Getting picked up by AI chatbots isn't about keywords anymore, it's also about clarity, intent, and usefulness. Here's how we think about it:
1. Write for the way people actually ask questions
Chatbots pull from content that reads like an answer, not a pitch. That means real sentences, not marketing fluff. The clearer your response, the more likely it is to show up.
2. Use structure that helps machines understand context
Headings, bullet points, short paragraphs, it's not just for human readers. This is how language models scan and interpret what's important.
3. Be specific, not generic
Most models don't just pull “the best”, they pull what's most relevant. Long-tail phrases, niche questions, examples that reflect how people really talk all give your content an edge.
4. Surface the signal
If your content answers something important, don't bury it. Put key information up top. Use FAQs or summaries to highlight what matters.
5. Add schema, if it fits
Structured data helps some AI tools recognise what your content is about. It's not a magic trick, but it's a helpful nudge.
6. Prioritise trust
The most useful content is often overlooked if the domain looks unreliable or thin. Authority matters. So does accuracy and design.
7. Think like a system instead of a site
What you publish is just one part. Think about how all your content connects, can someone move through it easily? Can a model?
8. Keep checking what shows up
AI results shift constantly. Stay curious, check where your content appears, and where it doesn't. The gaps tell you what to improve.
We approach builds with this in mind at Pecometer, not just making things work, but making them make sense to both humans and systems.
If you're building for people who rely on AI tools to find what they need, your product has to think that way too.
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