Playbook
llms.txt for AI discovery for mobile attribution vendors
A practical playbook for UA marketers to improve llms.txt—with checks, fixes, and measurement.
Why llms.txt matters in mobile attribution
UA marketers cannot win AI shortlists on content alone if llms.txt is broken. llms.txt is a root-level orientation file that summarizes your product, key URLs, and citation preferences for AI systems—without replacing crawlable pages.
In mobile attribution, common blockers include: Glossary and FAQ pages are absent; Brand mentions are generic without citations; Open-web retrieval prefers aggregator domains. Marketplace listing pages can outrank your homepage in AI answers if your product facts live only behind auth.
What to check
- /llms.txt present at the site root with an accurate product summary
- Optional /llms-full.txt for longer documentation
- Links to pricing, docs, and canonical product pages
- Consistency between llms.txt claims and live page content
mobile attribution-specific page priorities
- Docs hub — ensure this URL is crawlable HTML with facts assistants can quote when answering “best mobile attribution tools for teams evaluating options”
- Customer stories — ensure this URL is crawlable HTML with facts assistants can quote when answering “best mobile attribution tools for teams evaluating options”
- API reference — ensure this URL is crawlable HTML with facts assistants can quote when answering “best mobile attribution tools for teams evaluating options”
Fix guidance
Ship a truthful llms.txt, keep it updated after launches, and still maintain crawlable HTML for every URL you list.
Deep dive: llms.txt for AI discovery. Industry hub: AI visibility for mobile attribution vendors.
Measure with BatSignal
- Run a Visibility Scan on your mobile attribution site
- Inspect the pillar tied to llms.txt
- Ship the prioritized fixes and copy-paste deliverables
- Re-verify within 30 days to confirm movement
Related
- mobile attribution hub
- crawl access for mobile attribution
- content readiness for mobile attribution
- ChatGPT citations for mobile attribution
- robots.txt AI policy for mobile attribution
- llms.txt for AI discovery
- All industries
FAQ
What is llms.txt for mobile attribution vendors?
llms.txt is a root-level orientation file that summarizes your product, key URLs, and citation preferences for AI systems—without replacing crawlable pages. For mobile attribution, this shows up when buyers ask “best mobile attribution tools for teams evaluating options” and when AI crawlers attempt to fetch your commercial pages.
How do we improve llms.txt?
Ship a truthful llms.txt, keep it updated after launches, and still maintain crawlable HTML for every URL you list. Industry-specific must-have pages include Docs hub, Customer stories, API reference.
How does BatSignal score this?
Content readiness / discovery signals. See the [methodology](/methodology) and related guide: /guides/llms-txt.