Original data: the hidden AI advantage

If you've read annual reports, you know the phenomenon. Three companies write the same thing in different words. "Innovative, customer-focused, quality-conscious." AIs recognise that. They don't cite it.

What they do cite: sentences that exist nowhere else. Numbers only you have. Stories that only happened inside your business.

What original data looks like in practice

Three categories.

Operating numbers from your business. "47 appointments a week." "188 WhatsApp messages a week to Andrea's salon." "63% of our air-conditioning repairs come in the first 14 days of a heatwave." These come from your day-to-day — AIs love them because they're not anywhere else.

Anonymised customer stories. "Mr S., 84, came from hospital after a stroke." With permission, with detail, no name. Why these stories work on aged-care sites, here.

Concrete mini-surveys. "We asked 87 salon clients what they value most about online booking — the answer is not the price." Self-run surveys take 6-8 weeks to collect and get cited for years.

What does not work

Quotes from large studies (Gartner, McKinsey). AIs cite the original source. You don't get co-cited.

Generic industry statistics ("70% of all workshops have staff shortages"). If it's in 50 other industry blogs, it's no longer an original data point.

Self-praise without proof ("We are the best workshop in Manchester"). AIs ignore self-praise.

What you can do today

Write down three numbers from your business that are true and surprising. How many inquiries a week? How many builders' clean jobs on the weekend? Which industry-specific quirks? Every one of these becomes a citation hook. How we mine your data for citation hooks, here. Which concrete sentence structures AIs love, here.