Tip 25 of 31: Explain How You Produced Your Numbers

Data without method is just a number. When you publish your own research or results, documenting how you produced the figures turns them from unsupported claims into evidence readers can assess.

Why Methodology Matters

Suppose you publish an article stating that the average recruitment agency fills a permanent role in 24 days. A reader wants to know: how many agencies were in the study? Which sectors and countries? What counts as “filled”? Was the average the mean or the median?

Without those answers, the figure lacks essential context. Readers cannot properly assess how it was calculated, how widely it applies or whether it can be compared fairly with other findings.

What to Include

A methodology section does not need to be long. For most business content, covering how the data was collected, the sample or scope, how calculations were made and any limitations is enough. A short paragraph is often sufficient to make the difference between a number readers dismiss and one they can understand, assess and reference.

This Is What Creates Citable Evidence

One of our clients generates £45,000 in placement fees from their website in a single month. That number is specific, time-bound and drawn from a documented client result. It is not presented as a typical outcome for every recruitment business. That context makes the claim more transparent, credible and useful. Apply the same standard to your own data.

Up Next

Tip 26 of 31 covers one of the most valuable things you can do for AI visibility: publish useful information that nobody else has.

Frequently Asked Questions

What if my data is based on a small sample?

State the sample size and relevant context clearly. For example, “Based on an analysis of 12 client websites over a six-month period” allows readers to judge how widely the finding may apply. A small sample with honest limitations is more useful than a broad claim with no supporting information.

Does every statistic need a methodology section?

Every original statistic should include enough information for readers to understand how it was produced. Widely reported or independently verifiable figures do not need a methodology written by you, but they should be attributed and linked to their original or most authoritative available source.

Can I publish data that reflects positively on my own services?

Yes, but disclose where the data came from and any relevant limitations. For example, “Based on an analysis of 100 RecruiterWEB client websites” makes it clear that the figures come from your own client base rather than an independent industry-wide study. Readers can then assess the evidence with that context in mind.

How does documenting methodology help with AI citations?

A documented methodology gives readers and automated systems more context for interpreting a figure. It can show the scope of the research, how the calculation was made and what limitations apply. This can make the information more useful and credible as source material, although it does not guarantee that an AI system will select or cite the page.

What about qualitative findings? Do those need methodology too?

Yes, in proportion to the claim. Qualitative findings based on interviews, case reviews or professional experience should explain their basis. For example, “Based on our experience building websites for 667+ recruitment agencies and executive search firms since 2004” gives readers useful context for an experiential conclusion without presenting it as a controlled quantitative study.

Darren Revell, Co-Founder, RecruiterWEB