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Publish one piece of original data or research

1-3 weeksImpact: highEffort: high

Publishing one piece of original data or research means producing something genuinely new — a survey, an analysis of your own real business data, or aggregated public data analyzed in a new way — rather than another summary of others' findings.

Original data is inherently more citable and shareable, since anyone writing about your topic eventually needs a source to cite, and you become that source.

The full picture

Original research occupies a genuinely different tier of content value than commentary or summary content, for a structural reason that's easy to overlook: virtually every piece of content discussing a topic eventually needs to cite a source for any specific claim or statistic it makes. Commentary content cites other commentary, which eventually traces back to some original source. Original research is that source — the terminus of the citation chain rather than another link in it, which is precisely why it accumulates backlinks and citations with a degree of passive, ongoing momentum that other content types rarely achieve.

Identifying a genuine data gap requires distinguishing between a question with no existing answer and a question with no existing good answer — both represent real opportunity, but they require different approaches. A genuinely unanswered question means you're producing entirely new knowledge for your field. A poorly-answered question — where existing data is outdated, based on too small a sample, or methodologically weak — means you're producing a genuinely better source, which is often a more achievable and still valuable project than starting from complete scratch.

The methodology transparency requirement is not a bureaucratic formality — it's the actual mechanism that makes original research citable and trusted in the first place. A statistic presented with no visible methodology is easy for anyone evaluating whether to cite it to dismiss, since there's no way to assess whether it's reliable. The same statistic presented with a clear, honest account of how it was gathered and analyzed — even an imperfect methodology, honestly disclosed — earns real credibility, because it gives anyone evaluating it the information needed to judge its reliability for themselves.

The realistic scope for most businesses doing this for the first time is smaller than "conduct a major industry study," and that's genuinely fine. A survey of your own existing customer base, honestly analyzed and reported, or a careful analysis of your own business's operational data, anonymized and generalized appropriately, both qualify as original research in the sense that matters here — data that didn't exist in public, citable form before you published it. The credibility comes from the honesty and clarity of the methodology, not from the scale of the underlying study.

How to do it

  1. 1
    Identify a genuine data gap in your space
    A question people in your field want answered but no one has published solid data on.
  2. 2
    Collect real data
    A survey, your own business data analyzed and anonymized appropriately, or public data analyzed in a genuinely new way.
  3. 3
    Publish with transparent methodology
    How you collected and analyzed the data — this is what makes it credible and citable.
  4. 4
    Make it easy for others to reference
    Clear charts, a summary of key findings, straightforward attribution guidance.

Common mistakes

How you will know it is done

Original research or data is published with transparent methodology.

Track this in your hive

Mark it complete once you have genuinely done it — H.I.V.E. tracks your full strategy progress in one place.

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