Part 1 tackled those all-important third-party citation signals, while Part 2 made the case for publishing original data: It is the strongest single predictor of page originality, and the bar to earning visibility/authority via this play is low.
This memo has more ammo to back up your use of proprietary data in content creation.
Publishing the number is necessary. But it’s not always what gets cited. We pulled Gauge’s citation data to find out what AI actually rewards when it comes to publishing first-party data, and the answer is narrower and more useful than “original data wins.” (Although original data does, in fact, win.)
AI rewards one format almost to the exclusion of everything else: The benchmark that answers “which is best.”
First-party research is scarce and punches above its weight
We worked from Gauge’s cited-URL set: 301 live pages that AI systems cited (316 unique prompts across 7 verticals), carrying 1,075 citations between them.
After a full URL audit, only 8 of those 301 pages qualified as primary research, meaning the original source of the data and methodology are on the page… rather than a writeup of someone else’s numbers.
Eight pages out of 301 is 2.7% of the set. Those same 8 pages earned 90 of 1,075 citations, or 8.4% of citation volume. First-party research shows up rarely, then over-indexes 3x on citation share when it does.
The cleaner way to see it is density.
Primary research averaged 11.3 citations per page. Everything else averaged 3.4. A primary-research page was 3.3x as citation-dense as a non-primary one.
Primary research compounds citations.
This is the same shape as the information gain finding discussed in Part 2, viewed from the AI side instead of the classic 10 blue links side.
There, original data correlated with page originality more than any other trait. Here, original data correlates with citation density. Both point the same direction: The number only you can produce is the lever.
Original research wins when the question has a benchmark
Here’s where the “original data wins” filter gets sharper.
The 90 primary-research citations are not spread across the 8 pages evenly, and they are not spread across topics evenly.
75 of the 90 came from one cluster: cloud data warehouse benchmarks. Fivetran’s warehouse benchmark alone took 44 citations, just under half of every primary-research citation in the set. (More on that below.)
Reality: Strip the benchmark cluster out and first-party research barely registers in the citation set. The win is not “we published original data.”
The win is “we published a benchmark that answers a buying comparison,” and almost nobody builds one. (“Benchmark” meaning you measure a set of named things against each other on a specific yardstick, and publish the results as numbers.)
Original research is most effective when it is packaged in a way that directly…
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