Firsthand data collection or original analysis producing findings supported by a documented method.
Original research produces findings through firsthand data collection or a new analysis. It can use interviews, observations, experiments or an existing dataset examined in a clearly described way. The originality lies in the work and findings, not in relabeling someone else’s statistics.
Explain how the evidence was gathered and what it covers. Readers need enough context to understand the sample, time period, definitions and important limitations. A result from one business’s records may be informative without representing every business or customer in the market.
Keep findings separate from interpretation. Describe what the data shows, then identify where your explanation involves judgment. An observed relationship does not by itself establish cause. Avoid presenting a hypothetical example or an estimate created for illustration as a completed study.
Takeaway: Research a question your business can investigate responsibly and explain honestly. A modest, well-documented finding is more useful than an impressive-sounding claim that the evidence cannot support.
Example
A delivery company reviews its own recorded missed-delivery reasons over a specified quarter. It can describe the categories and number of records included, along with missing-data limits. It should not turn those results into a claim about all deliveries nationwide without evidence supporting that broader population.
What to check
Preserve the method and underlying records needed to check the analysis, while protecting confidential information. Publish meaningful limitations with the findings. Credit reused datasets and clearly identify any filtering or calculations you performed.
For more detail, see Creating helpful, reliable, people-first content.