A chart of percentages can look convincing while leaving readers unable to understand exactly what was measured. Before comparing Greek businesses, consumers or technologies, research must be designed so someone else can examine its choices and limitations.
A benchmark does not gain value from an impressive headline. It builds value when readers know whom it represents, how people were questioned, when collection took place and when the findings do not apply.
1. Define the population before writing the questions
“Greek businesses” may mean something very different from companies in one industry or organizations of a particular size. Write down who falls within the research question, who is excluded and which group is eligible to answer. The question determines the sample, not the reverse.
2. Describe how participants were found
Record the invitation method, sampling frame, participation criteria and any incentives. If responses come through an open link, a newsletter or a customer list, say so clearly. Do not describe a volunteer sample as a representative picture of the whole country.
3. Test whether questions mean what you think they mean
Ask a few people from the audience to complete the questionnaire and explain how they understood key words. Ask about one idea at a time. Avoid double questions, an implied correct answer, unbalanced options and time periods requiring difficult recall. Keep documented changes from the pilot test.
4. State dates and how incomplete answers were handled
The collection date matters when the environment changes. Note when the research began and ended, how many responses were collected and how many were used in each analysis. Explain what you did with blanks, duplicates or out-of-scope responses. If the sample varies by question, percentages must show the correct denominator.
5. Separate findings from interpretation
First present what participants answered, then what you infer. Do not turn a correlation into a cause. Do not attribute a difference to industry, age or technology without sufficient evidence and a visible sample. On charts, show counts, units and scale, and explain when a subgroup is too small for a conclusion.
6. Give readers a way to repeat the work
Publish the questionnaire, coding method and sample description where feasible. State which data you can share and which is unavailable for confidentiality or participant protection reasons. Add a contact person for questions or corrections.
For DigitalNow, every future Digital Greece Pulse must start with this protocol before collection. This makes clear what can be said, what remains uncertain and how the work can be repeated. Data becomes useful public knowledge when its limitations are published alongside its conclusions.
The benchmark publication protocol is an original editorial methodology developed by DigitalNow. This article does not present research results.