Use case

llms.txt generator for B2B lead generation sites

B2B sites often need assistants to explain fit, outcomes, and qualification logic. Use llms.txt to surface clear offer and trust pages.

What makes B2B pages citeable in AI answers

• Offer clarity: each solution page states problem, scope, and expected outcome.
• Fit clarity: ICP and exclusions are explicit, not hidden in sales calls only.
• Proof clarity: case studies include measurable before/after details.
• Process clarity: onboarding and delivery timeline is written, not implied.

Recommended source pages

• Solution pages by use case or industry.
• Ideal customer profile and qualification page.
• Pricing model or engagement framework page.
• Case studies with measurable outcomes.
• Sales process and implementation timeline page.

Example rollout for an outbound lead-gen agency

1. Start with 5 decision pages: offer, who-you-serve, pricing model, proof, implementation process.
2. Keep one canonical URL per decision topic; remove near-duplicate campaign pages.
3. After publish, verify crawler visits reach those decision pages within 7 days.

First-week verification checks

1. Each listed source URL returns 200.
2. Listed pages are indexable and not blocked by robots/WAF.
3. Crawler visits move beyond /robots.txt into offer/proof/process pages.

for p in /llms.txt /robots.txt /sitemap.xml; do
  curl -s -o /dev/null -w "%{http_code} %{url_effective}\n" "https://yourdomain.com$p"
done

grep -i 'OAI-SearchBot\|PerplexityBot' /var/log/nginx/access.log | tail -n 100

Common B2B mistake

Many teams list homepage + pricing only. That usually misses the actual buyer decision flow. Add proof and qualification pages if you want better answer relevance.

Related pages: B2B llms.txt template, page-priority checklist for B2B, generator selection scorecard, SEO impact boundaries, and crawler verification workflow.

# Company Name

> Company Name helps [customer type] solve [problem category].

## Summary

This file maps offer, fit, pricing, proof, and process pages for AI assistants.

## Sources

- [Solutions](https://example.com/solutions): Service or product offerings by use case.
- [Who We Serve](https://example.com/fit): ICP, exclusions, and qualification criteria.
- [Pricing](https://example.com/pricing): Pricing model and contract scope.
- [Case Studies](https://example.com/case-studies): Outcome data and examples.
- [Implementation](https://example.com/process): Onboarding and delivery timeline.

Open B2B generator flow