Turning your own data into press coverage

Newsrooms need figures and have almost no capacity to generate them. A business with operational data holds something genuinely valuable to them.

What you already have

Every one of these exists in a normal business system and none of them is published.

Making it publishable

1. Aggregate and anonymise. No individual customer identifiable, no commercially sensitive detail.
2. State the sample. How many, over what period, from where.
3. State the method. How it was counted, what was excluded.
4. State the limitation. What the data does not show.
5. Do not over-extrapolate. Your 340 installations describe your 340 installations, not the national market.

Points three to five are what separate data that credible outlets will use from data they will not.

The angles that work

Change over time. A figure now against a figure two years ago is a story. A single current figure usually is not.

Regional comparison. Differences between districts in your own operating area are exactly what regional media want.

Seasonal or weather-linked. Predictable and reusable annually.

Counter-intuitive findings. Something that contradicts the assumption is the strongest form.

Packaging it

A short document: the headline finding, three supporting figures, the method, one chart, and a quotation from a named person explaining what it means.

Offer the underlying figures to any journalist who asks. Willingness to share the data is what establishes credibility.

The recurring version

The strongest form is data published on a regular schedule, so quarterly or annually. It becomes a reference point, journalists begin to expect it, and each edition builds on the last.

A regional business publishing a quarterly index of something it measures becomes the source that gets called, which is worth considerably more than any single story.

The internal check

Before publishing, consider: does this reveal anything commercially sensitive, does it expose any customer, does it create a claim you would have to defend, and would you be comfortable if a competitor analysed it.

Most operational aggregate data passes all four. The exercise takes ten minutes and prevents the occasional expensive mistake.