Original research content is associated with stronger self-reported results and can attract shares and links, but no source we found shows that it consistently produces more leads or a better return than comparable standard blog posts. We grade the evidence as mixed for performance associations and weak for any claim that research causes higher leads or ROI.
If you're deciding whether to spend weeks and real budget on a survey or a data study instead of publishing four more standard posts, that grade matters more than the headlines you've probably seen. Original research content marketing has a good reputation, and part of it is earned. The problem is that the reputation rests mostly on marketer surveys and one large but old study of shares and links, and none of those measured what you actually care about, which is qualified leads against cost.
This piece walks through what the evidence says, who ran each study and when, where it falls short, and how you can run a fair test with your own numbers. It stays on marketing performance (leads, engagement, shares, backlinks). It does not cover whether research earns AI citations, which we handle separately.
What the claim says and what counts as original research
The claim is simple: if you publish newly collected or newly analyzed data, you'll get better returns than you would from a regular post. For this article, original research content means public-facing content built around a new dataset or a new analysis, such as a survey, an analysis of your own product data, or a benchmark report. A standard blog post is one that explains or argues something without presenting a new dataset. A post that merely cites someone else's statistics isn't original research.
It also helps to know that the two categories overlap. In a 2018 survey of 698 marketers, reported by MarketingProfs, 77% of the marketers who created research-based content said they published it as blog posts. Smaller shares used infographics (55%) and PDFs (54%). So the useful comparison is research-led content against content that isn't research-led, and the publishing format matters less than it sounds.
One more distinction. The same MarketingProfs report counted three kinds of research: survey-based (58%), analysis of a company's own data (54%), and analysis of third-party data (42%). Newly analyzing someone else's data can produce something new, but it isn't the same effort or the same asset as collecting primary data, so keep that in mind when you read any claim about "original" research.
The evidence for: what the surveys and studies report
Here is what supports the claim, with the source and date attached to each piece.
Orbit Media's 2026 blogging survey
Orbit Media's 2026 blogging statistics report says original research still outperforms, and that publishing original research improves the likelihood of strong results by 50%. This is the most direct recent comparison we found for the question in the title.
It helps to be careful with that number. The report describes a survey of 1,042 content marketers and says the respondents were asked whether their content delivers results. In the report text we could see, there's no breakdown of how many research publishers versus non-publishers said they got strong results, no statement of how respondents were recruited, and no field dates. Orbit itself describes these findings as correlations between strategies and performance. So "50%" can't be turned into a 50-point jump, a lead increase, or an ROI multiple. It's a survey association, and the people who publish research may also be the people with bigger audiences, better distribution, or more mature measurement.
Orbit also notes that fewer marketers are now publishing new research, after its popularity rose for nearly a decade. That could mean the effort is not worth it for many teams, or that it's simply hard. The data doesn't say which.
The 2018 MarketingProfs survey of research-led content
The same 2018 survey (698 marketers, fielded in January and February, conducted by Mantis Research and reported by MarketingProfs) asked those using research-based content what it did for them. Of those marketers, 74% said it helped increase website traffic, 63% said social shares, and 56% said mentions by media, influencers, and bloggers.
These are reported benefits, not audited increases, and there is no group of standard posts to compare them against. The survey did not measure lead volume, conversion rate, revenue, or ROI. A separate 2018 article from Alterra Group, a firm that advocates for research-led thought leadership, describes the same survey (as 700 marketers) and says only 3% felt research failed to meet expectations. That's a perception, and it comes from a source with a stake in the answer.
BuzzSumo and Moz on shares and links
In September 2015, BuzzSumo and Moz published Content, Shares and Links, an analysis of more than one million articles across more than 600,000 domains. It associated research-backed content, along with serious opinion-forming journalism, with higher shares and links in particular content-type analyses.
That's a directional signal and nothing more. "Research-backed" is a broader category than original research, so the report doesn't isolate new data as the reason for the result. It's also old, and it measured shares and links, not leads. The study found essentially no overall relationship between shares and referring-domain links (a correlation of 0.021 across 757,317 articles), and more than 75% of posts in its random sample of 100,000 had zero external links. So even if research content earns more of one, you can't assume it earns the other, and you can't assume either turns into pipeline. The same dataset is a useful reminder that links are rare for most posts, which is one reason a research piece that earns a few can look like a win.
Case examples
Orbit Media's own content gives two examples. In an undated article, Michele Linn says the company's Annual Blogger Survey generated its most social shares and most backlinks of any Orbit content over the prior 12 months. The same article says a guide built from pain points surfaced by Content Marketing Institute research was downloaded thousands of times. There are no counts, no cost, no lead results, and no comparison guide.
An undated SurveyMonkey case story describes a financial firm, LionTree, that surveyed 523 respondents in early 2019 and used the findings in a client newsletter. The story reports client feedback, requests for more information, and higher social engagement, without numbers and without a standard-content control.
Both are fair illustrations of what research can do. Neither is evidence of what it does on average.
The evidence against a confident yes
None of this says research content fails. It says the evidence on content marketing format performance can't carry the strong version of the claim. Here are the specific gaps.
No direct head-to-head study. We didn't find a study that compared research posts and similar standard posts with the same audience, the same distribution, the same measurement window, and the same cost accounting, and then reported attributable qualified leads, revenue, or profit. That's the study the title question needs, and it doesn't appear to exist publicly.
Most of the evidence is self-reported. The surveys ask marketers what they publish and what benefits they believe they saw. That's different from analytics data, and it's different from verified attribution.
Correlation is doing a lot of work. Teams that publish original research may be bigger, better known, or better at distribution. Those traits could explain stronger results without research being the cause. Neither the Orbit association nor the BuzzSumo and Moz content-type findings can separate those factors.
Shares, links, and traffic are not leads. A piece can be widely shared and produce few inquiries. A narrow research asset can help sales without much public attention. The reviewed sources don't settle which is more common.
Selection effects exist. BuzzSumo and Moz built their structured sample on purpose to include well-shared posts, and its database tended to leave out content with no shares. That makes research-backed content look better than it might in a random draw.
Anecdotes aren't averages. Orbit's own results, Alterra's commentary, and the LionTree story are all useful. They're also all stories from people close to the work.
Format performance is a hard thing to compare cleanly, because the format is rarely the only thing that differs between two posts. Topic, promotion, domain strength, and timing all change at once.
What each piece of evidence can and can't tell you
| Source and date | What it reports | What it can support | What it can't support |
|---|---|---|---|
| Orbit Media, 2026 | Research publishing improves the likelihood of strong results by 50% | A survey association | A lead lift, a percentage-point gain, or causation |
| MarketingProfs reporting Mantis Research, 2018 | 74% traffic, 63% shares, 56% mentions among research users | What marketers believe they gained | Measured lift or a comparison with standard posts |
| Alterra Group, 2018 | 3% said research fell short of expectations | A perception from an interested source | Measured performance |
| BuzzSumo and Moz, 2015 | Research-backed content linked with higher shares and links in some analyses | A directional signal about linkability | A claim about original research specifically, or about leads |
| Orbit Media and SurveyMonkey cases, undated | Strong shares, backlinks, downloads, engagement | That research can work in a specific case | An average result or a return |
Read the table as a map of how far each source can carry you. The "can support" column is real. It just stops well short of ROI.
What it costs, and why cost is half of the ROI question
A better-performing asset isn't automatically a better-returning one. Return depends on what the extra performance is worth compared with the full extra cost, and the sources we reviewed give no representative cost for either side. We found no average price for original research and no matched figure for a standard post.
There is one concrete price point from a provider. Mantis Research lists its Research Sprint at a starting price of $17,500, not including response-gathering costs when those are needed, and describes a typical project as taking 8 to 10 weeks. That's one supplier's service offer, not a benchmark and not a budget you need. Orbit Media notes that research can be time-consuming and expensive, and argues that a project can be made more budget-conscious, without giving a universal figure.
So the cost side of your own math for original research content marketing has to be built from your numbers. That includes research design, panel or data costs, analysis, writing, design, any legal or privacy review, distribution, and the internal hours that don't show up on an invoice. It's easy to count only the survey fee and call the project cheap.
How to test it with your own numbers
Since public evidence can't answer this for your team, the practical move is a small, fair test. This is a suggested approach, not a finding from the studies above.
- Pick a baseline. Compare a research-led piece against standard posts aimed at a similar audience and intent. Matched topics and comparable promotion make the result much easier to trust, and anything you can't match should be written down.
- Define a lead before you start. A form fill isn't automatically a qualified lead. Decide in advance what qualifies, and track lead quality and downstream conversion separately.
- Measure three layers. Look at engagement (using whatever time or interaction definition you already use consistently), distribution (shares and referring domains), and business outcomes (qualified leads, opportunities, and revenue where your tracking allows it).
- Use the same window and rules for both groups. Don't compare a research post's lifetime links with another post's first-month leads. Report raw counts and rates with their denominators.
- Count the full incremental cost. Include panel costs, internal time, production, and promotion, not only the writing or survey fee.
- Calculate a simple return. Take the contribution you can credibly attribute to the research asset, subtract its extra cost, and divide by that cost. State the attribution model you used and how uncertain it is. If you can't credibly attribute contribution, report engagement and lead indicators and don't call it ROI.
- Handle repurposing on its own. If you turn the study into social posts, emails, and slides, those derivative pieces shouldn't get full credit for the original asset's result unless you've written down an attribution rule first.
If you run your own survey, quality matters because your result will be read as evidence. The American Association for Public Opinion Research advises ordering questions logically without influencing answers, and notes that general questions often work better before specific ones on the same concept. Pew Research Center describes pretesting as an essential part of questionnaire design. Publishing your question wording, sample, recruitment method, field dates, and the base behind each number makes your findings far easier to trust.
The verdict, and what to do with it
So does original research content work on ROI? Our verdict is that original research may well beat a standard post on attention, and it can be a distinctive asset that's hard for competitors to copy. Whether it beats it on return depends on cost, audience fit, distribution, the conversion path, and what you'd have published instead. The public evidence can't tell you that, and anyone who gives you a clean multiple is going beyond what the sources support.
A reasonable way to act on that depends on where you are.
- If your team is small and your audience is still building, a research project is a large bet on an unproven return. You may learn more from checking which of your standard content metrics already track to leads before you commit to a survey.
- If you already have first-party data (product usage, customer records, support patterns), an analysis of what you own is usually cheaper than fielding a new survey and may be where the first test belongs.
- If you already publish steadily and measure leads properly, run one research-led piece against your usual posts using the steps above, and let your own numbers decide the next one.
If you're still working out which topics are worth a research-level effort, DeepSmith's Content Map shows where competitors publish and you don't, and Opportunity Agents return ideas with the data point that justifies each one, which gives you a way to choose a research angle on evidence. You can start a free trial and see it on your own site.
What would change this verdict
We'd move from mixed to stronger if independent comparisons appeared that matched topics and promotion, declared their outcomes in advance, tracked actual qualified leads and revenue, and reported full production costs. Until better content marketing format performance data exists, the honest position is that original research is a reasonable bet with an unknown return, and your own test is the best evidence you'll get.
