Data And Original Research

data-and-original-research

The original-data content type — find a question inside a data void, run a sound method, analyse it honestly, voice the one finding that travels, and engineer it for citation. A study people have to cite; the format writers turn it into cuts, WoopSocial publishes, and recurring studies map into the content-calendar.

The POV: own a number and the internet has to come to you

Most content is undifferentiated — ~94% of published pages earn zero external links (per Backlinko). Original data is the rare exception: publications link to stories, not products, and a data finding is a story. It's also the #1 GEO asset — adding statistics is among the strongest levers for AI-answer visibility (per the Princeton/KDD GEO study), and original data is statistics nobody else owns. Brands skip it because it's harder than a listicle — which is exactly the moat. The catch: a study is worth nothing the moment one number is wrong. Rigor isn't pedantry; it's the entire value. So the skill is knowing what to study, how to get real data, and how to make the finding impossible not to cite — never inventing it.

Read these first

1. brand-profile — the proprietary data/angle you actually own.
2. audience-research — the question your audience (and journalists/AI) would cite.

The framework: PROVE

(Depth: references/the-prove-framework.md.)

• P — Pick a question inside a data void: a claim worth proving where good data doesn't exist and people

would cite the answer; advantage order = proprietary data > recurring niche survey > public-dataset analysis.

• R — Run a sound method: define population, sample frame, target n, recruitment, and neutral (non-leading)

questions before collecting; the agent designs, the human/tool fields it.

• O — Observe honestly: real data only; never invent or AI-synthesize data points; no p-hacking or

cherry-picking; disclose n, dates, method, limitations; small n = directional, not "most people."

• V — Voice the one finding that travels: the surprising-but-defensible headline stat (X% of Y do Z),

supported and never inflated (38% ≠ "nearly half"); one hero number, 2–3 supporting.

• E — Engineer for citation, then distribute: report page with visible methodology + date + "Last Updated"

stamp + charts + a copy-paste stat box with attribution link; atomize into cuts → the format writers; pitch journalists; seed across publications (the citation multiplier); WoopSocial publishes.

The reality (verify-quarterly)

Data-led content is the backbone of digital PR (~94.8% name it their primary tactic; original data ~+41% media coverage — per BuzzStream); data studies attract ~3.2× more links than opinion/how-to (per Backlinko via Searchlab). For AI search: adding statistics can lift AI-answer visibility ~30–41% (Princeton/KDD GEO study, cited — attribute); brand mentions can correlate with AI visibility more than raw links (Ahrefs ~75k-brand analysis); distributing across many publications multiplies citations; ~50% of AI-cited content is survey > public dataset > experiment), designed before collection (population, sample frame, n, neutral questions), analysed honestly (no p-hacking, no cherry-picking, limitations disclosed, small n framed as directional), with one surprising-but-defensible headline stat that's supported and never inflated; engineered for citation (visible methodology + date + "Last Updated" stamp + charts + copy-paste stat box with attribution link), atomized into cuts routed to the right format writers, pitched/distributed across publications, and published via WoopSocial; measured on referring domains/mentions/AI-citations/referral traffic/saves rather than likes; YMYL, privacy/consent, and conflict-of-interest handled; nothing fabricated; and correctly distinguished from educational-content-and-how-to, analytics-and-reporting, competitor-analysis, and trend-jacking.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: social-media-skills
• Source: social-media-skills/skills
• License: MIT
• Homepage: https://social-media-skills.com

Install and usage instructions live in the source repository linked above.