Definition
Original research is content built on data you collected yourself: a survey, a test, an analysis of your own operating records. Unlike a roundup of other people’s statistics, which passes on numbers anyone can find, original research creates a fact that has to be attributed. Attribution is how your name ends up inside an answer.
At a glance
- CategoriesContent
- Related fieldsContent
- DifficultyIntermediate
At a glance
- Original research produces a claim that cannot be verified anywhere except your page, which forces a citation.
- Most companies already hold publishable data in support, sales and operations systems and have never treated it as content.
- The method matters as much as the finding. A number with no stated sample, window or definition is not citable.
- A recurring study beats a one-off, because a figure people check annually becomes a reference point.
A number needs a source and the source is you
Watch what an assistant does with different kinds of claim. Ask it to define a term and you get a confident answer with nothing attributed, because the definition is settled and belongs to nobody.
Ask it for a figure and the behavior changes. It either declines, hedges, or names whoever published the number. It has to, because a specific quantity is checkable and a system that states one without a source is exposed.
That is the mechanic behind citation magnets, and original research is the purest form of it. You are not competing to explain something better. You are supplying the only available answer to a question that requires an answer with a source attached.
Second-hand statistics credit somebody else
A great deal of category content is built on numbers borrowed from someone else’s study. It reads as substantial and it works against you.
When you quote another firm’s figure, you have done the work of making their number more findable. An assistant reading your page extracts the claim and, if it attributes anything, attributes the original publisher. You have written a page whose most valuable sentence points at a competitor or an analyst firm.
The asymmetry is worth sitting with. One decent study of your own gets cited for years across many different questions, because a good dataset answers more than the question it was built for. A steady stream of posts built on borrowed statistics produces nothing anyone needs to name you for.
Run something small before you run something big
The usual mistake is planning an annual industry report and never shipping it. Start smaller than that.
- Pick one question your category argues about and cannot settle. Pricing spreads, delivery times, failure rates, how long something actually lasts.
- Check whether your own systems already answer it. Order records, support tickets, returns data and quote logs are research nobody has to commission.
- Write the method before the finding. What you counted, over what period, excluding what. If you cannot describe it in four lines, the number is not solid enough to publish.
- Publish the headline finding as a standalone sentence near the top of the page, answer-first, with the method beneath it.
- Put the next run in the calendar. The second edition is where the value is, because change over time is a story and a single snapshot is not.
A first study can be one question, one dataset, one afternoon of analysis and one page. That is enough to be cited, and it teaches you whether the bigger version is worth funding.
Frequently asked questions
-
Does original research need a large sample?
No, it needs an honest one. A small sample described accurately is publishable and citable. A large sample with a vague method is neither. State what you measured and how many, and let readers judge. The failure mode is not a modest sample size, it is dressing one up as something bigger.
-
Is a customer survey enough to count?
Yes, if the method is stated. A survey of your own customers is legitimate research as long as you say so plainly: who was asked, how many responded, over what period. Problems begin when a self-selected customer survey gets presented as an industry benchmark.
-
How is this different from information gain?
Information gain is the general property of adding something not already published. Original research is one way of producing it, and the most durable. You can also gain by documenting a process nobody has written down, or answering a question your competitors avoid, without collecting data at all.
-
What does a study like this cost?
Less than most teams assume when the data already exists internally, and considerably more when it does not. Analyzing your own records is cheap. Commissioned panel surveys are not. Start with what you already hold, prove the format earns citations, then decide whether to spend.
-
Is it worth it if nobody reads the report?
Often yes, which is counterintuitive. Research pages tend to have modest traffic and outsized influence, because the finding gets quoted by other writers, by journalists and by assistants. Judge it on how often the number is repeated with your name attached, not on sessions.