A quarterly study built from 500+ anonymised enterprise domain audits. Benchmarks, structural shifts, cross-model data. Free of charge, but available in limited supply — 600 slots per edition.
No newsletter. Only the report. Delivered on publication date.
18–24 pages of dense analysis — no filler, no marketing pitch. Every number from our own audit cohort, documented methodology, reproducible KPIs.
Absorption rate by industry and query type. Quarterly delta, 12-month trend.
The most-cited domains in GPT, Claude, Gemini and Perplexity — by industry.
Share of Model across models, markets and languages. DACH, UK/US, TR, ES, AR.
RDI median values by industry. Negative peaks, recovery periods, patterns.
GPTBot, ClaudeBot, PerplexityBot — frequency, status codes, 429 dead zones.
Which schema types correlate with which citation rates — adjusted for domain authority.
Wikidata coverage of top brands by industry. Gaps, opportunities, timelines.
Three prioritised actions per industry, based on the quarter's data.
Every prompt is executed against GPT-4o, Claude Sonnet 4.6, Gemini Pro and Perplexity Sonar — five times per model to control for statistical variance. Brand mentions are extracted with a spaCy-based NER pipeline; sentiment with a verified classifier. All raw data is stored in BigQuery, analysis in Python notebooks with reproducible versioning. Every published number has a documented source.
The AI Search Index is published quarterly. Every edition remains permanently accessible to existing readers.
A one-year retrospective since rollout. Which industries lost the most traffic, which gained through citations — and why.
Wikidata coverage of the DAX 40 and its correlation with LLM citation. The brands with anchored entities get cited more.
MVG values across 15 language regions. Which markets are most underrepresented and why the corpus asymmetry is structural.