What is the best way to read the null result? | Trakkr Research
Read p=0.85 as a non-significant test in the top 5,000 cited domains. The full sample returns p<0.001 with reported r=-0.065. Neither establishes that the causal effect is exactly zero.
Methodology: Built from HTTP scans of 37,894 AI-cited domains, linked to 337,362 citations and 882 citation snapshots in the Trakkr corpus.
Direct Answer
Read p=0.85 as a non-significant test in the top 5,000 cited domains. The full sample returns p<0.001 with reported r=-0.065. Neither establishes that the causal effect is exactly zero.
What this means
This answer matters because it turns a study finding into an operating rule teams can use when they decide what to publish, refresh, or measure next.
Evidence table
| Metric | Value | Why it matters |
|---|---|---|
| Top-5,000 Mann-Whitney p-value | 0.85 | Subset of the top 5,000 cited domains; not the full-sample test. |
| Full-sample Mann-Whitney p-value | <0.001 | Full 37,894-domain sample. The public JSON rounds this value to zero. |
| Full-sample reported effect size r | -0.065 | Small reported magnitude; not an estimate of causal citation lift. |
| Adoption rate | 13.3% | Domains with llms.txt in the study. |
| Domains scanned | 37,894 | AI-cited domains scanned for llms.txt. |
Frequently Asked Questions
What is the best way to read the null result?
Read p=0.85 as a non-significant test in the top 5,000 cited domains. The full sample returns p<0.001 with reported r=-0.065. Neither establishes that the causal effect is exactly zero.
Which numbers from The llms.txt Effect matter most here?
Top-5,000 Mann-Whitney p-value: 0.85. Subset of the top 5,000 cited domains; not the full-sample test. Full-sample Mann-Whitney p-value: <0.001. Full 37,894-domain sample. The public JSON rounds this value to zero.
What should a team do next?
Treat llms.txt as an optional housekeeping file, not a primary citation-growth lever. Prioritize answer quality, source coverage, and page structure before spending disproportionate effort on llms.txt. If you do publish llms.txt, measure discovery and crawl behavior directly instead of assuming it improved citation performance.
What to do next
- Treat llms.txt as an optional housekeeping file, not a primary citation-growth lever.
- Prioritize answer quality, source coverage, and page structure before spending disproportionate effort on llms.txt.
- If you do publish llms.txt, measure discovery and crawl behavior directly instead of assuming it improved citation performance.
Related pages
Continue through the same study cluster.
- what should teams do after seeing the llms txt data - Related answer page
- does llms txt look like a sector specific behavior more than a universal standard - Related answer page
- median citations are identical with and without llms txt - Related fact page
- llmstxt adoption by sector tracker - Related tracker page
Data & Sources
- The llms.txt Effect - Flagship study behind this page
- Page JSON - Machine-readable companion file