Publishing Original Data Studies That AI Assistants Cite

You cannot submit a study into an AI model’s training data, and no service can sell that. What you can do is publish original, well-documented data on your own site, get it referenced by others, and make it easy to read. Studies like that are often quoted by journalists, and AI assistants that browse the web regularly cite them as sources.

Why Original Data Works

AI assistants answer questions like “What is the average cost of a kitchen renovation in 2026?” or “How long do B2B sales cycles take for SaaS?” by looking for sources with specific numbers. If you are the original source of a number, other articles link back to you, and assistants that show citations, like Perplexity, often point to the origin. Rewritten opinion pieces do not have this effect, because they say what many other pages already say.

Picking a Study Topic

Good topics sit where three things meet:

• Data you actually have or can collect: anonymised order data, a customer survey, public records you analyse, or pricing you gather by hand.
• A question people ask: check what customers type into AI assistants and search engines about your field.
• A gap: no recent, trustworthy number already exists.

Example: a moving company could survey its own jobs to report how many hours an average two-bedroom move takes in different cities. A payroll software firm could analyse anonymised data on when small businesses run payroll.

How to Publish It So It Gets Cited

1. Lead with the key findings. Three to five clear sentences at the top, each with one number.
2. Explain the method. Sample size, dates, how data was collected, what is excluded. This is what makes the study trustworthy to editors and readers.
3. Use HTML tables, not only charts. Text in an image is hard for AI tools to read. Put the numbers in a table as well.
4. Give each finding its own heading so a single section can be quoted on its own.
5. Date it and plan updates. An annual refresh keeps the page relevant.
6. Name the authors and their roles, with a short bio.

Getting the Study Seen

A study with no links rarely gets cited. Send it to trade publications and journalists who cover your field, with one strong finding in the subject line. Share it with associations and communities where it is genuinely useful. Offer the data for others to use with credit. More ideas are in our guide to data-driven studies for authority.

Common Mistakes

• Tiny or biased samples presented as industry facts. Editors notice, and it damages trust.
• Gating the whole study behind a form. Assistants and journalists cannot read what they cannot reach. Gate the extended report if you must, but keep findings public.
• Calling it “research” when it is a sales page. Keep the product pitch short and separate.

For longer formats, see whitepapers and research for AI.

How Keboost Helps

Keboost shows which questions in your field AI assistants are asked and which sources they cite today, which helps you choose a study topic with a real gap. We also help you turn findings into focused content and distribute it so it can be found. We cannot place anything into AI training data or promise citations. Run a free AI visibility check to see where you stand, or compare our plans.