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Module 04 / Lesson 23 · Read, apply, check
Choose evidence that adds real information and describe its method, scope and limits honestly.
Originality can come from a useful observation, a carefully explained experiment, a qualified interview or a new analysis of reliable data. It does not require a large survey in every article. Begin with an unanswered customer question and identify the evidence that would improve the decision, rather than collecting numbers merely to create an impressive headline.
Explain the sample, dates, selection process, measurement and relevant exclusions. Readers need enough context to judge whether a finding applies to their situation. A convenient customer sample can provide useful insight without representing an entire industry. Label hypothetical examples clearly and never present an illustrative chart as a measured result.
Choose a contributor with relevant knowledge or direct experience of the specific subject. Ask how they reached the conclusion and what might change it. Check factual claims independently where possible. A respected title in one field does not automatically qualify someone to make confident statements about a different technical or high-stakes topic.
Show the method, supporting material and distinction between observation and interpretation. Use an original visual when it clarifies the evidence, with meaningful labels and an equivalent explanation. Preserve the record behind the published claim so corrections can be made. A unique dataset loses credibility if its methodology is hidden or its conclusions exceed what was measured.
“This lasts longer.” No method or source lets the reader inspect the conclusion.
A relevant primary source supports a clearly scoped statement.
Conditions, measurements and limitations explain what was actually observed.
A suitable method, sample and analysis support a conclusion no broader than the evidence.
Hypothetical example: a customer-support software company studies recurring onboarding questions from its own service records. It removes private information, defines the time period and groups questions using a documented method. The resulting article explains which issues appeared in that customer sample and includes an operations expert’s interpretation. It does not claim to describe every software buyer. The team adds a practical checklist based on the observed problems and labels a demonstration chart as illustrative where it uses invented values. An editor can now assess both the useful finding and its limits. The work adds more value than rewriting several competitor articles while calling the result original research.
A marketer asks an AI system to invent a survey percentage and attaches a generic expert biography to the article. The result may sound authoritative, but neither the data nor the stated review exists. Replacing the invented number with a properly attributed existing study, or conducting a modest transparent investigation, is a substantive correction. Better design cannot turn fabricated evidence into research.
Misconception: original research must prove a universal conclusion. Correction: a narrow observation can be valuable when its scope is clear. Overstating generality makes the evidence less useful because readers cannot reliably decide where it applies.
Research involving people or confidential records may require consent, appropriate permissions and specialist review. Use aggregated or appropriately handled information, and do not expose private details simply to make a marketing asset appear more credible.
Do this today · 35 minutes
Choose one unanswered customer question and outline a feasible evidence plan. Specify the source, collection method, limitations and useful output. Write one sentence the evidence could support and one broader claim it could not support.
Use an authorized page or campaign relevant to this lesson, or work entirely from the illustrative sample below. Record proposed changes as drafts until they are approved and implemented.
Support tickets repeatedly ask which dimensions cause failed furniture deliveries; the company has anonymized operational records.
Before: A small internal sample is described as a universal industry fact.
After: The sample’s scope is explicit and supports a bounded practical resource.
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Check the method before collecting data and retain enough documentation for another person to inspect the conclusion.
Before you move on
A company analyzes support questions from its own customers and finds a recurring onboarding problem. The marketing team wants to call it a global industry survey. The sample was not designed to represent the industry. How should the article present the finding and still add useful value?
Next lesson →Google: Helpful, reliable content
Lesson edition 2 · References reviewed 14 October 2026 · Practical exercise reviewed 15 October 2026. Examples are illustrative teaching scenarios.
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