The problem this solves
Look at what AI assistants cite and one content type keeps recurring: the page with the number. Benchmarks, rates, averages, costs - when a question has a quantitative shape, engines reach for the source that states a figure plainly and shows where it came from. Most brands publish opinion and product copy; the statistics that answer their own category questions sit unpublished in their data or scattered across paywalled reports.
Owning a number is the most durable citation there is. Opinion pages compete on prose quality forever; a well-methodologized figure gets cited because there is nothing else to cite, and every citation reinforces the page as the canonical source until displacing it requires better data rather than better writing. The work is identifying which numbers are actually being asked for, checking your data can honestly support them, and packaging each one so a machine can lift the figure with confidence and attribute it cleanly.
How the mission runs
- Find the quantitative questions. Keyword Intelligence and live answer sampling surface the questions in your category with a numeric shape - how much, how long, what percentage, what does it cost - and grade how well current answers source their figures.
- Match numbers you can own. Against that demand, the mission maps what you can credibly publish: aggregates from your own data, original analysis of public data, or a small survey design. Every candidate stat is checked for a real methodology behind it.
- Design the statistics page. Each stat gets the citable treatment: the figure stated in one liftable sentence, the methodology note beside it, a dated update cadence, and structure that lets an engine quote the number without misreading it.
- Deliver the publish plan. A Notion plan lands with the prioritized stat list, the page design, the methodology write-ups, and the update calendar - because a stale benchmark loses its citations to whoever publishes a fresher one.
The prompt
This is the exact objective the agent receives. Swap the obvious placeholders for your own domain, segment or channel and run it as-is from the console, Slack, or the API.
What comes back
A publish plan for a statistics program: the quantitative questions your category asks with weak current sourcing, the specific numbers you can own with defensible methodology, page designs built for machine quotation, and the update cadence that keeps the citations yours. One well-kept benchmark page can outperform a year of opinion posts on citation share.
Make it yours
- Start with a single flagship benchmark and build the program around its success rather than launching ten stats at once.
- Pair each stat with a short methodology post - engines cite the number, skeptical humans click through to the method.
- Refresh the highest-cited stat quarterly and timestamp it visibly; freshness is half the defense once rivals notice your citations.
Frequently asked questions
What if our data is too small to be authoritative?
Authority follows methodology more than scale. A clearly bounded figure - median across N anonymized accounts, dated, with the caveats stated - beats an unsourced industry number, and engines reward the page that shows its work. The plan sizes claims to what your data honestly supports.
Why do engines favor statistics pages so heavily?
Numbers are verifiable, compact, and safe to quote: an engine answering a quantitative question wants a source that states the figure cleanly and explains its origin. Prose answers require judgment; a well-published stat requires only attribution, and attribution is the citation.
Does this replace our other content work?
It anchors it. Statistics pages earn the citations, and the surrounding guides and comparisons inherit authority from living on the domain the engines already quote. The plan positions the stat pages as the citation spine the rest of the content hangs from.