuracy leaderboards from the RAND Forecasting Initiative and records of the forecasting questions that participants answered. These are presented as static historical content rather than interactive or ongoing forecasting services, since the original platform is no longer active.
The RAND Forecasting Initiative Archive is a permanent online archive that preserves the final accuracy leaderboards and question records from the RAND Forecasting Initiative, a crowd-sourced forecasting platform that is now discontinued. It exists to maintain a historical record of forecaster performance and the prediction questions used during the initiative's operation, for research and reference purposes.
RAND Forecasting Initiative Archive has low AI-search visibility, scoring 15/100 on Brand Analyzer's AI visibility composite (visibility 0, trust 22, recommendation 32). This estimates how likely AI engines like ChatGPT, Claude, Gemini and Perplexity are to know, trust, and recommend the brand.
RAND Forecasting Initiative Archive scores 32/100 on Brand Analyzer's AI recommendation signal, indicating it is less likely to be surfaced when AI assistants like ChatGPT suggest Non-profit options. Recommendation depends on crawlability, structured data, and category authority.
It is known for being the definitive, permanent record of the discontinued RAND Forecasting Initiative, specifically preserving forecaster accuracy rankings and the historical set of crowd-sourced prediction questions that were part of the platform.
RAND Forecasting Initiative Archive can improve AI discoverability by strengthening structured data (Organization and FAQ schema), maintaining an accurate Wikipedia/Wikidata entity, earning authoritative citations, and keeping content crawlable for AI bots. Brand Analyzer measures these as visibility, trust, and recommendation signals.
The archive is intended for researchers, forecasters, data analysts, and others interested in forecasting accuracy, prediction markets, and the history of crowd-sourced forecasting. These users likely consult it to study past forecaster performance, review historical prediction questions, or reference the RAND Forecasting Initiative for academic or analytical purposes.
RAND Forecasting Initiative Archive scores 15/100 for AI visibility - how well ChatGPT, Claude, Perplexity and Google AI Overviews can discover, identify and cite the brand.
RAND Forecasting Initiative Archive has a weak AI-visibility profile at 15/100 - a proxy for how readily ChatGPT, Perplexity and Google's AI Overviews can recognise and cite it. Its strongest area is recommendation likelihood (32/100) and its weakest is visibility (0/100). It benefits from open access for AI crawlers (GPTBot, ClaudeBot, etc.). The main gaps holding it back: no clear Wikipedia entity to anchor it in LLM training data, no strong Wikidata entry and a low Moz Domain Authority of 23/100. In a live check (September 2026), Claude could not identify RAND Forecasting Initiative Archive from memory, confirming the gaps above.
The score combines seven dimensions - name quality, digital presence, visual identity, messaging clarity, trust foundation, AI discoverability, and brand authority - into a single objective benchmark.
Ranked closest to RAND Forecasting Initiative Archive: Talbot Rice Gallery (44/100), National Museum of the USAF (44/100), Americans for the Arts (43/100), Forest Park Chamber of Commerce & Development (43/100).
A step up - brands to learn from: PLANETARY (56/100), St Kilda South Port Uniting Church (56/100).
Category leader: Change.org (97/100).
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